Begin the practice of prayer!
Prayer establishes a life changing relationship allowing you to bring your most heartfelt needs to a God who genuinely cares for you. Simply start with an honest conversation and listen to Him as He guides you.
Praying
Why should you pray?
The best way to build a relationship with someone is to spend time talking to the other person. The same thing is true within your relationship with God. Just as reading your Bible helps you know God more intimately, so does spending time with him in prayer.
Tips for a strong prayer life:
Set aside time every day for prayer. Don’t be tempted to push your conversations with God into the leftover pieces of your busy day.
Make prayer a priority. Combining your prayer time and your Bible reading time into a morning devotional is a great idea.
Don’t role play for God. Just be yourself and talk to Him.  Just come to God as simply and honestly as you can. Speak from your heart. He is your father.
I will give them hearts that recognize me as the Lord. They will be my people, and I will be their God, for they will return to me wholeheartedly.
Jeremiah 24:7
How should you pray?
Spend some time praising and thanking God for the good things in your life.
Confess any sins that you have committed or sinful habits you’re struggling with.
Tell God what is worrying you and what you need help with.
Pray that God will guide and direct your life. Spend time praying for others as you become aware of their needs and desires.
Remember, prayer is a conversation, not a monologue. As you develop your prayer life, you will get more comfortable both speaking to and hearing from God. Ask Him to reveal himself to you.


---
layout: post
title: "My Week in Review"
date: 2015-03-08 17:45:00 +0000
categories:
tags:
image: https://s3.amazonaws.com/audreywatters/2015-03-08-hermosa.jpg
imagecredits: https://www.flickr.com/photos/surreal_badger/16754938165/
---
Travel (and Speaking)
- I traveled to Washington DC for 48 hours. Thankfully I was able to escape as the storm hit on Thursday morning.
- Upcoming week: Hermosa Beach. Fingers crossed: no more travel until the end of April.
Hack Education Writing
Writing Elsewhere
Other Projects
- I sent off the manuscript of Reclaim Your Domain. (One of this week’s task: revisions.)
- I went to DC to interview New America Foundation’s Kevin Carey about the publication of his new book The End of College.
- The Teaching Machines Federated Wiki Happening is happening. We held Google Hangouts on Friday and Saturday.
- I had a quick run-through of a talk I’ve delivering virtually to Leeds University next week.
- I had a wonderful call with Stephen Turnipseed from Lego Education, part of my research into the history of ed-tech (in this case, the history of Mindstorms).
- I met Sam Chaltain for coffee while I was in DC.
- I drafted a review of The End of College. Publication and co-authors TBD.
Reading and Viewing
- I picked Liz Losh’s The War on Learning up again.
- I started Jill Lepore’s The Secret History of Wonder Woman (thanks in part to a connection that Kate Bowles made in the FedWiki happening, linking intelligence testing and machines to William Moulton Marston – the inventor of the lie detector and the creator of Wonder Woman).
- I watched the Mockingjay, Part 1.


{% extends "header.html" %} {% block body %}
Taxulator is a website designed to assist you and enhance your shopping experience. It is a free service to you and you can quit at any time. This website will allow you to see what you will be paying for what is in your cart, including taxes, before you reach the cash register. This will allow you to make better infromed decisions as to what you want to buy. You can also add a shopping list as well as a budget to keep you on track with your spending.
{% endblock %}


Great Hill Corporation Step 7: Finishing Touches |
[Prev] [Tutorial3] |
This tutorial has taught you how to create a simple VRaniML program using MFC.
We discussed:
| How to get started. | |
| How to link to the VRaniML library, include the header files and .DLLs that are
needed to run VRaniML programs. | |
| How to add a browser member to the Document class. | |
| How to add a some nodes to the browser's scene graph and render the scene graph. | |
| How to open a VRML file. | |
| How to animate a scene graph. |
Of course, the program can be extended in many ways (and in fact was in the Sample Browser):.
| Add menu, mouse and keyboard support | |
| Add better support for opening VRML 2.0 .wrl files | |
| Add support for exporting VRML 2.0 .wrl files | |
| Make more interesting objects and animations | |
| Add sound and videos | |
| A million other things limited only by your imagination |


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| java.lang.Object | |
| ↳ | eu.monnetproject.lemon.LemonModels |
Set of static task that work on lemon models
| Public Methods | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
Quickly add a lexical entry to a lexicon
| |||||||||||
Get all the entries in a lexicon as an alphabetic sorted list
| |||||||||||
Select a lexical entry by its form
| |||||||||||
Select a lexical entry by the form's representation
| |||||||||||
Get entries by their written representation and properties
| |||||||||||
Select a lexical entry by the form's representation, using regex
| |||||||||||
Get entries in a lexicon mapped by the references they have
| |||||||||||
Get the set of entries that refer to a given reference
| |||||||||||
Get the set of entries that refer to a given sense
| |||||||||||
Get the set of lexica containing a given entry
|
|
[Expand]
Inherited Methods | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
From class
java.lang.Object
|
Quickly add a lexical entry to a lexicon
| entryURI | The identifier for the entry |
|---|---|
| canForm | The canonical form |
Get all the entries in a lexicon as an alphabetic sorted list
| model | The model containing the lexica |
|---|---|
| lexicon | The lexicon to list |
| offset | The first entry to show |
| limit | The maximum number of entries to return, 0 for no limit |
Select a lexical entry by its form
| model | The model containing the appropriate lexica |
|---|---|
| form | The form object |
Select a lexical entry by the form's representation
| model | The model containing the appropriate lexica |
|---|---|
| form | The representation of the form |
| lang | The languages of the form |
Get entries by their written representation and properties
| model | The model containing all lexica |
|---|---|
| form | The written representation of the form |
| lang | The language of the form |
| props | The set of properties the entry object has |
Select a lexical entry by the form's representation, using regex
| model | The model containing the appropriate lexica |
|---|---|
| form | The representation of the form |
Get entries in a lexicon mapped by the references they have
| model | The model containing all the lexica |
|---|---|
| lexicon | The lexicon containg all entries |
| offset | The first entry to return |
| limit | The maxiumum number of entries to return, 0 for unlimited |
Get the set of entries that refer to a given reference
| model | The model containing the appropriate lexica |
|---|---|
| reference | The uri reference |
Get the set of entries that refer to a given sense
| model | The model containing the appropriate lexica |
|---|---|
| sense | The sense object |
Get the set of lexica containing a given entry
| model | The model containing the appropriate lexica |
|---|---|
| entry | The entry |


What is BPMN
BPMN is a standard Business Process Model and Notation, which provides businesses with the capability of understanding their internal business procedures in a graphical notation and gives organizations the ability to communicate these procedures in a standard manner. Furthermore, the graphical notation facilitates the understanding of the performance collaborations and business transactions between the organizations. This ensures that businesses will understand themselves and participants in their business and will enable organizations to adjust to new internal and B2B business circumstances quickly.
For further readings, see Business Process Model and Notation (Wikipedia) or Object Management Group Business Process Model and Notation.
About Process Modeller
Process Modeller is a free-to-use webapp to visualize BPMN diagramms. This webapp uses the BPMN.io framework as it's core.
The Repository
In the Repository you can view and access your stored BPMN project, displayed on project cards. Your options are to open, export and delete the BPMN project file.
History & version controll
This feature, only available trough the modeller page, allows you to view the changes you did to your project and if necessary, revert to an older state.
Import a BPM project
Here you can import a BPMN project file to your Process Modeller workspace.
Export a diagramm
The process Modeller allows you to export your BPMN project as project XML file, a SVG or PNG picture.
Please click on the button below and take part in a short survey.
Survey


‘We do not talk, we burgeon one another with facts and theories gleaned from cursory readings of newspapers, magazines and digests.’
- Henry Miller
Henry Miller wrote it in 1945, it's still the same. We talk ,but we rarely communicate. We figured out there is one golden time on the clock when we really communicate. It's 3:AM. You must have had a fun night with friends or family. We talk till 2 but we start sharing what really matters at 3:AM. This is the place where you can share your 3:AM stories at any time. We are here to listen. It can be type of story. Funny.Scary.Feel good. Embarrassing. Sad. Relationship. Crime. Anything!! We want to here it. 3:AM Story is a story that connects us all. When you share,you feel better. All the stories written on this site are by anonymous people.Many people emailed us saying it feels good when they write what they want to express without getting judged.These stories won't be conventional attractive one, but needed to get heard. We want to hear it,with complete anonymity to our 3AM stories sharers.We wouldn't comment but respond.This is the place you want to be. You can make your own category.Write your own story. This is your time. Go to categories, write. We are waiting.
POSTED BY BALLAL PATHARE. ON SEPT 20, 2016


Pre-built integrations and mappings simplify how you move your data into HubSpot
Load Accounts, Campaigns, Contacts and Leads across cloud services.
Data is secured using a complete 256 bit AES encryption scheme.
Select the services you from which to map and pull data into HubSpot.
Drag and Drop the fields you wish to map from each cloud service.
Flexible scheduling gives you the option to pull data from a day, week, month ago or more.
| HubSpot Resource | Also Known As | ZohoCRM | SugarCRM | Pipedrive |
|---|---|---|---|---|
| companies | accounts | |||
| contacts | ||||
| leads | Not Supported | |||
| owners | users | Not Supported | ||
| deals | potentials, opportunities | |||
| interactions | tasks, activities | (Tasks Only) |
Not Supported | |
| notes | Not Supported | Not Supported | ||
| custom fields | ||||
| email messages | Not Supported | Not Supported | Not Supported |


Tools to compare several model adjustment and validation methods prior to application in a final analysis.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.1.1) |
| Imports: | logistf, penalized, rms, graphics, stats, shrink |
| Suggests: | knitr, testthat, rmarkdown |
| Published: | 2015-11-24 |
| Author: | Romin Pajouheshnia [aut, cre], Wiebe Pestman [aut], Rolf Groenwold [aut] |
| Maintainer: | Romin Pajouheshnia <R.Pajouheshnia at umcutrecht.nl> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | apricom results |
| Reference manual: | apricom.pdf |
| Package source: | apricom_1.0.0.tar.gz |
| Windows binaries: | r-devel: apricom_1.0.0.zip, r-release: apricom_1.0.0.zip, r-oldrel: apricom_1.0.0.zip |
| OS X binaries: | r-release: apricom_1.0.0.tgz, r-oldrel: apricom_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=apricom to link to this page.


Spoilers: Car crash drama for Linda in EastEnders
Linda Carter (Kellie Bright) has been under immense pressure in EastEnders as of late, and as a result she’s turned to alcohol. However, her reliance on the substance begins to cause some serious problems in the coming episodes, as she ends up having a minor car accident — and is arrested as a result.
In spite of battling a hangover, Linda agrees to take Ollie to school so that Mick can head off to his doctor’s appointment. However, problems ensue when she accidentally backs into another vehicle outside the school gates.
She gives some thought about what to do for the best, but — upon realising that nobody’s seen the accident, she decides to remain shtum about the whole thing.
However, little does she know that someone was watching.
Later, Linda exits the school with Chantelle (Jessica Plummer) by her side, but she’s shocked to find Mieko and Shelley waiting for her with two police officers in tow.
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Linda attempts to defend herself but the officers insist that she take a breathalyser test, and she’s left feeling humiliated as a result.
However, humiliation is the least of her worries, as she’s arrested.
Will Linda face ramifications for her actions?
One to watch: Monday 25thNovember at 8pm on BBC One.


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Hurricane Matthew: I almost refused to evacuate. Here’s why I changed my mind.
By
Michael More Sanderson
How Donald Trump may have avoided 18 years of federal taxes, explained with a simple cartoon
By
Michael Sanderson
Let’s dispel with this notion that Donald Trump knows what he’s doing
By
Thomas Mitchell
In conversation with Junot Díaz: on the force field of privilege and the power of art
By
Laura Hawkins


{% include "./sidebar.html" %}
Abstract
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{% for img in images %} {% include "./image_block.html" %} {% endfor %}
{% include "./footer.html" %}


A week ago I received my results from 23andme.com. Aside from the obvious points of interest, health risks, heritage, neanderthal composition, etc., I was also interested in getting my own data in raw format. While 23andme does provide a way to download your “raw” data, they are not really providing raw data. One cannot access the image data from the microarray sequencer that they used. What they do provide is formatted as follows:
1 2 3 4 5 6 7 |
|
Rows that begin with a ‘#’ are header rows, of which, there may be as many as you please. 23andme puts some data in here, like which reference the coordinates are based on. This is an interesting topic as the build being used has just recently changed from hg18 to hg19. If you downloaded your raw data before August 9, 2012, you have hg18, after, and you have hg19. However, someone forgot to update the header to reflect this, so it still reads “build36”.
The rsid column is a unique identifier for reference SNP identifier from dbSNP. These identifiers were more useful before the completion of the human genome project, as there was no coordinate system capable of resolving the locations of these various SNP’s. Now it is possible to address them like you might address a house, with the State or City being analogous to the chromosome and the street address being analogous to the “position”. The position is the number of bases from the beginning of the chromosome that a SNP is located at.
The final column is the genotype at the listed address. There are two bases listed because humans have two copies of each chromosome.
VCF Format
So this leaves us with a list of addresses. This is well and good, but many bioinformatics applications use a different format, not all that different, called the “Variant Call Format”. Specifically, a tool for predicting the biological effects of mutations (bases different than the reference bases), uses the VCF format. It is snpEff, or SNP effect predictor.
In order to facilitate the use of the various and sundry tools that use the VCF format, I have made a tool for converting the 23andme raw format to VCF. It is the 23andme2vcf converter. In order to use it, follow these steps:
1 2 3 |
|
If you do not use git, you may download the tarball from github, unpack it, and run line 3 of the above commands.


OpHintArgumentTracker
Conceptually tracks indices of arguments of "OpHint functions".
The inputs and arguments of these functions both use an instance of the class so they can have independent numbering.
__init__
__init__( function_name, unique_function_id, node_name_prefix, attr_name, level=1, children_inputs_mappings=None )
Initialize ophint argument.
function_name
: Name of the function that this tracks arguments for.unique_function_id
: UUID of function that this tracks arguments for.node_name_prefix
: How identities that are created are named.attr_name
: Name of attribute to use to store the index for this hint.
i.e. FUNCTION_INPUT_INDEX or FUNCTION_OUTPUT_INDEXlevel
: Hierarchical level of the Ophint node, a number.children_inputs_mappings
: Inputs/Outputs mapping for children hints.add
add( arg, tag=None, name=None, aggregate=None, index_override=None )
Return a wrapped tensor of an input tensor as an argument.
arg
: A TensorFlow tensor that should be considered an argument.tag
: String tag to identify arguments that should be packed.name
: Name of argument. This is included in the Identity hint op names.aggregate
: Strategy to aggregate.
Acceptable values are OpHint.AGGREGATE_FIRST, OpHint.AGGREGATE_LAST,
and OpHint.AGGREGATE_STACK.
Note, aggregate is only valid if tag is specified.index_override
: Specify what input/output index should this be in the
final stub. i.e. add(arg0, index=1); add(arg1, index=0) will make the
final stub be as stub_func(inputs[arg1, arg0], outputs=[]) rather than
the default call order based ordering.A tensor representing the wrapped argument.
ValueError
: When indices are not consistent.


Hi!
I’m Maaike, a 4th year PhD student in the DTAI research group at KU Leuven, under the supervision of Professor Jesse Davis.
My research interests include artificial intelligence, data mining and machine learning, especially when applied to sports. My current research focuses on extracting tactical insights from soccer (event / positional) data using a combination of learning and reasoning techniques.
Prior to starting my PhD, I obtained a Master’s degree in Computer Science with a major in Artificial Intelligence at KU Leuven in 2019.
Besides computer science, my interests include playing soccer , traveling , and all things space-related .