-
If you are the owner or a member of this project, use the
MPContribs python client
and the code snippet below to add data to this project. Full examples for other
projects can be found
on GitHub.
-
If you don't have permissions to manage or view the data in this project, feel free
to reach out to the
owner
to become a member of the
{{name}}
group.
from mpcontribs.client import Client
client = Client(
host="{{API_CNAME}}",
apikey="{{ request.META.HTTP_X_CONSUMER_CUSTOM_ID }}",
project="{{name}}"
)
client.init_columns({"a": "eV", "b.c": None, "b.d": ""})
contributions = [{
"identifier": "mp-4",
"data": {
"a": "3 eV",
"b": {"c": "hello", "d": 3}
},
"structures": [`pymatgen.core.Structure`, ...],
"tables": [`pandas.DataFrame`, ...],
"attachments": [`pathlib.Path`, `mpcontribs.client.Attachment`, ...]
}]
client.submit_contributions(contributions)


{% extends '__base.html' %} {% block title %} Overview | {{ block.super }} {% endblock %} {% block content %}
The Centre for Computational Science and Engineering (CCSE) is pleased to have hosted the 1st Computational Science and Engineering Symposium at the University of Toronto Institute for Aerospace Studies (4925 Dufferin St, Toronto, ON) from May 21—22, 2019. The event was a big success and we wish to thank all who attended.
| Day 1 (May 21, 2019) | ||
|---|---|---|
| 08:45-09:00 | Opening Remarks | David Zingg |
| 09:00-10:00 | Invited Speaker | Jan Hesthaven |
| 10:00-11:00 | Invited Speaker | Stephen Wright |
| 11:00-11:15 | Coffee Break | |
| 11:15-12:15 | Invited Speaker | Alán Aspuru-Guzik |
| 12:15-13:15 | Lunch | |
| 13:15-14:15 | Invited Speaker | Eleuterio Toro |
| 14:15-15:15 | Invited Speaker | Ann Almgren |
| 15:15-15:30 | Coffee Break | |
| 15:30-16:30 | Invited Speaker | Alessandro Veneziani |
| 16:30-17:30 | Roundtable Discussion | |
| 18:30 | Event Dinner | Terra Restaurant [Map] |
| Day 2 (May 22, 2019) | ||
|---|---|---|
| 08:45-09:00 | Coffee | |
| 09:00-10:00 | Invited Speaker | Rémi Abgrall |
| 10:00-11:00 | Invited Speaker | Fariba Fahroo |
| 11:00-11:15 | Coffee Break | |
| 11:15-12:15 | Invited Speaker | Steven Johnson |
| 12:15-13:15 | Lunch | |
| 13:15-14:15 | Invited Speaker | Anthony Patera |
| 14:15-15:15 | Invited Speaker | Nobuyuki Umetani |
| 15:15-15:30 | Coffee Break | |
| 15:30-16:30 | Roundtable Discussion | |
| 16:30-16:45 | Closing Remarks | David Zingg |
Title: High order approximation of compressible flows: some new results
Abstract:In this talk, I will describe two classes of methods for the simulation of compressible flows (perfect gases, or complex with phase transition). The first one uses a high order finite element like method with hybrid meshes. It can satisfy, besides local conservation, satisfy several constraints like entropy conservation (if needed), local conservation of the kinetic momentum, etc. The second one, with only one dimensional preliminary results, uses a kinetic formulation of the equations and can run at CFL=1 on regular meshes, bearing some similarities with LBM methods. In both cases the methods are high order (i.e. higher than second order) in time and space.
Bio:Professor Abgrall has been awarded an Advanced Research Grant from the ERC in 2008 and an Inria International Chair for the period 2019-2024. He is editor in chief of the Journal of Computational Physics, and associate editor of several international journals, including the Computers and Fluids, the Journal of Scientific Computing. His research is about the design of very high order schemes, using unstructured meshes, for hyperbolic problems, as well as efficient algorithms for the simulation of compressible materials (single fluids, multiphase, interface problems, compressible solids). He is also interested in model reduction for these problems.
Title: Low Mach Number Modeling
Abstract:Low Mach number equation sets approximate the equations of motion of a compressible fluid by filtering out the sound waves, which allows the system to evolve on the advective rather than the acoustic time scale. Depending on the degree of approximation, low Mach number models retain some subset of possible compressible effects. In this talk I will discuss low Mach number models for reacting and stratified flows arising in combustion, astrophysics and atmospheric modeling.
Bio:Ann Almgren is a senior scientist in the Computational Research Division of Lawrence Berkeley National Laboratory and the Group Lead of the Center for Computational Sciences and Engineering. Her primary research interest is in computational algorithms for solving PDE’s in a variety of application areas. Her current projects include the development and implementation of new multiphysics algorithms in high-resolution adaptive mesh codes that are designed for the latest HPC architectures. She is a SIAM Fellow and the Deputy Director of the U.S. DOE Exascale Computing Program's AMR Co-Design Center.
Title: Quantum algorithms for near-term quantum computers
Abstract:We are in the NISQ era of quantum computing. NISQ stands for "Near-term intermediate-scale quantum computer". These machines are not error corrected and have of the order of tens of quantum bits. In this talk, I will discuss a family of quantum algorithms that are promising applications for these devices that my group and others have developed. I will discuss potential applications for the simulation of chemistry and materials and quantum machine learning.
Bio:Alán Aspuru-Guzik's research lies at the interface of computer science with chemistry and physics. He works in the integration of robotics, machine learning and high-throughput quantum chemistry for the development of materials acceleration platforms. These "self-driving laboratories" promise to accelerate the rate of scientific discovery, with applications to clean energy and optoelectronic materials. Alán also develops quantum computer algorithms for quantum machine learning and has pioneered quantum algorithms for the simulation of matter. He is jointly appointed as a Professor of Chemistry and Computer Science at the University of Toronto. Previously, he was a full professor at Harvard University. Alán is also a co-founder of Zapata Computing and Kebotix, two early-stage ventures in quantum computing and self-driving laboratories respectively.
Title: An Overview of Computational and Applied Math at AFOSR: Learning From the Past and A View Towards the Future
Abstract:In this talk, I will present an overview of the research vision in computational and applied mathematics at the Air Force Office of Scientific Research (AFOSR). I will draw from specific examples of programs in development of high-order methods of accuracy, reduced order modeling, uncertainty quantification and data-driven modeling and their relative success and impact on the field to formulate a path ahead for future program ideas to nurture and enhance the computational way of thinking and research in the science and engineering.
Bio:Dr. Fariba Fahroo is a Program Officer at the Air Force Office of Scientific Research (AFOSR) and is managing programs in Computational Mathematics and Optimization and Discrete Math. She rejoined AFOSR in March of 2018, after 4 years as a Program Manager at the Defense Advanced Research Projects Agency (DARPA) in the Defense Science Office (DSO). While at DARPA she initiated and managed programs in applied mathematics in the areas of Uncertainty Quantification for modeling and design of physical systems (EQUiPS), dynamic data modeling (MoDyL) and large scale nonlinear optimization (Lagrange). Prior to DARPA, her previous tour at AFOSR involved managing basic research programs in various areas of computational math and control theory such as multiscale modeling and computation, design under uncertainty, distributed, multi-agent control and estimation and computational control theory. She is a fellow of IEEE, SIAM and Associate Fellow of AIAA.Dr. Fariba Fahroo is a Program Officer at the Air Force Office of Scientific Research (AFOSR) and is managing programs in Computational Mathematics and Optimization and Discrete Math. She rejoined AFOSR in March of 2018, after 4 years as a Program Manager at the Defense Advanced Research Projects Agency (DARPA) in the Defense Science Office (DSO). While at DARPA she initiated and managed programs in applied mathematics in the areas of Uncertainty Quantification for modeling and design of physical systems (EQUiPS), dynamic data modeling (MoDyL) and large scale nonlinear optimization (Lagrange). Prior to DARPA, her previous tour at AFOSR involved managing basic research programs in various areas of computational math and control theory such as multiscale modeling and computation, design under uncertainty, distributed, multi-agent control and estimation and computational control theory. She is a fellow of IEEE, SIAM and Associate Fellow of AIAA.
Title: Precision Algorithms: Algorithm Augmentation by Machine Learning
Abstract:While the success of modern simulation techniques is undisputed, many of the most successful schemes rely on the tuning of parameters, often in a nonlinear and spatio-temporal fashion to ensure optimal algorithm performance. Classic examples include the detection of bad cells when one solves conservation laws with high-order methods, the adaptive selection of stencils in ENO/WENO methods or general adaptive methods, or the formulation of efficient and robust reduced order models for nonlinear problems where standard projection based methods often fail. These specific elements are all characterized as playing a central role in an otherwise successful algorithm. In this talk we discuss the potential of using ideas of machine learning to overcome such bottlenecks and augment the algorithm to allow the choice of optimal local parameters and eliminate critical performance bottlenecks, resulting vastly improved performance of the augmented algorithm. The central approach is to carefully identify such bottlenecks and explore data driven solutions but otherwise maintain the integrity of a well tested method. After a brief introduction to machine learning techniques and, in particular, neural networks, we demonstrate the success of this general idea through a number of specific examples, primarily motivated by challenges associated with the numerical solution of conservation laws. Time permitting, we also touch on advances in reduced order modeling, enabled by a similar approach. While exemplified through specific examples, the overall philosophy is general and we conclude the talk with a more general discussion of the potential of augmenting algorithms by machine learning, resulting in a class of methods which can perhaps be referred to as precision algorithms.
Bio:Jan S Hesthaven holds the Chair of Computational Mathematics and Simulation Science at EPFL since 2013 and is the Dean of the School of Basic Sciences at EPFL since 2017. His research focuses on the development, analysis and application of high-order accurate methods for time-dependent partial differential equations with an emphasis on wave dominated problems. Prior to joining EPFL in 2013, he was on the faculty of the Division of Applied Mathematics at Brown University for 15 years. He is an Alfred P Sloan fellow, an NSF Career awardee, and a SIAM fellow. He current serves as the editor-in-chief of SIAM Journal of Scientific Computing and on the editorial board several other leading journals, incl Journal of Computational Physics, Mathematical Modeling and Numerical Analysis, and Numerische Mathematik.
Title: Large-scale Optimization in Nanophotonics
Abstract:Increasingly sophisticated nanofabrication techniques have opened an enormous space of design parameters for nanophotonic devices, and one approach to this flexibility is large-scale optimization (or "inverse design"): allowing a computer to search a huge range of possible geometries with minimal human input in order to choose the best design for a given objective. The key question in such approaches is often not what optimization algorithm to use, however, but how to formulate the optimization problem: there are often many choices of formulations, parameterizations, and objective functions for a single conceptual task, and which one is chosen can make an enormous difference in the feasibility of the computation and the usability of the result. We illustrate these ideas with problems in the design of nonlinear microcavities and large-scale "metasurfaces", both of which quickly become intractable if attacked naively.
Bio:Steven G. Johnson is a Professor of Applied Mathematics and Physics at MIT. He works in the field of nanophotonics—electromagnetism in media structured on the wavelength scale, especially in the infrared and optical regimes—where he works on many aspects of the theory, design, and computational modeling of nanophotonic devices, both classical and quantum. He is coauthor of over 200 papers and over 25 patents, including the second edition of the textbook Photonic Crystals: Molding the Flow of Light. In addition to traditional publications, he distributes several widely used free-software packages for scientific computation, including the MPB and Meep electromagnetic simulation tools and the FFTW fast Fourier transform library (for which he received the 1999 J. H. Wilkinson Prize for Numerical Software).
Title: Artie: An Artificial Student for Heat Transfer
Abstract:An undergraduate student in heat transfer (or similar engineering science continuum discipline) maps a non-prescriptive problem statement in natural language first to a relatively simple mathematical model and finally to a closed-form approximate solution. This classical approach remains relevant even today: to develop design tools which serve to narrow the parameter domain prior to more refined optimization; to provide transparent reference solutions which serve to verify the results of large-scale simulation. "Artie" is software which replicates the undergraduate student procedure and further expands the analysis capability to incorporate numerical solution of parametrized partial differential equations (PDEs). We anticipate that Artie could ultimately earn an A+ in an MIT heat transfer subject. The latter, in turn, has important implications for education and professional practice: we must update the undergraduate curriculum, and we must revisit the roles of engineers. However, many technical challenges remain, in particular related to geometry and image processing, natural language understanding, incorporation of (heat transfer) empirical data and correlations, identification of asymptotic limits in complex configurations, acceleration of associated PDE computations, and assessment of model and approximation error.
Bio:Anthony T. Patera is Ford Professor of Engineering and Professor of Mechanical Engineering at MIT. He has undergraduate and graduate degrees in Mechanical Engineering from MIT and a doctoral degree in Applied Mathematics also from MIT. His current research focuses on two areas: integrated methodologies for mathematical modeling and (numerical) approximation in disciplines informed by partial differential equations; reduced basis approximation and a posteriori error estimation for the parametrized partial differential equations of elasticity, acoustics, fluid dynamics, and heat transfer.
Title: Brain Fluid Dynamics and Associated Diseases: A Holistic Modelling Approach
Abstract:First I review the physiology of extracellular fluid compartments in the human central nervous system with emphasis in their anatomical connections, their mechanics as well as some recent discoveries. This is followed by a brief discussion on a range of fluid-dynamics related disorders associated to diseases that include Meniere’s Disease, Idiopathic Parkinson’s Disease, Multiple Sclerosis, Alzheimer’s Disease and Idiopathic Intracranial Hypertension. I then describe a global, closed loop mathematical model for the entire human circulation coupled to the dynamics of other bodily fluid systems. I present results on the role of intracranial and extracranial venous outflow anomalies on brain dynamics. We predict disturbed brain fluid dynamics, intracranial venous hypertension, intracranial hypertension, reverse flow and reduced perfusion. We speculate that such disturbances may be part of the triggering mechanisms of several neurological diseases. To conclude I point out some of the limitations of our work and some mathematical and computational problems still unsolved.
Bio:Eleuterio F. Toro, born in Chile on 16th July 1946, is currently an Emeritus Professor of Mathematics at the University of Trento, Italy and formerly a full Professor of Numerical Analysis at the same University. He holds an Honours BSc in pure mathematics (University of Warwick, UK); an MSc in functional analysis and differential equations (University of Dundee, UK); a PhD in computational mathematics from Teesside University (UK 1982) and is recipient of several honours and distinctions. Professor Toro’s research has for many years focused on the construction of computational methods for solving time-dependent evolutionary partial differential equations, with particular emphasis on hyperbolic balance laws and applications to industrial, aerospace and environmental problems. Currently, Professor Toro’s research is focused on the biophysics of neurodegenerative diseases and their association to the disturbed dynamical interaction of fluid compartments in the central nervous system (arterial blood, venous blood, interstitial fluid, cerebrospinal fluid, the brain parenchyma and the lymphatic system) and their potential association to neurological diseases.
Title: Machine Learning CFD for Interactive Aerodynamic Design
Abstract:Designing aerodynamic 3D objects today continue to be a time-consuming task. The designer needs to carefully optimize the objects' performance such as drag coefficient which often can be evaluated through the expensive CFD simulation. Leveraging the power of machine learning, we can now drastically accelerate various kinds of simulations for 3D shape designs. Based on the prior real-world or simulation examples for various existing shapes, machine learning can instantly synthesize simulation results for a novel input shape. In this talk, I describe our several interactive approaches to integrate CFD simulation into geometric modeling to actively support creative design processes. Importance of interactivity in the design system will be discussed in various practical contexts including wind musical instrument design, hand-launching airplane design, three-dimensional kite design, and aerodynamically efficient car shape design.
Bio:Nobuyuki Umetani is a project lecturer at the University of Tokyo. Previously, he was a research scientist at Autodesk Research, leading the Design and Fabrication group. He was a postdoctoral researcher at Autodesk Research and Disney Research Zurich. He received his Ph.D. degree in 2012 from The University of Tokyo under the supervision of Takeo Igarashi. He also spent one year at Columbia University and in TU Delft, and spent three months in Microsoft Research Asia and in UCL. He won the Microsoft Research Asia fellowship in 2011. The principal research question he addresses through his studies is: how to integrate real-time physical simulation into an interactive geometric modeling procedure to facilitate creativity. He is broadly interested in physics simulation, especially the finite element method, applied for computer animation, biomechanics, and mechanical engineering.
Title: Clinical Cardiovascular Mathematics: Challenges and Perspectives
Abstract:While mathematical models and numerical simulations have been proving a tremendous potential impact to the understanding and the care of Cardiovascular Diseases, their use in the clinical practice - even if growing up - is still limited. This is due to several reasons, both practical and cultural. An interdisciplinary collaboration between clinicians and mathematicians is not easy to sustain over a long time, not only for the difference of academic and scientific targets, but also for the intrinsic challenges raised by the clinical activity for what attains their mathematical aspects. The need for processing a large volume of patients, the diversity of cases encountered in patient-specific settings, the rigorous certification of the reliability of the results are only some of the specific challenges, calling for efficient methods, reduced order models, uncertainty quantification, data assimilation. In this talk, I will report some of the methodological developments in the "translational" activity at Emory to finalize mathematical and numerical tools to the clinical practice. Specifically, I will address problems in modeling the geometry of patient-specific coronaries after a stent deployment, of uncertainty quantification of defective boundary problems and of data assimilation for cardiac conductivities. Perspectives of numerical modeling in clinical routine will be discussed, in view of the recent developments of data-based methodologies and the success of entrepreneurial initiatives in the field of cardiovascular mathematics.
Bio:Alessandro Veneziani is professor of Mathematics at Emory University since 2015, and he was previously with the Politecnico di Milano, the School of Advanced Studies IUSS in Pavia, with the University of Verona and of Bergamo in Italy. Since 2017 he is also co-founder and Chief Scientific Officer of the Company Covanos with Don Giddens, for using numerical tools in Cardiovascular Clinics. He is the recipient of several Grants, from - among the others- the NSF, the Brain Aneurysm Foundation and the Georgia Research Alliance. He was awarded of the SIAM outstanding Paper prize in 2004 and of the Giovanni Sacchi-Landriani International Prize in 2007. He is engaged by the applications of advanced mathematical and numerical tools to the clinical treatment of Cardiovascular Diseases.
Title: Optimization in Machine Learning
Abstract:Optimization is vital to the modern revolution in data science, and techniques from optimization have become essential in formulating and a wide variety of data analysis problems. In turn, data has caused a ferment of new research activity in optimization by posing challenging new problems and new contexts. We start this talk with an overview of the many problem classes in data science in which optimization provides the key solution methodology. We discuss several areas of recent interest that are relevant to both areas, including such areas as nonconvex optimization, robust optimization, adversarial machine learning, neural networks, and matrix optimization. Throughout, we will highlight aspects relevant to scientific computing, noting that the computational needs of optimization algorithms in many machine learning applications are very high.
Bio:Stephen J. Wright holds the George B. Dantzig Professorship, the Sheldon Lubar Chair, and the Amar and Balinder Sohi Professorship of Computer Sciences at the University of Wisconsin-Madison. His research is in computational optimization and its applications to many areas of science and engineering. Prior to joining UW-Madison in 2001, Wright held positions at North Carolina State University (1986-90), Argonne National Laboratory (1990-2001), and the University of Chicago (2000-2001). He has served as Chair of the Mathematical Optimization Society (2007-2010) and as a Trustee of SIAM for the maximum three terms (2005-2014). He is a Fellow of SIAM. In 2014, he won the W.R.G. Baker Award from IEEE for best paper in an IEEE archival publication during the three years 2009-2011. Wright is the author / coauthor of widely used text and reference books in optimization including "Primal Dual Interior-Point Methods" and "Numerical Optimization". He has published widely on optimization theory, algorithms, software, and applications. Wright is current editor-in-chief of the SIAM Journal on Optimization and previously served as editor-in-chief of Mathematical Programming Series B. He has also served as associate editor of Mathematical Programming Series A, SIAM Review, SIAM Journal on Scientific Computing, and several other journals and book series.


What is User Experience Design ?
User experience design (UX, UXD, UED or XD) is the process of enhancing user satisfaction with a product by improving the usability, accessibility, and pleasure provided in the interaction with the product.User experience design encompasses traditional human–computer interaction (HCI) design, and extends it by addressing all aspects of a product or service as perceived by users.
User experience is explained by many individual's.One of the reputed one's are nngroup and Techved.


{% extends "orchid/base_layout.html" %} {% block title %}Identify Photo | OrchID{% endblock %} {% block content %}
Click and drag on the photo to select the flower if it does not comprise the entire photo, especially if there are leaves or a pot in the photo as well. Make sure that there is only a single flower in the selection with at least a small margin around it. Then click the "Identify Photo" button to start the identification.
{% endblock %} {% block scripts %} {% endblock %}


{include file='public/head' /}
{$language_tag.index_operations_operationsEmail_create_backlog_email_template}
{include file='public/header' /}
{include file='public/left_menu' /}
{$language_tag.index_public_homepage}
{$language_tag.index_branchcompany_showBranchProductManage_branchManagement}
{$language_tag.index_operations_operationsEmail_backlog_email_template}
{$language_tag.index_operations_operationsEmail_create_backlog_email_template}
{$language_tag.index_operations_operationsEmail_backlog_email_title}:
{$language_tag.index_operations_operationsEmail_subheading}:
{$language_tag.index_operations_operationsEmail_main_body}:
{$OperationsEmail.content}
{$language_tag.index_branchcompany_showCompanyOrderManage_addEdit_submit}
{$language_tag.index_public_cancel}
{include file='public/foot_js' /}


{{message.entryQuote}} Up Vote {{numberOfLikes}} Down Vote {{numberOfDislikes}} Delete
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$54,000
Showing all 3 results
Newport Beach, CA
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2 Bathrooms
700sq ft
1 Parking
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1200sq ft
Websites in professional use templating systems. Commercial platforms.
123 Benton, Savannah, GA, USA
<EMAIL_ADDRESS>+1<PHONE_NUMBER>
Friday-Wednesday: 9.00AM to 5.00PM


form
element
Pass Criteria
#1: Element is supported
#2: Correct HTML and Core Accessibility API mappings
#3: Correct Accessible Name & Description Calculation
Reference
HTML
form
element
HTML Accessibility API Mappings for
form
element
Core Accessibility API Mappings for
form
role
Test form-001:
form
element
Name
Test form-002:
form
element with
required
attribute on
input type="text"
.
Name
Test form-003:
form
element with
novalidate
attribute and
required
attribute on
input type="text"
.
Name


Next:
component of induction equation
Up:
Components of MHD equations
Previous:
component of induction equation
component of induction equation
The
component of the induction equation is given by
(
83
)
which can be further written as
(
84
)
where
(
85
)
is the negative local magnetic shear. Using
, equation (
84
) is written as
(
86
)
(
87
)
Eq. (
87
) agrees with Eq. (21) in Cheng's paper[
3
].
Next:
component of induction equation
Up:
Components of MHD equations
Previous:
component of induction equation
yj 2015-09-04


Solid State Lidar - the 3D Camera
29 Jun 2020Episode #313: Solid State Lidar - the 3D Camera
Erin Bishop from Sense Photonics talks about the technology in their “Solid State” LiDAR sensors that allows them to detect objects more accurately and over a larger field of view than traditional scanning LiDAR. Erin dives into the technical details of Solid State Lidar, discusses the applications and industries of the technology.
Erin Bishop
Erin operates at the intersection of product management, project engineering, customer development, and product-market fit within 3D camera company Sense Photonics. Over the past several years, she has worked to initiate the market appetite for telepresence robots, indoor mobile robots, and robotic picking in warehouses. Erin has made appearances at CES, UX Week, RoboBusiness, HardwareCon, and Mobile Future Forward.
Erin creates partnerships that result in large-scale deployment of the company’s revolutionary solid-state FLASH architecture. Prior to joining Sense, she held product manager, marketing, and research roles with several robotics companies, including Industrial Perception, Inc. – which was acquired by Google in 2013 – Adept Technology, iRobot, and DEKA. Erin earned her Master’s in Mechanical Engineering from UMass Lowell, where she performed extensive research in Human-Robot Interaction.


{% extends "base.html" %} {% block header %} > Privacy Policy {% endblock %} {% block content %}
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Because we value your privacy we have taken the necessary precautions to be in compliance with the California Online Privacy Protection Act. We therefore will not distribute your personal information to outside parties without your consent.
As part of the California Online Privacy Protection Act, all users may change their public nickname at any time by logging in to their account and clicking the "Change Nickname" link at the bottom of any page.
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We serve as home for hundreds of pets.
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Misc Improvements
- Support for JsonInclude.Include.NON_EMPTY and JsonInclude.Include.NON_NULL on relationships.
- Support for java.util.Optional based on built-in Jackson support. For more information how to setup Jackson, see
https://www.baeldung.com/jackson-optional.
UrlBuilder
is available from CrnkBoot and, in case of Spring, as bean for injection.
It allows the easy construction (and manipulation) of URLs.
- The JPA module has updated its sorting behavior to according to
https://stackoverflow.com/questions/8139437/how-to-set-the-column-order-of-a-composite-primary-key-using-jpa-hibernate
where Hibernate does sort columns alphabetically rather than by file/line order. Most notable use case are entities
with multiple attributes as primary key with paging and no or non-unique sort order. Then crnk already automatically adds
the primary key to make sure the order is total. This change ensures to hit the index as generated by Hibernate.
But the behavior can also be disabled. More details here.


This is the top-level package for the menu application for the HD Cookbook. This is the main menu for the Blu-ray disc image included on the DVD in the HD Cookbook.


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While in Exo, Tao was also the maknae. Tao is known for his effortless rapping skills in the Mandarin songs. Tao has a very interesting and unique character. While he may look scary and intimidating while showcasing his martial arts skills, he has a really cute and confident personality.
Tao left Exo because he had many injuries. Tao has been pursuing a solo career that has been extremely successful. Every song Tao releases always ends up on the charts. Tao has also been acting more. Tao's goal is to make Cpop known around the world. He is not afraid to be his confident self. Tao's music is produced by himself and a close friend. Tao oversees everything when producing music and writing lyrics.


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Have just read INSERT, Don’t DELETE by Aaron Brown, and have some lengthy response, which is why I write this post instead of commenting on said post.
I wish to offer my counter thought and suggest that DELETEs are probably the better choice.
Aaron suggests that, when one wishes to purge rows from some table, a trick can be used: instead of DELETEing unwanted rows, one can INSERT "good" rows into a new table, then switch over with RENAME (but please read referenced post for complete details).
I respectfully disagree on several points discussed.
Lockdown
The fact one needs to block writes during the time of creation of new table is problematic: you need to essentially turn off parts of your application. The posts suggests one could use a slave - but this solution is far from being trivial as well. To switch over, you yet again need to turn off access to DB, even if for a short while.
A switch over to a slave is quite a big deal, in my opinion, for the mere purpose of deletion of rows.
DELETEs are easy
The DELETEs are so much easier: the first thing to note is the following: You don't actually have to delete all the rows *at once*.
You just need to drop some rows, right? Why waste a huge transaction that takes minutes, when you can drop the rows by chunks, one at a time?
For that, you can use either pt-archive from Percona Toolkit, oak-chunk-update from openark-kit, or write a simple QueryScript code with common_schema:
while (DELETE FROM title WHERE title <= 'g' LIMIT 1000) { throttle 1; }
So, drop 1,000 rows or so at a time, then sleep some time, etc. The total runtime is longer, but who cares? The impact can be reduced to be unnoticeable.
Space reclaim
You can use online table operations to rebuild your table and reclaim the disk space. Either see oak-online-alter-table or pt-online-schema-change. Again, both work in small chunks, so no long stalls.
But more on this: my usual purge scenario shows that it is repetitive. You purge, data fills again, you purge again, and so on.
Which is why it doesn't make much sense to rebuild the table and reclaim the disk space: it just grows again to roughly same dimensions.
For a one time operation (e.g. after neglect of cleanup for long time) -- yes, absolutely, do a rebuild and reclaim. For repetitive cleanup - I don't bother.
Conclusion
Aaron does make note at the end of his post that DELETE operations can be done online, while the INSERT trick requires downtime, and this is a fair assessment.
But just to make a point: none of the DELETE timings are interesting. Since we are not concerned with deleting the rows in a given time (no "press the red button"), we can spread them over time and make the impact negligible. So not only is everything done online, it also goes unnoticed by the user. And this, I believe, is the major thing to consider.
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I am currently a 4th year Computer Engineering student at the University of British Columbia. Through working on various projects and co-ops, I have experience with full-stack android/iOS/NodeJS and firmware development. I'm also a member of UBC Thunderbots, a student design team building autonomous soccer-playing robots. I am particularly interested in robotics, autonomous vehicles, distributed systems, cloud services and backend web development. In my free time, I enjoy custom mechanical keyboards and esports.
Programming Languages
C++, JavaScript, Python, Go, Java, C
Technologies
Node.js, Express, SQL, MongoDB, Jest, Qt, Bazel, GTest
Other
Git, Linux, AWS, Travis CI, Wireshark, Raspberry Pi, Bash
UBC Thunderbots is a multidisciplinary student design team that builds fully autonomous soccer-playing robots to compete in the international Robocup Federation. As a member of the software sub-team, I have primarily worked visualization and GUI. I have worked on developing a robot diagnostics GUI, allowing for easier testing of components. I have also worked on improving our error handling by implementing custom logging sinks. To improve code quality in our codebase, I have also been involved in refactoring code, implementing various design patterns such as visitor and dependency injection. Codebase
Fin-der provides a tinder like interface to finding friends in the covid age. It is an android app that particularly aims to connect university students who aren’t able to interact face to face with their peers. I mainly worked on the NodeJS backend using Express, MongoDB, and AWS to implement a feature-complete user, match and chat systems. As a result of our agile process, we placed in the top 5 out of 24 groups while gaining valueable knowledge in RESTful APIs.
FOEX is an Android Application that estimates the expiration date of various produce. It also stores a history of items scanned, giving users reminders for when their food may expire. This project was completed at NWHacks 2020 and received the Wolfram Alpha Award.
Rover is a fully autonomous line following robot built with a Raspberry Pi, breadboard and chassis. I also built an Android App that allows the user to manually override control of the robot and live stream from the Pi Camera.


Jazz Gavel by Joe Guilmette
Primary colour
black
Secondary colour
gray
Tertiary colour
dark-gray
Neutral colour
light-gray


COOL AS ICE vs. BARB WIRE A film review by Shane Henry Copyright 1996 Shane Henry
Movie Review comparing Cool As Ice against Barb Wire By Banana-Kin, Z-Grade Movie Critic
Statistics:
Cool As Ice Barb Wire Stars: Vanilla Ice Pamela Anderson Lee Michael Gross (Family Ties) Pam's "Two Friends"
1991 1996
Review (Cool As Ice was rented from Formum Video in Rolla) :
Starring as "Johnny", (Starring being the operative word) Vanilla Ice demonstrates his (lack of) acting ability. Mr. Ice roles into town as a member of a rap band when one of his band members motorcycles breaks down. While the band waits on the repairs, Vanilla meets a high school girl. Worlds collide as her 4.0 life meets resistance with Vanilla's strong, free, dashing style. As the typical storyline would go (not too original, but for Mr. Ice it probabally is), her father (Michael Gross; Family Ties) forbids Kathy to see Johnny. Her father associtates Johnny with some crooked cops that he informed on some twenty years eariler that are now out for revenge.
Vanilla Ice delicately mixes charm with rap music and motorcycles, and even finds a use for his musical abilities (puke). Vanilla's entire acting career can be summed up in his most defining line: You don't know me.
You don't know me AT ALL.
Star rating: (0 stars-poor *****-excellent)
*/2 (One-Half Star)
Review (Barb Wire currrently playing at the Uptown theater in Rolla) :
Pamela Lee (Pamela Anderson: Baywatch) sets acting back 2,000 years as she "stars" as Barb Wire, a mercinary with a set of incredible upper kinetic energies (She is Gravitationally ImPAIRED Pardon the PUN). Set in the future of the "Second American Civil War", Ms. Wire carves out a meger existance as a bar owner in the last free city in America. Audiences, predominately male, will enjoy being able to hear Ms. Wire's thought process as Pamela Lee narates partions of the movie. The movie centers around the new government as it crushes the resistance, and Ms. Wire is the contact for both sides. People are traced through Retinal Scans... where the retina is scanned and recorded similar to fingerprinting. (Why not just use fingerprints?)
Romance meets with guns and grenades as Ms. Wire recounts her love with past freedom fighters and looks great in camoflauge.
This is definitely a T&A movie. The only saving grace for this movie was that I saw it for free. Laughs are frequent for the audience with a critical eye. As unrealistic as her silicon breasts, the movie was complete waste of my time. DEFINITELY do not see this with your wife, girlfriend or date.
Star Rating : (0 stars-poor *****-excellent)
*/4 (one quarter star) Hey, she is pretty hot!
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


The services our Support Team provides depend on the tier of your support seat.
The Lean trading engine is under constant development, so you may occasionally experience bugs when using it. If you think you have found a bug, share a simple backtest with us that reproduces the issue. You can contact us either through email, Discord, or the forum. We will review your submission. If we confirm you've found a bug, we will create a GitHub Issue to have it resolved. Subscribe to the GitHub Issue to track our progress in fixing the bug.
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| Bug Reports |
Our support ticket system enables you to privately email with our Support Team. We address support tickets in a first-in, first-out order, but we give priority to tickets opened by members with higher support seats. The following table shows our response time for each of the support tiers:
| Tier | Response Time (hours) |
|---|---|
| Gold | 24 |
| Silver | 48 |
| Bronze | 72 or Best Effort |
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| Email Support | - |
If you attach a backtest or live trading deployment when you open a support ticket, the intellectual property of your project is protected. We have a restricted subset of the Support Team who can access private support tickets. Using paid support plans ensures only a limited subset of the QuantConnect team can access the algorithms you attach to support tickets. These team members are carefully selected, have been at QuantConnect for at least 2 years, and have passed a background check. In contrast, if you share a backtest or live trading deployment to the forum for assistance, your project becomes part of the public domain.
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| IP Protection | - |
Paid support plans have access to our live deployment debugging service. If you experience an issue with a live trading deployment, open a support ticket. We can assist with uncovering the issue, fixing the issue, and getting you ready to redeploy the algorithm. We can't assist with live trading issues in the community forum or Discord.
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| Live Trading Debugging | - |
If you have a silver or gold support seat, we can offer suggestions on the design of your algorithms. Our Support Team members are experts on the inner workings of Lean, so we can guide you on improving the efficiency of your algorithms by following our common design patterns. We can usually reduce the size of your project's code files and increase the speed of your project backtesting.
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| Algorithm Design Suggestions | - | - |
When you require instant access to our Support team, we can open a private chatroom in Discord. In our private chatroom, you can ask our Support Team questions at any time and we focus on responding as quickly as we can. Request a private chatroom to avoid waiting for email responses on your support tickets.
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| Private Chatroom | - | - | - |
We offer phone support to members with gold support seats. You can take advantage of our phone support for up to 1 hour per month. During phone calls, feel free to ask about anything related to QuantConnect, Lean, or quant trading. We recommend planning your questions before you call in order to best utilize the time available.
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| Phone Call Consultations | - | - | - |
The following table shows the features available in each tier:
| Feature | Community | Bronze | Silver | Gold |
|---|---|---|---|---|
| Bug Reports | ||||
| Email Support | - | |||
| IP Protection | - | |||
| Live Trading Debugging | - | |||
| Algorithm Design Suggestions | - | - | ||
| Private Chatroom | - | - | - | |
| Phone Call Consultations | - | - | - |


{% extends "base.html" %} {% load crispy_forms_tags %} {% load clean from bleach %} {% load guardian_tags %} {% block breadcrumbs %} {% get_obj_perms request.user for algorithm as "algorithm_perms" %}
{% endblock %} {% block content %} {% get_obj_perms request.user for algorithm as "algorithm_perms" %} {% if "change_algorithm" in algorithm_perms %} {% if permission_request %}You currently do not have permission to use this algorithm. If you would like to use the algorithm, you can request permission here.
An email will be sent to the algorithm's editors. They can grant you access.
{% else %}You currently {% if permission_request.status != permission_request.ACCEPTED %}do not {% endif%}have permission to view this algorithm.
You have already sent a permission request. The status of your request is {{ permission_request.get_status_display|lower }}.
{% if permission_request.status == permission_request.REJECTED %} {% if permission_request.rejection_text %}The algorithm's editors have left the following reason for the rejection:
{{ permission_request.rejection_text }}
{% endif %} {% endif %} {% endif %} {% endif %} {% endblock %}


Even more websites all about website templates on Just Web Templates.
If you're looking for beautiful and professionaly made teplates you can find them at Template Beauty.
You can remove any link to our websites from this template you're free to use the template without linking back to us.


The river Guadiana, at its seaward end, forms the border between Portugal and Spain and has been a centre of trade for thousands of years. The town of Vila Real St António was rebuilt in the 18th century after being wiped out in a flood.
The river is navigatable for 20 miles to the town of Alcoutim.
Position 37°10.8’N, 07°24.5’W
If yacht is registered in the EU and all her crew are EU nationals, completion of the usual multi-part form in the marina office is sufficient.
Otherwise it is necessary to visit the offices of the Policia Maritima and Imigracao at the Capitania, about 50m south of the marina.
Last updated April 2014.
Entrance over the bar is possible 3hrs each side of HW, but is best just before HW due to the strength of the tidal stream. If navigating up river at night, take care as some of the buoys are unlit.
The marina here, is on the west bank of the river. If waiting for slack water (advisable) before berthing (or un-berthing), berth on the inside of the waiting pontoon. Mooring on the river side is not permitted.
The Guadiana is navigable all the way up to Pomarão, half way between Alcoutim and Mértola on the east bank of the river. Between Alcoutim and Pomarão it is very beautiful and remote. There are pontoons off Alcoutim, Sanlúcar and Pomarão and off some smaller villages, some with electricity and water. It is safe to anchor anywhere.
The road bridge beyond the marina, has sufficient clearance for most masted boats, but checking is essential.
See Ayamonte for more information on facilities on this river.
Last updated February 2015..


This survey form's purpose is to query web developers at all stages from new student to those already employed in the industry. It's a way for me to get to know my audience.


This class connects a custom constraint to the SDK. More...
#include <PxConstraintDesc.h>
Public Member Functions | |
| virtual void * | prepareData ()=0 |
| virtual bool | updatePvdProperties (physx::pvdsdk::PvdDataStream &pvdConnection, const PxConstraint *c, PxPvdUpdateType::Enum updateType) const =0 |
| virtual void | onConstraintRelease ()=0 |
| virtual void | onComShift (PxU32 actor)=0 |
| virtual void | onOriginShift (const PxVec3 &shift)=0 |
| virtual void * | getExternalReference (PxU32 &typeID)=0 |
| Fetches external data for a constraint. More... | |
| virtual PxBase * | getSerializable ()=0 |
| Obtain a reference to a PxBase interface if the constraint has one. More... | |
| virtual PxConstraintSolverPrep | getPrep () const =0 |
| Obtain the shader function pointer used to prep rows for this constraint. More... | |
| virtual const void * | getConstantBlock () const =0 |
| Obtain the pointer to the constraint's constant data. More... | |
| virtual | ~PxConstraintConnector () |
| virtual destructor More... | |
This class connects a custom constraint to the SDK.
This class connects a custom constraint to the SDK, and functions are called by the SDK to query the custom implementation for specific information to pass on to the application or inform the constraint when the application makes calls into the SDK which will update the custom constraint's internal implementation
|
inlinevirtual |
virtual destructor
|
pure virtual |
Obtain the pointer to the constraint's constant data.
|
pure virtual |
Fetches external data for a constraint.
This function is used by the SDK to acquire a reference to the owner of a constraint and a unique owner type ID. This information will be passed on when a breakable constraint breaks or when PxConstraint::getExternalReference() is called.
| [out] | typeID | Unique type identifier of the external object. The value 0xffffffff is reserved and should not be used. Furthermore, if the PhysX extensions library is used, some other IDs are reserved already (see PxConstraintExtIDs) |
|
pure virtual |
Obtain the shader function pointer used to prep rows for this constraint.
|
pure virtual |
|
pure virtual |
This function is called by the SDK when the CoM of one of the actors is moved. Since the API specifies constraint positions relative to actors, and the constraint shader functions are supplied with coordinates relative to bodies, some synchronization is usually required when the application moves an object's center of mass.
|
pure virtual |
When the SDK deletes a PxConstraint object this function is called by the SDK. In general custom constraints should not be deleted directly by applications: rather, the constraint should respond to a release() request by calling PxConstraint::release(), then wait for this call to release its own resources, so that even if the release() call occurs during a simulation step, the deletion of the constraint is buffered until that step completes.
This function is also called when a PxConstraint object is deleted on cleanup due to destruction of the PxPhysics object.
|
pure virtual |
This function is called by the SDK when the scene origin gets shifted and allows to adjust custom data which contains world space transforms.
| [in] | shift | Translation vector the origin is shifted by. |
|
pure virtual |
when the constraint is marked dirty, this function is called at the start of the simulation step for the SDK to copy the constraint data block.
|
pure virtual |
this function is called by the SDK to update PVD's view of it


<chdesc>
The <chdesc>
element is a description of an option that a user chooses
while performing a step to accomplish a task. It explains why the user would choose that
option and might explain the result of the choice when it is not immediately obvious.
Category: Task elements


{{ register_customer_form.email.label }}
{{ register_customer_form.password.label }}
{{ register_customer_form.reconfirm_password.label }}


This sample is a simple application that serves as an application under test for the SpinnerTest test application example.
This application illustrates basic state management across the Android application life cycle, mainly for the purpose of highlighting common patterns of Activity testing. When the application is first run, the spinner widget displays a default selection of "Earth". Thereafter, the application saves a selection as soon as it is made. The application remembers the selection from invocation to invocation, even if the device reboots.
The test application SpinnerTest shows you how to set up tests to monitor and prevent code regressions in the management of state across invocations and power cycles.
For more information about this application, see the Activity Testing tutorial.


@(client_id:String)
Welcome to freestyle-blog-app
Login either with credentials or using GitHub account (OAuth2.0)
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neurodegenerative disorder
severe loss of pigmented dopaminergic neurons in substantia nigra of midbrain
neurons project to corpus striatum - leads to overall decrease in motor activity
not fatal in itself but: falls, #, chest infections 2ary swallowing disorder - increase mortality in PD
Braak theory
-
pathology first starts in eneteric nervous systme and in medulla and olfactory bulb
-
then to substantia nigra
-
precede motor symptoms;
-
constipation and other autonomic symptoms
-
sweating
-
drooling @ night
-
erectile dysfunction
-
-
Hyposmia (decrease smell)
-
REM sleep disorder
-
severe depressive disorder
-
fatigue and/or mental infelxibility
-
lower back pain
-
epidemiology + genetics
-
1% > 65
- 3/1000 patients
-
median age onset = 60yo
-
life expectacy \~ 15yrs
Features
Characteristic symptoms:
-
stiffness
-
resting tremor
-
bradykinesia
-
handwriting
- typically slopes upwards
-
-
hypokinesia (reduction of movement)
-
asymetric
-
insidious
-
non motor;
-
excessive sweating
-
deression
-
reduced sense of smell
-
cognitive impairment
- alterante = lewy body dementia
-
hypotension (?)
- early hypotension = MSA
-
not useful in diagnosing PD limited specificity
-
Examination
-
rigidity
-
passive movements
-
‘cogwheel phenomenon
-
-
resting tremor
-
4Hz (4 cycles / sec)
-
typically affecting upper limb
-
-
impairment of dextrous upper limb movements and facial expression due to bradykinesia
-
affecting small muscle groups of face and hands
- usually seen in the early phases of the condition
-
-
gait disorder
-
later in course
-
lack of spontaneous arm swing
-
turning en bloc
- whole body turns when changing direction
-
festinating gait
-
small steps
-
shiffling
-
-
falls
-
Diagnosis
-
diagnosis = challenging
-
recommend specialist opinion (neurology vs. geriatrician) before treatment is initiated
- improve likelifood of a good outcome
-
response to levodopa = key criterion for diagnosis of PD
-
alternative dx
-
medicine-induced parkinsonism
-
essential tremor
-
multiple cerebral infarction
-
Management
no cure
symptom control
treatment = functional benefit for at least 10yrs
non-pharmalogical
multidisciplinary approach”
PT
OT
Speach language
nurse
specialist
GP
Exercise
-
formal exercise rehabilitation likely to benefit patients
-
PT specific interventions
-
start hesitancy
-
freezing of gait
-
festination
-
fals
-
-
-
Strategy training
-
Managmeent of musculskeletal issues
-
weakness
-
loss of ROM
-
-
General promotion of physical activity with specific interventions for falls prevention
-
no evidence that one measure better than any others; quality of comparisons were poor
Occupational therapy
-
safely maintain activity and employment
-
improve self esteem
-
also to determine re driving motor vehicle
Driving:
cognitive disturbance, adverse effect of dopaminergic treatment (daytime sleepiness)
limb strenght, accuracy of rapid foot movements, joint proprioception should be assessed
should always cease if there is doubt about a person’s ability to control a vehicle in an emergency situation
if trouble walking then trouble driving
Speech therapy
-
hypophonia (soft speech)
-
voice training can improve voice quality and audibility
-
SLT - focus on iincrease on volume of speech
-
dysphagia
Dietician
-
weight loss - some people
-
extra energy expenditure
-
tremor/rigidity
-
change swallowing
-
satiety
-
reduced appetite due to dopaminergic treatment
-
-
-
may benefit from high calorie supp. but little evidence
Parkinson’s NZ website
counselling for the patient
-
can assis in the development of self-management techniques - depression and anxiety
-
strain on families
Pharmacological treatment
-
motor symptoms tycially respond well
- response = diagnositc criteria
-
motor symptoms controlled = on
-
poor motor symptom control = offf
-
little evidence that treatment in early phases results in improved long-term outcomes
-
if doens’t respond consider other diagnosis
-
motor fluctuations
- dyskinesia 2ary levodopa treatment develop in all patients with PD
-
‘wearing off’ phenomenon
-
increase stiffness adn slowness after dose of med
-
very severe fluctuations between rigid-akinetic states adn severe episodes of dyskinetic (involuntary) movements
-
When to start
-
reports troubling sympomts
-
neurologist/geriatrician responsible for initiating treatment
-
diagnostic trials not considered without discussion with a neurologist or geriatrician
-
if delay -> phone
Levodopa + dopa-decarboxylase inhibitor
-
usually firstline
-
dopamine doesn’t cross b-b barrier - causes severe N&V when given at high doses (enought to cause motor effect)
-
Levodopa does cross
-
rapidly metabolised to dopamine by decarboxylase - in peripehry as well as in brain
-
therefore must be administered with peripheral decarboxylase inhibitor
-
carbidopa or beserazide
-
-
Patients over 40:
-
combination levodopa = first line
-
swallowed whole - not halved or broken
-
often need to increase doses of levodopa or add dopamine agonists
-
dose sdjusted according to level of diability
-
severity of patient’s dyskinesias often determine maximum dose and length of time that levodopa can be tolerated
-
modified release doesn’t reduce motor fluctuations
Patients \<40
-
dopamine agoinist
-
b/c likelifood developing motor fluctuations within 5yrs = 100%
-
ropinirole or pramipexole
-
also frequently used in combination wiht levodopa
-
‘smooth-out’ motor fluctuations
-
cause more sleepiness
-
impulse control disorders
-
binge eating
-
compulsive shopping
-
gambling
-
hypersexuality
-
-
-
bromocriptime/pergolide (ergot-derived)
-
no longer prescribed due to possibility of cardicac valvular fibrosis, pulmonary fibrosis, retroperiotoneal fibrosis
-
need to be monitored for these complications
-
MAOi-B
-
mild symptoms
-
Selegiline
-
can delay need for levodopa
-
alone or combination
-
inhibits catabolism of dopamine
-
may also be combined with levodopa
-
Amantadine
-
weak dopamine agonist
-
can be used to treat dyskinesia
-
not first-line
-
modest effect
-
last less htan 8 months
- although recent trial suggests may last for several years
Catechol-O-methyltransferase inhibitor may be added later in treatment
-
end-of-dose deterioration
-
COMT inhibitors - entacapone, tolcapone
-
prevent peripheral conversion
antimuscarninc medicines less effective compared to dpopaminergic treatments
Non-motor sympotms
Cardiovascular
-
postural and post prandial hypotension
-
increase fluid/salt
-
frequent small meals
-
compression stocking
-
anti-hypertensive meidicnes used with caution
-
fludrocortisone 50mcg daily
-
Gastrointestinal
-
Drooling
-
dopaminergic/antimuscarinic medicines
-
reduce drooling
-
usually cause adverse effects
-
1% atropine eye drops administered sublingually
-
-
-
dysphagia
-
partially responsive to dopaminergic
-
thickened fluids reduce risk of aspiration
-
SLT
-
-
gastroparesis
-
eat small meals
-
domperidone 10-20mg tds/qds
- dopamine antagonist that doesn’t cross B-B barrier
-
-
constipation
-
increase fluid/fibre
-
laxatives
-
bisacodyl (stimulant)
-
glycerol supp
-
docusate
-
docusate + sennosides shouldn’t be takien for long periods
-
-
pain
-
pain present during On or off
- adjusting dopamimnergic treatment may provide benefit
-
can be caused by restricted movmeent
-
muscle spasm
-
nortrip/amitrip
-
carbamazepine 100mg od or bd - increase according to response
-
gabapentin - max 3.6g
-
-
Cognitive
-
anxiety
- “off” state anxiety may benefit from increase dopaminaergic treatment
-
depression
-
assess for pain or sleep disturbance
-
TCA/SSRI may be appropriate
-
support and counselling
-
-
Hallucinations
-
non-troubling don’t require treatment
-
Quetiapine may be used with extreme caution
-
-
Dementia
-
clozpaine
- requires weekly FBC
-
-
-
genitourinary
-
Urgency/frequnecy/bocturia/incovontinence
-
avoid diuretic
-
oxybutyinin in cautino
-
-
-
Sleep
-
excessive daytime sleepiness
-
fatigue 1/3 of PD
-
less common taking levodopa compared to dopamine agonists
-
-
nocturnal doses of dopaminergic medicine may assis t with insomnia
-
levodopa and dopamine agonists may help pateinets wiht RLS
-
Methylphenidate 1-mg tds may be useful
-
benzodiazepine may be effective for patients with REM sleep disorder
-


| 378 | (A) | a fawkone vndir his fete witħ foure kene bladis |
| 382 | (C) | A fawcoune vndur his foote . with fowre kene federes |
| 383 | (D) | A faucon vndur his feet wiþ four kyn feþeres |
| 384 | (E) | & a faukun vnder his feet . with many maner fetheres . |
| (Ex) | ---- no text ---- | |
| 392 | (L) | a fauchyn vnder his feet with foure kene bladdys |
| 366 | (P) | A fachoun vnder his fete with foure kene blades |
| 376 | (U) | A faucon vndir his fote / witħ foure kene fethers |
| (V) | ---- no text ---- |


class Concurrent::TimerSet
Executes a collection of tasks, each after a given delay. A master task monitors the set and schedules each task for execution at the appropriate time. Tasks are run on the global thread pool or on the supplied executor. Each task is represented as a `ScheduledTask`.
@see Concurrent::ScheduledTask
@!macro monotonic_clock_warning
Public Class Methods
Create a new set of timed tasks.
@!macro executor_options
@param [Hash] opts the options used to specify the executor on which to perform actions @option opts [Executor] :executor when set use the given `Executor` instance. Three special values are also supported: `:task` returns the global task pool, `:operation` returns the global operation pool, and `:immediate` returns a new `ImmediateExecutor` object.
Concurrent::RubyExecutorService::new
# File lib/concurrent/executor/timer_set.rb, line 30 def initialize(opts = {}) super(opts) end
Public Instance Methods
Begin an immediate shutdown. In-progress tasks will be allowed to complete but enqueued tasks will be dismissed and no new tasks will be accepted. Has no additional effect if the thread pool is not running.
 If the delay is less than 1/100th of a second the task will be immediately post to the executor.
@param [Float] delay the number of seconds to wait for before executing the task. @param [Array<Object>] args the arguments passed to the task on execution.
@yield the task to be performed.
@return [Concurrent::ScheduledTask, false] IVar
representing the task if the post
is successful; false after shutdown.
@raise [ArgumentError] if the intended execution time is not in the future. @raise [ArgumentError] if no block is given.
# File lib/concurrent/executor/timer_set.rb, line 48 def post(delay, *args, &task) raise ArgumentError.new('no block given') unless block_given? return false unless running? opts = { executor: @task_executor, args: args, timer_set: self } task = ScheduledTask.execute(delay, opts, &task) # may raise exception task.unscheduled? ? false : task end
Private Instance Methods
Initialize the object.
@param [Hash] opts the options to create the object with. @!visibility private
# File lib/concurrent/executor/timer_set.rb, line 74 def ns_initialize(opts) @queue = Collection::NonConcurrentPriorityQueue.new(order: :min) @task_executor = Options.executor_from_options(opts) || Concurrent.global_io_executor @timer_executor = SingleThreadExecutor.new @condition = Event.new @ruby_pid = $$ # detects if Ruby has forked self.auto_terminate = opts.fetch(:auto_terminate, true) end
@!visibility private
# File lib/concurrent/executor/timer_set.rb, line 95 def ns_post_task(task) return false unless ns_running? ns_reset_if_forked if (task.initial_delay) <= 0.01 task.executor.post { task.process_task } else @queue.push(task) # only post the process method when the queue is empty @timer_executor.post(&method(:process_tasks)) if @queue.length == 1 @condition.set end true end
# File lib/concurrent/executor/timer_set.rb, line 130 def ns_reset_if_forked if $$ != @ruby_pid @queue.clear @condition.reset @ruby_pid = $$ end end
`ExecutorService` callback called during shutdown.
@!visibility private
# File lib/concurrent/executor/timer_set.rb, line 123 def ns_shutdown_execution ns_reset_if_forked @queue.clear @timer_executor.kill stopped_event.set end
Post the task to the internal queue.
@note This is intended as a callback method from ScheduledTask
only. It is not intended to be used directly. Post a task by using the `SchedulesTask#execute` method.
@!visibility private
# File lib/concurrent/executor/timer_set.rb, line 90 def post_task(task) synchronize { ns_post_task(task) } end
Run a loop and execute tasks in the scheduled order and at the approximate scheduled time. If no tasks remain the thread will exit gracefully so that garbage collection can occur. If there are no ready tasks it will sleep for up to 60 seconds waiting for the next scheduled task.
@!visibility private
# File lib/concurrent/executor/timer_set.rb, line 144 def process_tasks loop do task = synchronize { @condition.reset; @queue.peek } break unless task now = Concurrent.monotonic_time diff = task.schedule_time - now if diff <= 0 # We need to remove the task from the queue before passing # it to the executor, to avoid race conditions where we pass # the peek'ed task to the executor and then pop a different # one that's been added in the meantime. # # Note that there's no race condition between the peek and # this pop - this pop could retrieve a different task from # the peek, but that task would be due to fire now anyway # (because @queue is a priority queue, and this thread is # the only reader, so whatever timer is at the head of the # queue now must have the same pop time, or a closer one, as # when we peeked). task = synchronize { @queue.pop } task.executor.post { task.process_task } else @condition.wait([diff, 60].min) end end end
Remove the given task from the queue.
@note This is intended as a callback method from `ScheduledTask`
only. It is not intended to be used directly. Cancel a task by using the `ScheduledTask#cancel` method.
@!visibility private
# File lib/concurrent/executor/timer_set.rb, line 116 def remove_task(task) synchronize { @queue.delete(task) } end


The Amazingly Useful Tools from Yoksel
Easily manage projects with monday.com
I find myself web searching for some tool by Yoksel at least every month. I figured I'd list out some of my favorites here in case you aren't aware of them.
- Need to duo-tone an image? SVG filters can do that. Lentie Ward wrote about it for us, and Yoksel has a tool to create the filters yourself.
- Let's say you have an SVG you want to use as a CSS
background-image
? Drop it in this URL-encoder tool to make sure it's ready to go and safe to use. - Want to understand the difference between clipping and masking and how it works differently for SVG and CSS? We've written about that a few times, but Yoksel has the best reference for seeing live examples and the code for them.
- Perhaps you have a SVG path that you ultimately want to use as a CSS
clip-path
? You might fight against absolute units, but Yoksel has a tool to fix that. - SVG filters are incredibly powerful. Hand-crafting them is pretty hard. Yoksel has GUI tool for playing with them and combining them.


|
lwIP
2.1.3
Lightweight IP stack
|
Macros | |
| #define | netconn_new(t) netconn_new_with_proto_and_callback(t, 0, NULL) |
| #define | netconn_peer(c, i, p) netconn_getaddr(c,i,p,0) |
| #define | netconn_addr(c, i, p) netconn_getaddr(c,i,p,1) |
| #define | netconn_set_ipv6only(conn, val) |
| #define | netconn_get_ipv6only(conn) (((conn)->flags & NETCONN_FLAG_IPV6_V6ONLY) != 0) |
Enumerations | |
| enum | netconn_type { , NETCONN_TCP = 0x10, NETCONN_TCP_IPV6 = NETCONN_TCP | 0x08, NETCONN_UDP = 0x20, NETCONN_UDPLITE = 0x21, NETCONN_UDPNOCHKSUM = 0x22, NETCONN_UDP_IPV6 = NETCONN_UDP | 0x08, NETCONN_UDPLITE_IPV6 = NETCONN_UDPLITE | 0x08, NETCONN_UDPNOCHKSUM_IPV6 = NETCONN_UDPNOCHKSUM | 0x08, NETCONN_RAW = 0x40 } |
Functions | |
| err_t | netconn_prepare_delete (struct netconn *conn) |
| err_t | netconn_delete (struct netconn *conn) |
| err_t | netconn_bind (struct netconn *conn, const ip_addr_t *addr, u16_t port) |
| err_t | netconn_bind_if (struct netconn *conn, u8_t if_idx) |
| err_t | netconn_connect (struct netconn *conn, const ip_addr_t *addr, u16_t port) |
| err_t | netconn_recv (struct netconn *conn, struct netbuf **new_buf) |
| err_t | netconn_err (struct netconn *conn) |
| err_t | netconn_gethostbyname_addrtype (const char *name, ip_addr_t *addr, u8_t dns_addrtype) |
For use with TCP and UDP
| #define netconn_addr | ( | c, | |
| i, | |||
| p | |||
| ) | netconn_getaddr(c,i,p,1) |
| #define netconn_get_ipv6only | ( | conn | ) | (((conn)->flags & NETCONN_FLAG_IPV6_V6ONLY) != 0) |
TCP: Get the IPv6 ONLY status of netconn calls (see NETCONN_FLAG_IPV6_V6ONLY)
| #define netconn_new | ( | t | ) | netconn_new_with_proto_and_callback(t, 0, NULL) |
Create new netconn connection
| t | netconn_type |
| #define netconn_peer | ( | c, | |
| i, | |||
| p | |||
| ) | netconn_getaddr(c,i,p,0) |
| #define netconn_set_ipv6only | ( | conn, | |
| val | |||
| ) |
TCP: Set the IPv6 ONLY status of netconn calls (see NETCONN_FLAG_IPV6_V6ONLY)
| enum netconn_type |
Protocol family and type of the netconn
| Enumerator | |
|---|---|
| NETCONN_TCP | TCP IPv4 |
| NETCONN_TCP_IPV6 | TCP IPv6 |
| NETCONN_UDP | UDP IPv4 |
| NETCONN_UDPLITE | UDP IPv4 lite |
| NETCONN_UDPNOCHKSUM | UDP IPv4 no checksum |
| NETCONN_UDP_IPV6 | UDP IPv6 (dual-stack by default, unless you call netconn_set_ipv6only) |
| NETCONN_UDPLITE_IPV6 | UDP IPv6 lite (dual-stack by default, unless you call netconn_set_ipv6only) |
| NETCONN_UDPNOCHKSUM_IPV6 | UDP IPv6 no checksum (dual-stack by default, unless you call netconn_set_ipv6only) |
| NETCONN_RAW | Raw connection IPv4 |
Bind a netconn to a specific local IP address and port. Binding one netconn twice might not always be checked correctly!
| conn | the netconn to bind |
| addr | the local IP address to bind the netconn to (use IP4_ADDR_ANY/IP6_ADDR_ANY to bind to all addresses) |
| port | the local port to bind the netconn to (not used for RAW) |
Bind a netconn to a specific interface and port. Binding one netconn twice might not always be checked correctly!
| conn | the netconn to bind |
| if_idx | the local interface index to bind the netconn to |
Connect a netconn to a specific remote IP address and port.
| conn | the netconn to connect |
| addr | the remote IP address to connect to |
| port | the remote port to connect to (no used for RAW) |
Close a netconn 'connection' and free its resources. UDP and RAW connection are completely closed, TCP pcbs might still be in a waitstate after this returns.
| conn | the netconn to delete |
Get and reset pending error on a netconn
| conn | the netconn to get the error from |
Execute a DNS query, only one IP address is returned
| name | a string representation of the DNS host name to query |
| addr | a preallocated ip_addr_t where to store the resolved IP address |
| dns_addrtype | IP address type (IPv4 / IPv6) |
Close a netconn 'connection' and free all its resources but not the netconn itself. UDP and RAW connection are completely closed, TCP pcbs might still be in a waitstate after this returns.
| conn | the netconn to delete |
Receive data (in form of a netbuf containing a packet buffer) from a netconn
| conn | the netconn from which to receive data |
| new_buf | pointer where a new netbuf is stored when received data |


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MCQ ALEXANDER MCQUEEN
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DevOps – a cultural shift
Success today is defined by the ability to turn ideas into value faster than your competition, how quickly you can experiment, fail fast, learn fast, test, tune and make it better. The behavior of developers is to make changes and enhance the application to generate revenue streams. Operations, on the other hand, is all about stability and reliability to keep business running 24/7. So how can you reconcile these two conflicting views and reduce friction between the teams? Enter DevOps. DevOps is not a technology but it is a process and a mindset change to promote collaboration between Dev and Ops teams. According to research from Puppet Labs, IT organizations embracing DevOps deploy 200x more frequently, have 24x faster recovery times, 3x lower failure rates and spend 22% less time on unplanned work and rework. This is not a coincidence because these organizations have implemented a process of Continuous Integration and Continuous Deployment (CI and CD) where every step of the application lifecycle from development to deployment is automated with feedback loops for continuous improvement. Infrastructure automation Today, developers expect same level of efficiency, ease of access and disposal of infrastructure similar to hyperscale cloud environments. Therefore, every part of the infrastructure should be composable and accessible as a line of code. With HPE OneView, you can automate entire “Infrastructure-as-code” using your favorite configuration management tools such as Chef, Puppet or Ansible and deploy IT resources for any workload easily within few minutes, a task that used to take several days to weeks to deploy. A great example of Composable Infrastructure is HPE Synergy which includes HPE 3PAR StoreServ flash storage and software-defined storage StoreVirtual VSA as storage building blocks. The RESTful APIs from Storage platform are then exposed to automation tools via HPE OneView for storage provisioning, management etc. All-Flash Array as a DevOps enabler Historically, one of the reasons that Dev and Ops environments were siloed was because the underlying infrastructure – and storage in particular – did not have the horsepower to host both of these environments on same platform. This led to Dev and QA teams making their own redundant copies of datasets. Imagine if you had a 10TB database that gets copied around. . . you get the picture. Using 3PAR All-flash array, Dev and Ops can be consolidated on the same storage platform. Benefits to this approach include: Storage footprint reduction. By creating snapshots/clones of production datasets, IT teams can eliminate the need for Dev & QA to make multiple distinct copies of datasets. Improve code quality and faster issue resolution. Application development/QA will have access to fresh production quality datasets to test against real world environments. On a 3PAR StoreServ All-Flash array, you can use features such as Priority Optimization to set Quality of Service (QoS) controls and sub-1 ms latency. Ops teams can eliminate noisy neighbor issues and set bandwidth/IOPS/latency goals for Dev teams without compromising production SLAs. While DevOps is a power enabler that promotes collaboration between typically siloed Dev and Ops teams, it is equally important to have the right infrastructure that provides necessary automation to keep pace with application innovation and IT service delivery. HPE will be there as your partner as you take the journey towards a better enterprise that will quickly turn Ideas into successful business models.
Srikanth Venkataseshu


Guinea-Bissau newly appointed PM resigns under pressure from Ecowas
BISSAU (Reuters) - Guinea-Bissau’s newly appointed Prime Minister Faustino Fudut Imbali handed in his resignation on Friday after an ultimatum was given by West African regional bloc ECOWAS, the president said.
President Jose Mario Vaz named Imbali prime minister last week but his sacked predecessor Aristides Gomes refused to step down, triggering a political crisis in an already tensed context ahead of a presidential election.
Vaz, who is running again in the Nov. 24 poll, dissolved the government saying the political situation was undermining the normal functioning of state institutions in the West African country.
But regional bloc ECOWAS condemned the move, calling it illegal, and held an extraordinary summit on the Guinea-Bissau political situation in Niamey on Friday to pressure Imbali’s government to resign, threatening to apply sanctions if it didn’t comply.
ECOWAS also warned that any implication of the army or security forces would be considered a coup and also met with sanctions.
Instability in Guinea-Bissau has typically taken the form of military coups, led by officers drawn mostly from a narrow military elite who fought for independence in 1963-1974.


Scots killer jailed for 17 years after stabbing gran 47 times in £10k pension row
William Finlay confessed to neighbours after the frenzied knife attack on 44-year-old Fiona McDonald in Falkirk.
by Dailyrecord.co.ukA man who murdered his neighbour by stabbing her 47 times in a row over his £10,000 pension money was today jailed for life and ordered to spend at least 17 years behind bars.
William Finlay, confessed what he had done to neighbours and police and claimed he should 'be shot in the head” for the brutal killing of grandmother 44-year-old Fiona McDonald, who was also known as Fiona Canning.
He admitted murdering her in her flat in Camelon, Falkirk, in November last year.
Sentencing Finlay at the High Court in Glasgow judge Lady Stacey told him: “Nothing can take away the grief her family feel. Her mother, daughter and grandchildren have been deprived of her company.
“It is not up to me to decide when, if ever, you will be released, that is up to the parole board.”
The court heard that Finlay, who was made redundant after 20 years from a job in international electronics, came back to Falkirk to look after his mother.
He became friends with Ms McDonald but it was a volatile relationship.
In March 2018 Finlay took £10,000 out of his pension pot and by November that year he was £1,300 in debt to the housing association for his rent.
Defence QC Thomas Ross said: “They had a very complicated relationship. At times they were friends and other times they had violent disagreements.
“Mr Finlay, who latterly worked as a cleaner in banks and financial institutions, drew a pension payment for £10,000 in March, 2018 and was in debt to the tune of £1,300 by that November.
“Fiona McDonald had accrued debts and men were turning up at his door looking for money. He believed she had built up debt with drugs using him as credit.
“It is unusual for someone with no history of violence to behave in such a brutal fashion.”
Mr Ross described the attack on Ms McDonald as “brutal and sustained.”
Finlay, 57, from Falkirk, told police, who questioned him, that he was pushed to his limits and could not apologise enough for killing someone, but said it was 'revenge.”
He said he believed she had been “rinsing him” of his £10,000 pension payment.
Prosecutor Margaret Barron said: “He stated to witnesses that she had been 'rinsing him' and was constantly asking for money.”
The court heard that Finlay, who was covered in blood, turned up at a friend's house and confessed to the murder.
When Finaly left his house the friend dialled 999.
Finlay also told neighbours: “I've just murdered Fiona.”
When they rushed to her flat they saw her seated on a couch “just staring into the sky,” with blood all over her body.
A small kitchen knife was found near to her body.
Finlay when arrested told police officers: “Junkies bothering me, that's why I got my revenge.
“I took it out on a poor woman who robbed me for thousands of pounds.
“I deserve to be shot in the head for what I've done tonight.
"I apologise for doing it, but you can't apologise for killing someone – this is what happens when you get pushed to the limits.”
Finlay showed no emotion as he was led away to begin his sentence.


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\(\def\loading{......LOADING......Please Wait} \def\RR{\bf R} \def\real{\mathbb{R}} \def\bold#1{\bf #1} \def\d{\mbox{Cord}} \def\hd{\widehat \mbox{Cord}} \DeclareMathOperator{\cov}{cov} \DeclareMathOperator{\var}{var} \DeclareMathOperator{\cor}{cor} \newcommand{\ac}[1]{\left\{#1\right\}} \DeclareMathOperator{\Ex}{\mathbb{E}} \DeclareMathOperator{\diag}{diag} \newcommand{\bm}[1]{\boldsymbol{#1}} \def\wait{......LOADING......Please Wait}\)
Pathway Lasso : Estimate and Select Multiple Mediation Pathways
Xi (Rossi) LUO
Brown University
Department of Biostatistics
Center for Statistical Sciences
Computation in Brain and Mind
Brown Institute for Brain Science
Brown Data Science Initiative
ABCD Research Group
IBC, Barcelona Spain
July 10, 2018
Funding: NIH R01EB022911, P20GM103645, P01AA019072, P30AI042853; NSF/DMS (BD2K) 1557467
Co-Author
Yi Zhao
Currently postdoc at Johns Hopkins Biostat
Slides viewable on web:
bit.ly /ibc1807
Motivating Example: Task fMRI
Task fMRI: performs tasks under brain scanning
Story vs Math task:
listen to story (treatment stimulus) or math questions (control), eye closed
Not resting-state: "rest" in scanner
Goal: how brain processes story/math differently?
Like this talk: want to know your brain processed
fMRI data : blood-oxygen-level dependent (BOLD) signals from each
cube /voxel (~millimeters),
$10^5$ ~ $10^6$ voxels in total.
Lego brain of real brain
red cube is a voxel
track activity from each cube at each time vector
dimension: address temporal separately
Conceptual Model with Stimulus
Sci Goal : quantify
red ,
blue , and other pathways
from stimulus to orange outcome region activityHeim et al, 09
Other Potential Applications
Genomics/genetics/proteomics
Multiple genetic pathways
Integrating multiple sources
Common theme: many potential pathways/mediators to disease outcomes
Mediation Analysis and SEM
$$\begin{align*}M = Z a + { \epsilon_1}, \qquad R = Z c + M b + { \epsilon_2}\end{align*}$$
Indirect effect: $a \times b$; direct : $c$
Mediation analysis
Baron&Kenny, 86; Sobel, 82; Holland 88; Preacher&Hayes 08; Imai et al, 10; VanderWeele, 15;...
Multiple (Full) Pathway Model Daniel et al, 14
Stimulus $Z$, $K$ mediating brain regions $M_1, \dotsc, M_K$, Outcome region $R$
Strength of activation ($a_k$) and connectivity ($b_k$, $d_{ij}$)
Potential outcomes too complex, e.g. $K = 2$ Daniel et al, 14
Practical Considerations
The previous model requires specifying the order of mediators, usually unknown in many experiments
We don't know yet the order of brain regions
fMRI: not enough temporal resolution to determine the order
Theoretically and computationally challenging with a large number of mediators
High dimensional (large $p$, small $n$) setting: $K>n$
Mediation Analysis in fMRI
Parametric Wager et al, 09 and functional Lindquist, 12 mediation, under (approx.) independent errors
Stimulus $\rightarrow$ brain $\rightarrow$ user reported ratings, one mediator
Usual assumption: $U=0$ and $\epsilon_1 \bot \epsilon_2$
Parametric and multilevel mediation Yi and Luo, 15 , with correlated errors for two brain regions
Stimulus $\rightarrow$ brain region A $\rightarrow$ brain region B, one mediator
Correlations between $\epsilon_1$ and $\epsilon_2$
This talk: multiple mediator and multiple pathways
High dimensional: more mediators than sample size
Dimension reduction: optimization Chen et al, 15 , testing Huang et al, 16
Our Reduced Pathway Model
$$\scriptsize \begin{align}M_k & = Z A_k + E_{1k},\, k=1,\dotsc, K\\ \scriptsize R & = Z C + \sum_{k=1}^{K} M_k B_k + E_2 \end{align}$$
$A_k$: "total" effect of $Z$→$M_k$; $B_k$: $M_k$→R
Pathway effect: $A_k \times B_k$; Direct: $C$
Two Models
Full Model
Reduced Model
Proposition : Our "total-effect" parameters are linearly related or equivalent to the "individual-effect" parameters in the full model
$C=c$ and $B_k=b_k$, $k=1,\dotsc, K$, are the same in both models
$A_k$ and $a_k$ in two models are linearly related
$A_k \times B_k$ interpreted as the "total" effect when $M_k$ is the last mediator Imai & Yamamoto, 13
Additional Relation to Full Model
Proposition : Our $E_k$'s are correlated, but won't affect point estimation consistency (affect variance)
The price of ignoring the order
Related to causally independent mediators if assuming indepdent $E_k$
Reduced model: a first step to select mediators
Strong overall inflow/outflow of a mediator
Causal Assumptions
We impose standard causal mediation assumptions:
SUTVA
Model correctly specified
Observed is one reliazation of the potential outcomes
Randomized $Z$
No unmeasured confounding/sequential ignorability
Similar assumptions discussed in Imai & Yamamoto, 13; Daniel et al, 14; VanderWeele, 15
Could be too strong or sensitivity analysis Imai & Yamamoto, 13
Regularized Regression
Minimize the penalized least squares criterion
$$\scriptsize \sum_{k=1}^K \| M_k - Z A_k \|_2^2 + \| R - Z C - \sum_k M_k B_k \|_2^2 + \mbox{Pen}(A, B)$$
The choice of penalty $\mbox{Pen}(\cdot)$ to be discussed
All data are normalized (mean=0, sd=1)
Want to select sparse
pathways for high-dim $K$
Alternative approach: two-stage LASSO Tibshirani, 96 to select sparse
$A_k$ and
$B_k$ separately: $$ \scriptsize \sum_{k=1}^K \| M_k - Z A_k \|_2^2 + \lambda \sum_k | A_k | \\ \scriptsize \| R - Z C - \sum_k M_k B_k \|_2^2 + \lambda \sum_k |B_k| $$
Penalty: Pathway LASSO
Select strong pathways effects: $A_k \times B_k$
TS-LASSO: shrink to zero when $A$&$B$ moderate but $A\times B$ large
Penalty (prototype) $$ \scriptsize \lambda \sum_{k=1}^K |A_k B_k| $$
Non-convex in $A_k$ and $B_k$
Computationally heavy and non-unique solutions
Hard to prove theory
We propose the following general class of penalties$$ \scriptsize \lambda \sum_{k=1}^K ( |A_k B_k| + \phi A_k^2 + \phi B_k^2) $$
Theorem $$v(a,b) = |a b| + \phi (a^2 + b^2)$$ is convex
if and only if $\phi\ge 1/2$. Strictly convex if $\phi > 1/2$.
Contour Plot of Different Penalties
Non-differentiable at points when $a\times b = 0$
Shrink $a\times b$ to zero
Special cases: $\ell_1$ or $\ell_2$
TS-LASSO: different $|ab|$ effects though $|a|+|b|$ same
$|ab|$
Non-convex
$|ab|+\phi (a^2 + b^2)$
Pathway Lasso
$|a| + |b|$
Two-stage Lasso
Pathway Lasso is a family of (convex) penalties for products
Algorithm: ADMM + AL
SEM/regression loss: $u$; Non-differnetiable penalty: $v$
ADMM to address differentiability $$ \begin{aligned} \text{minimize} \quad & u(\Theta,D)+v(\alpha,\beta) \\ \text{subject to} \quad & \Theta=\alpha, \\ & D=\beta, \\ & \Theta e_{1}=1, \end{aligned}$$
Augmented Lagrangian for multiple constraints
Iteratively update the parameters
We derive theorem on explicit (not simple) updates
Asymptotic Theory
Theorem: Under regularity conditions,
$$ \Ex (Z \sum_k \hat{A}_k\hat{B}_k - Z \sum_k {A}^*_k {B}^*_k )^2 \le O(s \kappa \sigma n ^{-1/2} (\log K)^{1/2}), $$
where $s = \#\{j: B_j^* \ne 0\}$ and $\kappa =\max_j |B_j| $.
With high probability,
$$ \| \hat{A} \hat{B} - A^* B^* \| \le O(s \kappa \sigma n ^{-1/2} (\log K)^{1/2})$$
Complications
Mixed norm penalty $$\mbox{PathLasso} + \omega \sum_k (|A_k| + |B_k|)$$
Tuning parameter selection by cross validation
Reduce false positives via thresholding Johnston and Lu, 09
Inference/CI : bootstrap after refitting
Remove false positives with CIs covering zero Bunea et al, 10
Simulations
Our PathLasso compares with TSLasso
Simulate with varying error correlations
Tuning-free comparison: performance vs tuning parameter (estimated effect size)
PathLasso outperforms under CV
Pathway Recovery
ROC
F1 Score
MSE
Our PathLasso (red ) outperforms two-stage Lasso (blue )
Other curves: variants of PathLasso and correlation settings
Data: Human Connectome Project
Two sessions (LR/RL), story/math task Binder et al, 11
gICA reduces voxel dimensions to 76 brain maps
ROIs/clusters after thresholding
Apply to two sess separately, compare replicability
Jaccard: whether selected pathways in two runs overlap
$\ell_2$ diff: difference between estimated path effects
Tuning-free comparisons
Jaccard
$\ell_2$ Diff
Regardless of tuning, our PathLasso (red ) has smaller replication diff (selection and estimation) than TSLasso (blue )
Stim-M25-R and Stim-M65-R significant shown largest weight areas
M65 responsible for language processing, larger flow under story
M25 responsible for uncertainty, larger flow under math
Summary
High dimensional pathway model
Penalized SEM for pathway selection and estimation
Convex optimization for non-convex products
Sufficient and necessary condition
Algorithmic development for complex optimization
Improved estimation and selection accuracy
Higher replicability using HCP data
Manuscript:
Pathway Lasso (arXiv 1603.07749 )
Limitations: causal assumptions, covaraites, interactions, error correlations Rpkg: macc , time series gma , functional cfma
Thank you!
Comments? Questions?
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