Hi!
My Name is Stephen Batifol and I am looking for a
PhD in Machine Learning or a Data Scientist position.
I am a graduate student at
Paris
Sud University pursuing my Master's degree in Computer Science, with a major in Machine Learning. I am also doing a Magistère in Computer Science, which is a complementary
degree that is taken alongside the rest of my Master's degree and has a minimum GPA requirement for entry.
I studied as an undergraduate at
Paris Sud University
graduating
Cum Laude in Computer Science.
I wrote my Master's thesis at
NEC Europe Labs in Heidelberg, Germany where I worked on
Scalable Latent Feature Profiling with Topics Models.
The goal of my thesis was to develop a system that makes latent features understandable for humans. Most of the customers of NEC are not
machine learning experts and therefore, do not care about probabilities and are only interested in
simple outputs.
During the summer of 2016, I did a research internship at the
LIMSI-CNRS
laboratory in the
Automatic
translation and machine learning group. The goal of my internship was to implement an
automatic text segmentation in order to improve machine translation quality. You can find
more details in the
experience section below.
The year before that, I worked for
En Equipe where I developed the
Android application and their new website. The company has since been acquired, therefore the
application and the website are no longer maintained.


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PyData London 2018
Around 700 attendees across three days. Talks covering new techniques and applications of machine learning (ML), natural language processing (NLP), image classification, more traditional methods, graph theory and architecture of data science projects. This was my second PyData conference having previously attended the 2016 event.
If you look at one thing from the talk, pick one of these talks (details below):
- 'Winning with Simple, even Linear, Models' - for ways to get a lot out of linear models
- 'Planes, Trains, and Skateboard Shoes - Bayesian methods in engineering and product design' - just a great talk and intro to Gaussian processes.
- 'Building out data science at QBE' - to see how the competition are doing it.
- 'Python Doesn’t Have to Be Slow: Speeding Up a Large-Scale Optimization Algorithm' - how to get the most out of Python for computationally heavy processes.
From the talks and my chats with other attendees my takeaways are:
- Beyond particular techniques there is still a compelling argument for actuarial teams to adopt many data science practices (use of code, how to measuring model accuracy, version control, notebooks).
- Data science is still a young profession with attendees average age around 30 and many people coming from PhDs in the sciences. There is an energy and enthusiasm among the attendees that is quite infectious.
- Wide range of industries and academia (tech, fashion, taxi apps, supermarkets, insurance (only QBE), banking, telecoms, Google) represented - everyone is investing in this.
- Pace of innovation and development of open source data science is accelerating with new features added to existing tools and new tools being released all the time.
- As a result, fragmented ecosystem tools is a challenge as there are so many options and pros and cons of each option are not clear. Still the pros of open source out-way the cons in my opinion.
- Most people work within mixed teams of developers, IT, data science folk and end customers (e.g. marketers, traders, etc) rather than just with other data scientists which is very different to most actuarial teams in the insurance industry.
- Most people use Slack in their work teams for messaging (replacing email and instant messaging), macs and Linux for computing and Git for version control. Most people code and present their results through Jupyter notebooks. They are comfortable with cloud tools such as Amazon AWS and Google Cloud and avoid proprietary software as much as possible.
- Code is king - no-one is talking about GUIs for data science (although being PyData it is a biased sample). They may use code to build interfaces for exploring data or communicating with their clients.
All talks should end up here.
Friday
Computer Vision: An (Un?)Expected Journey, with Keras and Tensorflow
Speaker: Rodolfo Bonnin (Machinalis)
GitHub repository
Can also be run on Google CoLab
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
Keras seems to be a ML library with a straightforward syntax that incorporates many standard modelling techniques into the default fitting routines (e.g. validation).
Most of the neural net stuff was over my head but this talk introduced many concepts which will make it easier to get started if I start looking at image classification in more detail.
Use of Google CoLab was interesting.
Apache Airflow in the Cloud: Programmatically orchestrating workloads with Python
Speakers: Satyasheel, Kaxil Naik (Airflow contributor) both at Data Reply
GitHub repo
Failed to run on my machine due to a combination of Windows and Python 2 issues (Airflow was not working on Python 3 at the time, bug fixed by Sunday apparently). Airflow looks like the go to tool for managing tasks in complex calculations.
Looks like the goto tool for running workflows - potentially useful for ML and capital modelling.
Network Science, Game of Thrones and US Airports
Speaker: Mridul Seth
GitHub repo
Subject was very interesting and the examples helped with understanding the concepts.
Hypothesis Testing with SciPy
Speaker: Hillary Green-Lerman, head of data science at Codecademy.com
Codecademy Course
A bit basic for actuaries I suspect.
Winning with Simple, even Linear, Models
Speaker: Vincent Warmerdam, koaning.io
http://koaning.io/theme/notebooks/bayes.pdf
Talk differed from the title. Covered a lot of topics but key takeaway was that linear models and feature engineering still have a lot of value compared to more complex ML techniques.
Saturday
Keynote: Democratising data journalism: building a collaborative and investigative network across the UK
Speaker: Charles Boutaud
Data, Science: Investigating 1 Million Galaxies with Humans and TensorFlow
projects/penguintom79/penguin-watch
An astrophysics post grad on labelling galaxy images. He is using a website called zooniverse to get volunteers to crowd source labelling of galaxies.
Python Doesn’t Have to Be Slow: Speeding Up a Large-Scale Optimization Algorithm
Speaker: Dat Nguyen (Zopa)
Slides
- Speeding up their NP hard problem using a combination of Numpy over Pandas, joblib and Numba.
- Recommends profiling before optimisation and using ipython profiling.
- Preferred Numba over cython or C++ to keep code Pythonic.
- NamedTuples
- Joblib for parrallisation
- Numba
- Processes 1M assets in 20s
Creating correct and capable classifiers
Speaker: Ian Ozsvald modelinsight.io, founding member of PyData London
Slides
Working with QBE currently.
Data_science_delivered GitHub repo
- pandas_profiling - useful for high level view of data frame
- Use of dummy classifier for a baseline model
- Do repeatedkfold on dummy classifier to understand variability in response
- randomforest to provide new baseline
- YellowBrick highly recommended for visualising ML results
- improve confusion matrix with probabilities in cells
- ELI5 'explain it like I'm 5' library for sklearn models.
- Permeation importance method for finding variable importance across model types
- classification report on splits of data by key factors
- tSNE using fit error to spot poor performing regions
- Pandas colouring in Jupiter notebook?
Building out data science at QBE
Speakers: Natalie, Liam P. Kirwin, both QBE
- 8 data scientists, 4 software engineers, 20 people total
- Report to head of business intelligence
- One of 7 strategic themes of the company
- Team started with fraud
- Viewed QBE actuarial team as 'old school, better safe than sorry, do everything in Excel'
- Fraud check - checking GP register for GP's details
- A hard fight to get software they needed but now have good relationship with IT
- Noticeably less detailed talk than others - possibly due to not wanting to give away IP (but would equally apply to other presenters)
- Lime
Stationary data? Forget about it! Bayesian forgetting and Random Effects for forecasting TV ratings
Speaker: Ruadhán Stokes, Channel 4
Bayesian TV forecasting model. Could recursive least squares be applied to claims inflation?
https://github.com/rstokes92/pydata
Making the Big Data ecosystem work together with Python: Apache Arrow, Spark, Beam, and Dask
Speaker: Holden Karau, Google
Sunday
Learning programming and science with Scientific Python
Speaker: Emmanuelle Gouillart ( director of joint CNRS / Saint-Gobain)
JupyterHub from the Ground Up with Kubernetes
Speaker: Camila Montonen, @spimescape, race-conditions.net
Slides
JupyterHub is a way for creating a consistent porgramming environment with computing resources on remote servers.
Useful for companies, teaching or some.web services (quantopian)
Databases for Data-Science
Speaker: Alex Hendorf, Konigsweg
Slides
Do tyres dream of electric clouds?
Speaker: T. Alisi, Pirelli
Slides
- Data-Science team of around 20
- Used https://www.dominodatalab.com as a data analysis platform.
- See slide 18 for mix of teams and tools.
Using Survival Analysis to understand customer retention
Speaker: Lorna Brightmore, tails.com
Use of survival models to predict retention of customers to a dog food subscription service.
Python packages lifelines, sklearn-survival, or in R, KMSurv, OISurv
Planes, Trains, and Skateboard Shoes - Bayesian methods in engineering and product design
Speaker: Jim Parr, Maclaren Applied Technologies
GitHub rep
Used notebook slides which looked really cool. Use of Gaussian processes to optimise design of products. One of the best talks I saw.
Talks I missed
Test-Driven Data Analysis
https://github.com/tdda/pydatalondon2018ad
http://www.tdda.info/?from=@
Missed this one but looks interesting
Deep Probabilistic Methods with PyTorch
https://github.com/chrisorm/pydata-2018
Visualising NLP pipelines with Pynorama
Didn't see talk but new tool looks really useful. GitHub Repo.
Optimisation
https://github.com/gcampanella/pydata-london-2018
Evaluating fairness in machine learning with PyMC3
Couple of the papers mentioned in the fairness talk:
- Counterfactual Fairness https://arxiv.org/abs/1703.06856
- Fairness in Criminal Justice Risk Assessments: The State of the Art https://arxiv.org/abs/1703.09207
For the Fairness talk, Google has published an interactive visualisation for understanding various fairness policies: https://research.google.com/bigpicture/attacking-discrimination-in-ml/
Based on paper ‘Equality of Opportunity in Supervised Learning’: https://arxiv.org/abs/1610.02413
RNN sequence labeling for document parsing in Tensorflow
Speaker: Carsten van Weelden, textKernel, Nederland
Using recurring neural network (RNN) to parse over CVs to create structured data.
Used TensorBoard to visualise the NN.
Searching for Shady Patterns: Shining a light on UK corporate ownership
https://github.com/Cadarn/pyDataLDN2018_network_corporations
CatBoost
New ML technique that is yielding strong results.
Touchdown Localisation with aircraft flight data
More About Generators
Benefits of linear models
Making computation easier with cool Numpy tricks
https://github.com/kirit93/NumpyTutorial
Missed this one but heard lots of good things so need to watch the video.
Understanding and diagnosing your machine-learning models
Speaker: Gael Varoquaux, one of the founding contributors to sci-kit learnt
Missed this one but attendees said the talk was very good.
http://gael-varoquaux.info/interpreting_ml_tuto/
https://github.com/GaelVaroquaux/interpreting_ml_tuto
Demystifying pandas internals


Before Change
self._X = X
self._X2 = X2
if X2 is None: X2 = X
self._K_dist = X[:,None,:]-X2[None,:,:] // this can be computationally heavy
self._params = np.empty(shape=(1,0)) //ensure the next section gets called
if not np.all(self._params == self._get_params()):
self._params == self._get_params()
self._K_dist2 = np.square(self._K_dist/self.lengthscale)
self._K_dvar = np.exp(-0.5*self._K_dist2.sum(-1))
def _psi_computations(self,Z,mu,S):
//here are the "statistics" for psi1 and psi2
After Change
//_K_dist2 = np.square(_K_dist/self.lengthscale)
X = X/self.lengthscale
X2 = X2/self.lengthscale
self._K_dist2 = (-2.*np.dot(X, X2.T) + np.sum(np.square(X),1)[:,None] + np.sum(np.square(X2),1)[None,:])
self._K_dvar = np.exp(-0.5*self._K_dist2)
def _psi_computations(self,Z,mu,S):
//here are the "statistics" for psi1 and psi2


Score Player 1:
Score Player 2:
Roll
Hold
"Your Score for This Round"


--- layout: post title: 'test only: posting from YouTube(WoW Whatever) => sofasportler' date: 2006-11-25 11:37:49.000000000 +01:00 type: post published: true status: publish categories: - test - whatever tags: [] meta: _publicize_job_id: '14401147300' original_post_id: '51' _wp_old_slug: '51' author: login: joesixpack email<EMAIL_ADDRESS>display_name: dirk lüsebrink first_name: '' last_name: '' ---
getting into testing frenzy, posting videos from YouTUBE to the blog.
What i don't get is, i need uname and pass, ok, but what for they want an wordpress API KEY and the API URL for it on the YouTUBE side? The API URL turns out just to be the blog posting url(../xmlrpc.php in my case) which still leaves me with the question of what do they need the my API key for? account credentials should be sufficient. tbc|investigated...
update: i couldn't get the YouTube posting to work, the embedded video you see above got inserted manually, sigh.
Internet i must say, we're not yet there, not even close...


WITNESS LIST Environmental Regulation Committee April 5, 2005-8:00A HB 39 For: Hill, Glen (Self) Hill, Kelly (Self) On: Harwell, Phil (Tx Comm. on Environmental Quality) HB 1609 For: Brown, Gary (City of Floydada) Hanbury, Mark (City of Dalhart and Panhandle Regional Planning Comm. Solid Waste Advisory) King, William (City of Meadow) Powell, Jim (City of Perryton) Smith, James (City of Meadow) Tillman, Marvin (City of Olton) Against: Reed, Cyrus (Lone Star Chapter, Sierra Club) On: Schneider, Robin (Tx Campaign for the Environment) Wheatley, Wade (Tx Comm. on Environmental Quality) HB 1611 For: Alvarez, Ramon (Environmental Defense) Culver, Anne (Tx Clean Air Working Group) Eastland, Mike (North Central Tx Council of Governments) Morehead, Bee (Texas Impact) Stevenson, Shannon (North Central Tx Council of Governments) Walker, Scheleen (Travis Co. Commissioners Court) Wickersham, Tod (Mobile Emissions Reduction Coalition) HB 2370 For: Grimm, James (Texas Poultry Federation) HB 2793 For: Alvarez, Ramon (Environmental Defense) Harman, Dale (Tx Chaparral Steel Midlothian, LP and Steel Manufacturers & Recyclers of Tx) Iguaran, Ruben (Border Steel Inc. and Steel Manufacturers & Recyclers of Tx) Lambing, Debbie (Tx Auto Recyclers Assoc.) Luera, Noel (Nucor and Steel Manufacturers & Recyclers of Tx) Metzger, Luke (Tx Public Interest Research Group) Nasi, Michael (Commercial Metals Co. Steel Group) Peters, Michael (SMI-Texas and Steel Manufacturers & Recyclers of Tx) Pettigrew, Hugh (Tx Auto Recyclers Assoc.) Roane, Steve (Gerdau Ameristeel and Steel Manufacturers & Recyclers of Tx) Snyder, Dan (Tx Auto Recyclers Assoc.) Against: Andary, Casimer (Alliance of Automobile Manufacturers) Fellows, Anne Nolan (Ford Motor Co.) Good, Ross (Daimler Chrysler) On: Schanbacher, David (Tx Commission on Environmental Quality) Telander, Ellen (MN Waste Wise) HB 2862 For: Grimm, James (Texas Poultry Federation) HB 3141 Against: Reed, Cyrus (Lone Star Chapter, Sierra Club)


|
Spring Security Framework | |||||||||
| PREV NEXT | FRAMES NO FRAMES |
| Packages | |
|---|---|
| org.springframework.security | Provides core Spring Security interfaces and classes. |
| org.springframework.security.acl | Enables retrieval of access control lists (ACLs) for domain object instances. |
| org.springframework.security.acl.basic | Access control list implementation based on integer bit masks. |
| org.springframework.security.acl.basic.cache | Caches ACL information for the BasicAclProvider . |
| org.springframework.security.acl.basic.jdbc | JDBC-based data access object for ACL information. |
| org.springframework.security.acls | Interfaces and shared classes to manage access control lists (ACLs) for domain object instances. |
| org.springframework.security.acls.domain | Basic implementation of access control lists (ACLs) interfaces. |
| org.springframework.security.acls.jdbc | JDBC-based persistence of ACL information. |
| org.springframework.security.acls.objectidentity | Provides indirection between ACL packages and domain objects. |
| org.springframework.security.acls.sid | Provides indirection between ACL packages and security identities, such as principals and GrantedAuthority[]s. |
| org.springframework.security.adapters | Allows external containers to obtain authentication information from the system. |
| org.springframework.security.adapters.catalina | Adapter to Catalina web container (Tomcat). |
| org.springframework.security.adapters.jboss | Adapter to JBoss. |
| org.springframework.security.adapters.jetty | Adapter to Jetty web container. |
| org.springframework.security.adapters.resin | Adapter to Resin web container. |
| org.springframework.security.afterinvocation | Used for post-processing of an object returned from a secure object invocation. |
| org.springframework.security.annotation | |
| org.springframework.security.authoritymapping | |
| org.springframework.security.concurrent | Concurrent session control and registration classes. |
| org.springframework.security.config | |
| org.springframework.security.context | Provides a "request context". |
| org.springframework.security.context.httpinvoker | Enables use of Spring's HttpInvoker extension points to
present the principal and credentials located
in the ContextHolder via BASIC authentication. |
| org.springframework.security.context.rmi | Enables use of Spring's RMI remoting extension points to propagate
the ContextHolder (which should contain an
Authentication request token)
from one JVM to the remote JVM. |
| org.springframework.security.event.authentication | Enables events to be published to the Spring application context. |
| org.springframework.security.event.authorization | Provides support objects for security event interception (ie authorization). |
| org.springframework.security.intercept | Actually enforces the security and ties the whole security system together. |
| org.springframework.security.intercept.method | Provides support objects for securing Java method invocations via different AOP libraries. |
| org.springframework.security.intercept.method.aopalliance | Enforces security for AOP Alliance MethodInvocation s, such as via
Spring AOP. |
| org.springframework.security.intercept.method.aspectj | Enforces security for AspectJ JointPoint s, delegating secure
object callbacks to the calling aspect. |
| org.springframework.security.intercept.web | Enforces security for HTTP requests, typically by the URL requested. |
| org.springframework.security.ldap | |
| org.springframework.security.ldap.populator | LdapAuthoritiesPopulator implementations. |
| org.springframework.security.ldap.search | LdapUserSearch implementations. |
| org.springframework.security.providers | Implements a provider-based approach to authentication decisions. |
| org.springframework.security.providers.anonymous | Allows you to secure every invocation (especially useful for web request URI security) by always having either an actual principal or an anonymous principal authenticated. |
| org.springframework.security.providers.cas | An authentication provider that can process JA-SIG Central Authentication Service (CAS) service tickets and proxy tickets. |
| org.springframework.security.providers.cas.cache | Caches CAS tickets for the CasAuthenticationProvider . |
| org.springframework.security.providers.dao | An authentication provider that relies upon a data access object. |
| org.springframework.security.providers.dao.cache | Caches User objects for the DaoAuthenticationProvider . |
| org.springframework.security.providers.dao.salt | Implementations that provide salts for more secure password encoding. |
| org.springframework.security.providers.encoding | Password encoding implementations. |
| org.springframework.security.providers.jaas | An authentication provider for JAAS. |
| org.springframework.security.providers.jaas.event | Enables JAAS events to be published to the Spring application context. |
| org.springframework.security.providers.ldap | The LDAP authentication provider package. |
| org.springframework.security.providers.ldap.authenticator | LDAP authenticator implementations. |
| org.springframework.security.providers.openid | An authentication provider that can process OpenID Authentication Tokens as created by implementations of the OpenIDConsumer interface. |
| org.springframework.security.providers.preauth | |
| org.springframework.security.providers.rcp | Allows remote clients to authenticate and obtain a populated
Authentication object. |
| org.springframework.security.providers.rememberme | Authentication provider that processes RememberMeAuthenticationToken s. |
| org.springframework.security.providers.x509 | This package is now deprecated and will be removed in a future version. |
| org.springframework.security.providers.x509.cache | Deprecated and will be removed in a future version. |
| org.springframework.security.providers.x509.populator | This package is now deprecated and will be removed in a future version. |
| org.springframework.security.runas | Allows secure objects to be run under a different authentication identity. |
| org.springframework.security.securechannel | Classes that ensure web requests are received over required transport channels. |
| org.springframework.security.taglibs.authz | Java implementation of security taglib. |
| org.springframework.security.taglibs.velocity | |
| org.springframework.security.token | |
| org.springframework.security.ui | Authentication processing mechanisms, which respond to the submission of authentication credentials using various protocols (eg BASIC, CAS, form login etc). |
| org.springframework.security.ui.basicauth | Authenticates HTTP BASIC authentication requests. |
| org.springframework.security.ui.cas | Authenticates standard web browser users via JA-SIG Central Authentication Service (CAS). |
| org.springframework.security.ui.digestauth | Authenticates HTTP Digest authentication requests. |
| org.springframework.security.ui.logout | |
| org.springframework.security.ui.ntlm | |
| org.springframework.security.ui.ntlm.ldap.authenticator | |
| org.springframework.security.ui.openid | Authenticates standard web browser users via OpenID. |
| org.springframework.security.ui.openid.consumers | Implementations of the OpenIDConsumer interface using 3rd party libraries. |
| org.springframework.security.ui.portlet | Authentication interceptor (and related classes) for use with the Portlet 1.0 (JSR 168) Specification. |
| org.springframework.security.ui.preauth | |
| org.springframework.security.ui.preauth.header | |
| org.springframework.security.ui.preauth.j2ee | |
| org.springframework.security.ui.preauth.websphere | |
| org.springframework.security.ui.preauth.x509 | |
| org.springframework.security.ui.rememberme | Support for remembering a user between different web sessions. |
| org.springframework.security.ui.savedrequest | Stores a HttpServletRequest so that it can subsequently be emulated by the
SavedRequestAwareWrapper . |
| org.springframework.security.ui.session | HttpSession events and publisher classes. |
| org.springframework.security.ui.switchuser | Provides HTTP-based "switch user" (su) capabilities. |
| org.springframework.security.ui.webapp | Authenticates users via HTTP properties, headers and session. |
| org.springframework.security.ui.x509 | This package is now deprecated and will be removed in a future version. |
| org.springframework.security.userdetails | |
| org.springframework.security.userdetails.checker | |
| org.springframework.security.userdetails.hierarchicalroles | |
| org.springframework.security.userdetails.jdbc | Exposes a JDBC-based authentication repository. |
| org.springframework.security.userdetails.ldap | |
| org.springframework.security.userdetails.memory | Exposes an in-memory authentication repository. |
| org.springframework.security.util | General utility classes used throughout the Spring Security framework. |
| org.springframework.security.vote | Implements a vote-based approach to authorization decisions. |
| org.springframework.security.wrapper | Populates a Servlet request with a new Spring Security compliant
HttpServletRequestWrapper . |
| org.springframework.web.portlet.sample |
|
Spring Security Framework | |||||||||
| PREV NEXT | FRAMES NO FRAMES |


CrimPapers
Articles published on 31 October 2019
On 31 October 2019, 6 new articles were published in 5 journals.
Make Sense of Self in Prison Work: Stigma, Agency, and Temporality in A Chinese Women’s Prison
Patient‐rated Impulsivity and Aggression Compared With Clinician‐rated Risk in A Forensic Psychiatric Sample: Predicting Inpatient Incidents by Julie Karsten,
gerjonne J. Akkerman‐bouwsema,
loes A. Hagenauw,
coby Gerlsma,
marike Lancel
Valeria Vegh Weis: Marxism and Criminology: A History of Criminal Selectivity
The Electronic Monitoring of Offenders in Context: From Policy to Political Logics
Hearing and Justice: the Link Between Hearing Impairment in Early Childhood and Youth Offending in Aboriginal Children Living in Remote Communities of the Northern Territory, Australia by Vincent Yaofeng He, Jiunn-Yih Su, Steven Guthridge, Catia Malvaso, Damien Howard, Tamika Williams and Amanda Leach
Book Review: Punishing Disease: Hiv and the Criminalization of Sickness by Jordan Nichols


Beta This is a test version of the layout of this page. Take the survey to help us improve it
Collection
The EFA contractors framework is for use for all school building construction projects
The new Education Funding Agency (EFA) contractors framework was launched in November 2013. This framework can be used to design and build larger schools and is suitable for either single or grouped schools projects.
The contractors framework can be used to deliver schools totalling £4 billion in capital cost and will expire in November 2017.
The companies appointed to the contractors framework (alphabetically by geographical area) are:
| Sector north | Sector south |
| Balfour Beatty Group Plc | Balfour Beatty Group Plc |
| BAM Construction Ltd | BAM Construction Ltd |
| Bowmer & Kirkland Limited | Bowmer & Kirkland Limited |
| Carillion Construction Limited | Carillion Construction Limited |
| Galliford Try Construction Ltd | Galliford Try Construction Ltd |
| Kier | Kier |
| Sir Robert McAlpine | Sir Robert McAlpine |
| Thomas Vale Construction Plc | Wates Construction Ltd |
| Wates Construction Ltd | Willmott Dixon |
The standard preparation and procurement documents and templates for preparing a project for the contractors framework are available from the download section on the right-hand side of this page. If you are considering the use of this framework please contact the EFA at:
Email<EMAIL_ADDRESS>The regional framework was launched in July 2014. This framework is suitable for smaller projects such as block replacements, smaller schools and refurbishment projects.


A FISH CALLED WANDA A film review by Peter van der Linden
A local theater previewed A FISH CALLED WANDA last weekend. A FISH CALLED WANDA is an awkward title for a very funny film. John Cleese (who wrote and stars in, but does not direct this film) is back on form! If you like zany comedies, then you'll love this. Some of Cleese's earlier solo films were patchy (PRIVATES ON PARADE), and some were downright boring (CLOCKWISE), but here we see sustained, clever, inventive comedy. It simply gleams with wit!
The story line is straightforward, based on a gang of double-crossing jewel-thieves after a successful raid. The story is set in London, and it's a pleasure to see the care taken with the location shooting (apart from the final shot of the speeding car heading from the Old Bailey to Heathrow; why are you going via Oxford, John?) Some of the film editing is a bit clumsy, too (how does Michael Palin end up on the luggage conveyor at the airport?). Kevin Kline is superb as the ex-CIA hitman, sneering at the Brits.
The audience broke into spontaneous applause at the end of this film, and you don't hear that very often these days. A FISH CALLED WANDA is funny, contains sharp characterizations, and deserves to be an extraordinary success.
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


https://api.free-proxies.info/v1/proxy/list?api_key=[API_KEY]
&country_code=IT&anonymityLevel=anonymous&google=true&elapsed=5&get=true&post=true&https=true&port=8080
| Name | Type | Value | Description |
|---|---|---|---|
| api_key | string | Register to get your free API key | REQUIRED Your API key (check your account settings for the request. You need to make the request from the same host). |
| country_code | string | ISO 3166-1 alpha-2 | Add this to retrieve only proxies at this location. Comma-separate multiple values to search with OR condition. DEFAULT: All countries |
| anonymityLevel | string | anonymous, or transparent | Add this to retrieve only proxies with a specific level of anonymity. DEFAULT: All types |
| boolean | is a google proxy? | Add this to retrieve only proxies that works with google (HTTP; HTTPS) DEFAULT: All types |
|
| https (future: protocols) | boolean (future: string) | actuale a boolean; future values: http, https, socks4, or socks5 | Add this to retrieve only proxies with a specific protocol (actual only https). Comma-separate multiple values to search with OR condition. DEFAULT: All protocols |
| elapsed | boolean | digit from 0 to 20 (max second for timeout request) | Only retrieve proxies that were tested to with a max latency of the number you write (less is better). DEFAULT: < 3 |
| get or post | boolean | true or false, to define the both parameters | Only retrieve proxies with a specif method. get parameters is for get only method.DEFAULT: All methods |
| port | integer | 80, 8080 ... | Only retrieve proxies with a specif port. Comma-separate multiple values to search with OR condition. DEFAULT: All ports |
{ "address": "<IP_ADDRESS>", "anonymityLevel": "transparent", "cookies": true, "country_code": "IT", "full_address": "<IP_ADDRESS>:1189", "get": true, "port": "1189", "post": true, "referer": true, "supportHttps": true, "user_agent": true, "websites": { "amazon": false, "google": true } }


Robot:
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disconnected
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Unknown state
Autonomous:
Blue
Red
2019
2018
Path Planning


Best Lines from the movie The Departed. Frank Costello (Jack Nicholson) : When I was your age they would say we can become cops, or criminals. Today, what I'...
We’re doomed to permanent bloodshed and power struggle
That’s the human condition
I have all of human history to back me up
Prove me wrong
@Deleted User i don’t watch tv
I’ve been banned from *most social media(edited)
*Still kicking on twitter acct #3
To the north maybe?
Venezuela
Bet she wasn’t fat
1
I’m a burger, through and through, what’s the situation on the ground there
Apparently the entire amazon is on fire
And Venezuela should be entirely dead
/burgernews
Suspicious0bservers drops their climate vid tomorrow
The chairman of the US SEC says he is for technological solutions that reduce the cost of international payments, but the SEC won’t change the law to facilitate them.


Daniel Ritchie
Researcher ~ Educator ~ Programmer
I am a PhD Student in Education at the University of California, Irvine, with a specialization in Digital Media. My research focus is interactive educational technology and technology education, and I work with Dr. Mark Warschauer, Dr. Ying Xu, and other amazing scholars at the UCI Digital Learning Lab.
My upcoming dissertation work will involve co-designing, engineering, and then testing both a curriculum and a web-based tool to teach gamified data literacy and artificial intelligence literacy to middle school students.
My hobbies and interests include playing video games, Dungeons and Dragons, soccer, and keeping up-to-date on Marvel movies.
Mapping data collected about course design from Canvas to instructor behavior.
May 2023 - Present
July 2021 - Present
Digital Learning Lab, UC Irvine
June 2020 - September 2020
Polar
June 2019 - June 2020
Center for Regional Change, UC Davis
June 2019 - August 2019
ThoughtSTEM
Xu, Y., Wang, D., Yu, M., Ritchie, D., Yao, B., Wu, T., Zhang, Z., Li, T., Bradford, N., Sun, B., Hoang, T., Sang, Y., Hou, Y., Ma, X., Yang, D., Peng, N., Yu, Z., & Warschauer, M. (2022). Fantastic questions and where to find them: FairytaleQA— An authentic dataset for narrative comprehension. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL ‘22).
Zhang, Z., Xu, Y., Wang Y., Yao, B., Ritchie, D., Wu, T., Yu, M., Wang, D., & Li, T. (2022). Storybuddy: A human-AI collaborative agent for parent-child interactive storytelling. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ‘22).
Ritchie, D. (2020). Review of existing video games for computer science education. Prized Writing, 31, 187-197.
2026 (Expected)
2021


'Typical Hull' - The Slaven Bilic message that kept West Brom top
Hull City 0-1 West Brom | A Jake Livermore first half strike was enough to earn all three points at the KCOM and keep them top of the league
by Ben Husband, https://www.birminghammail.co.uk/authors/ben-husband/Slaven Bilic has revealed he told his West Bromwich Albion players they needed to dig in to earn all three points against Hull City.
Jake Livermore gave Albion the lead in the first half, with a scorching strike from distance.
And they were made to work hard to hold onto that advantage, with the home side piling on the pressure in the second half. But Bilic, who saw his side stay at the top of the Championship, was pleased with his side's willingness to adapt their game and win in what was a difficult situation.
“That’s the aim [to win in any situation]. I said to the guys at half time. We had to manage it more maturely. Don’t get me wrong, Hull is a kind of team who, unless they risk totally, you have to give them something for them to hurt you.
“You have to lose the ball, and not be in the positions that allows them to make the chances that Grosicki had. In the first half we gave them a couple of those situations, but at the same time we were able to pass the ball very fluidly in the first half.
“We had to continue that, because you can’t defend and sit back for 45 minutes, but we had to manage the game a bit better. We were going to lose the ball, so we had to have enough numbers at the back to be ready to stop them from hurting us. That’s what we did in the second half.”
West Brom latest
This is your round up of all things West Brom; the one-stop shop that will keep you updated on the latest goings on at the club and beyond.
Transfers, injuries, match-days and managers, we’ve got you covered.
We’ll be bringing the very latest on the Baggies throughout the week and around the clock.
Make sure you keep yourself updated with our handy daily catch up...
Must reads...
- 'Typical Hull' - The Bilic message that kept Albion top - READ
- Bilic confronts a fan and other things you missed - READ
- Player ratings as Livermore & the leaders haunt Hull - READ
- Albion suffer double blow ahead of Sheffield Wednesday - READ
For all your latest WBA news, opinion, analysis and transfer gossip, click here
You can follow our West Brom reporter Joseph Chapman on Twitter, and his email address is<EMAIL_ADDRESS>Bilic added: “It was a good game, it was a game with two teams who came into this game with a confidence.
“Both teams had a great run in the last few games. We expected it from them. They’re very good on transitions, the way they had their chance from Grosicki - it’s typical Hull. We didn’t manage to get our full-back from the other side inside.
“Overall it was a very good performance from us, the only thing that was missing was that second goal.”


Shortcuts allow quick access to some of your communities. Search your communities and click on toad them into your shortcut list.
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MarTeX-Cpp is a flexable, extendable and fast TeX-to-HTML converter by fully tokenizing-lexing-parsing-interpreting the TeX source. It can be compiled to serve as a module for different languages, like PHP or JavaScript. It's goal is to provide a way to allow users to write TeX they are familiar with to produce nice looking pages like this one, but without allowing code injection.
Make a big fancy title.
Make a chapter title.
Make a section title.
Make a subsection title.
Make a subsubsection title.
Render Text in bold.
Render Text in italics.
Render Text underlined.
Render Text .
Render Text monospaced.
Make a horizontal line.
Line break, equivalent to a double backslash.
Reference a label (from an image, for example). Works with both forward and backwards declaration (The label can be both above and below the ref command). Outputs a question mark when the label is undefined.
Set the global Variable to Value. Often used to change module behaviour.
Make a hyperlink to URL with text Text
Change the colour of a piece of text. \colour{ff00ff}{text}
| Command | Result | Command | Result | |
| \& | & | \"AaEeIiOoUuy | ÄäËëÏïÖöÜüÿ | |
| \% | % | \'AaEeIiOoUuZ | ÁáÉéÍíÓóÚúŹ | |
| \$ | $ | \`AaEeIiOoUu | ÀàÈèÌìÒòÙù | |
| \copy | © | \^AaEeIiOoUu | ÂâÊêÎîÔôÛû | |
| \> | > | \^AaEeIiOoUu | ÂâÊêÎîÔôÛû | |
| \< | < | \~AaIiOoNnUu | ÃãĨĩÕõÑñŨũ | |
| \} | } | \.AaUu | ÅåŮů | |
| \{ | { | \-Oo | Øø | |
| \cdot | · | \ss | ß | |
| \euro | € | \Alpha\alpha | Αα | |
| \pound | £ | \Beta\beta | Ββ | |
| \deg | ° | ... | ||
| \backslash | \ | \Omega\omega | Ωω |
Images are pretty. Normally the images try to fill the page width, you can control this behaviour with the provided sizing options. If you add a caption to an image it will put "Figure 1: caption" under it. You can change "Figure" to , for example, "Picture" by setting the header with a \define{header}{Picture }.
Use to display an image.
Use to display text under your image.
Use to give your image a label, so you can use \ref{label} to reference it.
Set the width of your image. Width can have the following formats: 10 (this is a percentage), 10px, 10cm, 10em.
Set the height of your image. Height can have the following formats: 10 (this is a percentage), 10px, 10cm, 10em.
Set the alt text, also called hovertext, of your image.
\begin{figure} \includegraphics{test.png} \caption{This is a test image} \label{testimage} \width{120px} \height{30} \alttext{A mouse!} \end{figure}
Note that there are two different list environments: enumerate and itemize with a different default markers, respectively numbers and bullets.
Mark the start of the next item in the list.
Set the marker type. Valid types are: square, bullet, circle, none, numbers, letters, LETTERS, roman, ROMAN.
\begin{itemize} \setmarker{square} \item Apple \item Banana \item Kiwi \item Pear \end{itemize}
Tables are a good way to represent content in a neat way. In MarTeX they behave pretty similar to the LaTeX tabulars. The tabular format accepts '|' for vertical lines, 'l' for left aligned column, 'c' for a centered column and 'r' for a right aligned column.
Add a horizontal line at this position in the table. Maximum of two lines per row.
Make a cell span over N columns. You can add special formatting to this cell (so just like your table formatting).
Make a cell span over N rows
\begin{tabular}[|| l | c | r ||] \hline \hline 1 & 2 & 3 \\\hline 4 & 5 & 6 \\\hline 7 & 8 & 9 \\\hline \multicolumn{3}{| c |}{0} \\ \hline \end{tabular}
Please feel free to submit anything! The only thing I ask is that you include at least one test that verifies the behaviour of your change.
If you find a way insert arbitrary html tags and/or get javascript execution from a certain input string then first I'd like to congratualate you on a job well done! Please contact me privately with said input and we'll work on pushing out a fix as quickly as possible. Because I'm still a student there is unfortunately no hard cash to be made here, but certainly there is coffee and cake in it for you!
Thanks to my committee for their endless patience and enthusiasm while listening to me whining on about this.
Thanks to Diego Perini for writing a nifty regex-based URL validator.
This project is licensed under the MIT License - see the LICENSE.md file for details


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Founded in 2010, Vardaan Precast has gained an admirable position in manufacturing, supplying, trading and service providing of GRC Components, Product Mould Services, GRC 3D Wall, GRC Balustrades, GRC Wall Panel, GRC Ceilings, GRC Cladding Panels, GRC Domes, GRC Screens and Core Cutting Machine.
About Vardaan Precast
The Begning of new era
Founded in 2010, Vardaan Precast has gained an admirable position in manufacturing, supplying, trading and service providing of GRC Components, Product Mould Services, GRC 3D Wall, GRC Balustrades, GRC Wall Panel, GRC Ceilings, GRC Cladding Panels, GRC Domes, GRC Screens and Core Cutting Machine.
About Our Products
These products are extremely admired in the market owing to their water resistance, heat resistance, easy to use, affordable rate, attractive design, and low maintenance. Our offered products are made utilizing the best quality of input. These inputs are obtained from trustworthy retailers of market. In addition, in order to present the reliable products, we check them on varied quality parameters. In addition, we offer our clients reliable services such as Finished Product Services, Installation Services, Screen Grill Design and GRC Services. These services are handled and completed by industry known experts who have rich industry skill and knowledge. Furthermore, we follow the current market trends in the making of our products and delivering our services.
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EBD - Easton Bible DIctionary
Hill of evil counsel
HILL OF EVIL COUNSEL
"HILL OF EVIL COUNSEL "on the south of the Valley of Hinnom. It is so called from a tradition that the house of the high priest Caiaphas, when the rulers of the Jews resolved to put Christ to death, stood here.
"HILL OF EVIL COUNSEL "on the south of the Valley of Hinnom. It is so called from a tradition that the house of the high priest Caiaphas, when the rulers of the Jews resolved to put Christ to death, stood here.


NOTE: THIS DOCUMENT IS INCOMPLETE.
The specification of binary integer values is a common task usually accomplished using hexidecimal literals. This is an unnecessary and error-prone indirection between what is intended and what is accomplished.
The simplest method of converting binary literals to values is to perform the conversion at runtime.
#include <stdio.h> #include <stdlib.h> unsigned long binary(const char* x) { unsigned long r = 0; while (*x) (r *= 2) += *x++ - '0'; return r; } int main(void) { printf("%lu\n", binary("101010")); return EXIT_SUCCESS; }
Besides the inefficiency of runtime computation, the major drawback of this approach is that the result cannot be used as a compile-time constant.
(On the other hand, the major advantage of this approach is that it can do the computation at runtime--which is important in its own right.
int main(int argc, char* argv[]) { if (argc < 2) { return EXIT_FAILURE; } printf("%lu", binary(argv[1])); return EXIT_SUCCESS; }
Neither template metaprogramming nor preprocessor metaprogramming can achieve that.)
In C++, template metaprogramming can be used to specify binary literals by reinterpreting the value of decimal literal (containing nothing but 0
's and 1
's).
#include <iostream> template<class T, T V> struct map_integral { static const T value = V; }; template<class T, T V> const T map_integral<T, V>::value; template<unsigned long x> struct binary : map_integral<unsigned long, binary<x / 10>::value << 1 | x % 10> { }; template<> struct binary<0> : map_integral<unsigned long, 0> { }; int main(void) { std::cout << binary<11111111>::value << '\n'; // prints 255 return 0; }
However, there are a few drawbacks to using the template mechanism for this purpose, the most obvious of which is that this approach can only be used in C++. The other drawbacks are more subtle....
Integer literals cannot contain enough digits to specify the full range of the greatest-width integer.
If, for example, an unsigned long
is a 32-bit integer, a decimal literal would require thirty-two digits to fully specify each bit--which is well outside the range of a 32-bit integer.
binary<10101010101010101010101010101010>::value // error!
Thus, in order to specify such a value, the bits must be separated into groups and processed semi-independently. The following implementation uses four groups of at most eight bits (note that, for simplicity, the value of a particular bit group isn't checked for overflow):
#include <iostream> template<class T, T V> struct map_integral { static const T value = V; }; template<class T, T V> const T map_integral<T, V>::value; template<int A, int B = -1, int C = -1, int D = -1> struct binary : map_integral< unsigned long, binary<A, B, C>::value << 8 | binary<D>::value > { }; template<int A, int B, int C> struct binary<A, B, C> : map_integral< unsigned long, binary<A, B>::value << 8 | binary<C>::value > { }; template<int A, int B> struct binary<A, B> : map_integral< unsigned long, binary<A>::value << 8 | binary<B>::value > { }; template<int A> struct binary<A> : map_integral< unsigned long, binary<A / 10>::value << 1 | A % 10 > { }; template<> struct binary<0> : map_integral<unsigned long, 0> { }; int main(void) { std::cout << binary<11111111>::value << '\n' << binary<11111111, 11111111>::value << '\n' << binary<11111111, 11111111, 11111111, 11111111>::value << '\n'; return 0; }
(With a little help from preprocessor metaprogramming, the boilerplate of this metafunction implementation can be extended to handle (nearly) arbitrary numbers of bit groups. However, doing so would probably be overkill, as the greatest-width integer type is unlikely to grow fast (or differ from platform to platform) enough to justify the boilerplate of the preprocessor generation itself.)
The reliance on the greatest-width integer type illustrates another drawback of the template-based approach. The compiler cannot perform arbitrary-precision arithmetic (at least, not directly). As such, there is a (relatively low) limit on the maximum integer width on which the compiler can perform arithmetic. This isn't terrible--most results need to be stored in some integer variable anyway. Nevertheless, the limitation exists.
The most subtle drawback of the template-based approach is that the value of each bit group must be either 0
or begin with 1
.
Otherwise, the literal is treated as octal instead of decimal--which fouls up the entire mechanism:
binary<00000010>::value // 8 (not 2)
Thus, binary literals cannot be specified (as they typically are) with leading 0
's to fill up some specific width.
That limitation is not only annoying, but is fundamentally error-prone because there is no way to verify the original forms of the input values.
(One possible solution to this problem is to alter the implementation to expect hexidecimal numbers instead of decimal numbers.
This would allow leading 0
's at the inconvenience of prefixing each value with 0x
or 0X
.)
Though the implementation can be specified in a number of different ways, these drawbacks are fundamental. The second, third, and fourth drawbacks are all the result of a single root issue. The above code acts on integral values instead of acting on the literals themselves.
As it happens, there is a language mechanism that can operate (to a degree) on literal values--macros.
Given some data structure of bits (i.e. 0
's and 1
's), it is relatively easy to calculate a decimal value by accumulating the bits.
unsigned long binary(const char* x) { unsigned long r = 0; while (*x) { (r *= 2) += *x++ - '0'; } return r; }
Each time a bit is found, the algorithm doubles the running result and adds the value of the bit.
Instead of accumulating the elements of a data structure by manually looping (or recursing), a generalized notion of "accumulation" can be used--std::accumulate
.
#include <cstring> #include <numeric> unsigned long binary(const char* x) { struct local { static unsigned long exec(unsigned long x, char bit) { return x * 2 + (bit - '0'); } }; return std::accumulate(x, x + std::strlen(x), 0UL, &local::exec); }
This is a higher-order transformation which yields a design that has greater similarity to a typical preprocessor-based design than the original iterative algorithm.
Note that the above transformation is actually two transformations.
The first is the abstraction of looping itself (e.g. the loop body is executed repeatedly until some supplied predicate yields false
).
The second is the abstraction of the terminating condition--when the input sequence is exhausted.
Direct iteration, such as the while
loop above, is impossible with the preprocessor.
However, the code can be rewritten recursively--which can be mirrored with the preprocessor.
unsigned long binary(const char* x, unsigned long r = 0) { return *x ? binary(x + 1, r * 2 + (*x - '0')) : r; }
It is possible to implement a preprocessor-based version at any of these (not counting the iterative version) levels of abstraction. (The following examples all use a string data structure to specify bits.)
Direct translation of the recursive version requires a much more detailed understanding of how recursion is generalized in Chaos. For the sake of comparison, it is listed here:
#include<chaos/preprocessor/arbitrary/add.h>
#include<chaos/preprocessor/arbitrary/demote.h>
#include<chaos/preprocessor/arbitrary/mul.h>
#include<chaos/preprocessor/control/iif.h>
#include<chaos/preprocessor/recursion/basic.h>
#include<chaos/preprocessor/recursion/expr.h>
#include<chaos/preprocessor/string/core.h>
#define BINARY(string) BINARY_S(CHAOS_PP_STATE
(), string) #define BINARY_S(s, string) \CHAOS_PP_EXPR_S
(s)(BINARY_I( \CHAOS_PP_OBSTRUCT
(),CHAOS_PP_NEXT
(s), string, (0) \ )) \ /**/ #define BINARY_INDIRECT() BINARY_I #define BINARY_I(_, s, string, x) \CHAOS_PP_IIF
_(CHAOS_PP_STRING_IS_CONS
(string))( \CHAOS_PP_EXPR_S
_(s)(BINARY_INDIRECT _()( \CHAOS_PP_OBSTRUCT
_(),CHAOS_PP_NEXT
(s), \CHAOS_PP_STRING_TAIL
_(string), \CHAOS_PP_ARBITRARY_ADD
_( \CHAOS_PP_ARBITRARY_MUL
_(x, (2)), \ (CHAOS_PP_STRING_HEAD
_(string)) \ ) \ )), \CHAOS_PP_ARBITRARY_DEMOTE
_(x) \ ) \ /**/ BINARY(1 0 1 0) // 10
This version is the lowest-level, and, as such, it is likely the most efficient. However, the code is dominated by code to emulate recursion rather than code to calculate the value of a binary literal.
A cleaner implementation can be designed if the level of abstraction is increased.
The next step up from low-level recursion is the use of a higher-order looping construct, such as CHAOS_PP_WHILE
, which eliminates the need to deal with recursion.
#include<chaos/preprocessor/arbitrary/add.h>
#include<chaos/preprocessor/arbitrary/demote.h>
#include<chaos/preprocessor/arbitrary/mul.h>
#include<chaos/preprocessor/array/elem.h>
#include<chaos/preprocessor/control/while.h>
#include<chaos/preprocessor/facilities/as_args.h>
#include<chaos/preprocessor/recursion/expr.h>
#include<chaos/preprocessor/string/core.h>
#define BINARY(string) BINARY_S(CHAOS_PP_STATE
(), string) #define BINARY_S(s, string) \CHAOS_PP_ARBITRARY_DEMOTE
(CHAOS_PP_ARRAY_ELEM
( \ 1, \CHAOS_PP_EXPR_S
(s)(CHAOS_PP_WHILE_S
( \ s, \ PREDCHAOS_PP_AS_ARGS
(2), \ OPCHAOS_PP_AS_ARGS
(2), \ (2, (string, (0))) \ )) \ )) \ /**/ #define PRED(s, string, x)CHAOS_PP_STRING_IS_CONS
(string) #define OP(s, string, x) \ (2, ( \CHAOS_PP_STRING_TAIL
(string), \CHAOS_PP_ARBITRARY_ADD
( \CHAOS_PP_ARBITRARY_MUL
(x, (2)), \ (CHAOS_PP_STRING_HEAD
(string)) \ ) \ )) \ /**/ BINARY(1 0 1 0) // 10
This version, as far as clarity is concerned, is much better than the raw recursive version.
However, there are still a few annoyances.
The state on which the loop operates includes both the string of bits and the running result.
This means that the operation has to operate on both in order for the predicate to eventually yield 0
.
Likewise, when the loop does terminate, the result is both the nil string and the arbitrary-precision value that holds the result.
Thus, the actual result must be extracted (in this case, with CHAOS_PP_ARRAY_ELEM
).
All of these annoyances can be eliminated if the level of abstraction is increased yet again.
The next step up is to use a higher-order algorithm that generalizes the notion of accumulation--which is also known as "folding."
In this example, the algorithm of choice is CHAOS_PP_FOLD_LEFT
.
#include<chaos/preprocessor/algorithm/fold_left.h>
#include<chaos/preprocessor/arbitrary/add.h>
#include<chaos/preprocessor/arbitrary/demote.h>
#include<chaos/preprocessor/arbitrary/mul.h>
#include<chaos/preprocessor/recursion/expr.h>
#include<chaos/preprocessor/string/core.h>
#define BINARY(string) BINARY_S(CHAOS_PP_STATE
(), string) #define BINARY_S(s, string) \CHAOS_PP_ARBITRARY_DEMOTE
( \CHAOS_PP_EXPR_S
(s)(CHAOS_PP_FOLD_LEFT_S
( \ s, OP, (CHAOS_PP_STRING
) string, (0) \ )) \ ) \ /**/ #define OP(s, bit, x) \CHAOS_PP_ARBITRARY_ADD
( \CHAOS_PP_ARBITRARY_MUL
(x, (2)), (bit) \ ) \ /**/ BINARY(1 0 1 0) // 10
The above example eliminates the problems associated with the template-based approach.
It unifies the syntax by eliminating the need for groups of bits, it minimizes the "maximum value" problem, and it avoids the "octal literal" issue.
However, this implementation has its own drawback--the binary literal itself must be encoded in a string data structure (e.g. 1 0 1 0
as opposed to 1010
).
That isn't too terrible, but it isn't ideal.
Maybe the idea of having groups of bits isn't such a bad idea after all. It is possible to support groups of bits with the preprocessor as well. Such a syntax would look something like
BINARY(10101010 10101010)
The major drawback of this approach is that it requires 256 macros (for eight-bit groups) to transform a group into something that can be processed.
Beyond that, the main problem is that 10101010 10101010
(and similar) is not a valid string because each element has more than one character.
In fact, it isn't any library-defined data structure.
Thus, the special form must be manually converted (using a set of 256 macros) before the result can be accumulated.
This is accomplished with a CHAOS_PP_WHILE
loop that transforms each "element" into a string.
#include<chaos/preprocessor/algorithm/fold_left.h>
#include<chaos/preprocessor/arbitrary/add.h>
#include<chaos/preprocessor/arbitrary/demote.h>
#include<chaos/preprocessor/arbitrary/mul.h>
#include<chaos/preprocessor/config.h>
#include<chaos/preprocessor/control/while.h>
#include<chaos/preprocessor/detection/is_nullary.h>
#include<chaos/preprocessor/facilities/split.h>
#include<chaos/preprocessor/logical/compl.h>
#include<chaos/preprocessor/recursion/expr.h>
#include<chaos/preprocessor/string/core.h>
#ifCHAOS_PP_VARIADICS
#define BINARY(x) BINARY_S(CHAOS_PP_STATE
(), x) #define BINARY_S(s, x) \CHAOS_PP_ARBITRARY_DEMOTE
( \CHAOS_PP_EXPR_S
(s)(CHAOS_PP_FOLD_LEFT_S
( \ s, ACC, \ (CHAOS_PP_STRING
)CHAOS_PP_SPLIT
( \ 0, \CHAOS_PP_EXPR_S
(s)(CHAOS_PP_WHILE_S
( \ s, PRED, OP,, x \ )) \ ), \ (0) \ )) \ ) \ /**/ #define ACC(s, bit, x) \CHAOS_PP_ARBITRARY_ADD
( \CHAOS_PP_ARBITRARY_MUL
(x, (2)), (bit) \ ) \ /**/ #define PRED(s, r, x) \CHAOS_PP_COMPL
(CHAOS_PP_IS_NULLARY
(x())) \ /**/ #define OP(s, r, x) \ rCHAOS_PP_SPLIT
(0, BYTE_ ## x),CHAOS_PP_SPLIT
(1, BYTE_ ## x) \ /**/ #define BYTE_00000000 0 0 0 0 0 0 0 0, #define BYTE_00000001 0 0 0 0 0 0 0 1, #define BYTE_00000010 0 0 0 0 0 0 1 0, // ... #define BYTE_11111111 1 1 1 1 1 1 1 1, BINARY(00000101) // 5 BINARY(10001000) // 136 BINARY(11111111) // 255 BINARY(11111111 00000000) // 65280 #endif
(The BYTE_
boilerplate can be pre-generated with a small program such as the following:
#include <stdio.h> #include <stdlib.h> void byte(int depth) { static char s[9] = { 0 }; if (depth == 8) { printf( "#define BYTE_%s %c %c %c %c %c %c %c %c,\n", s, s[0], s[1], s[2], s[3], s[4], s[5], s[6], s[7] ); } else { s[depth] = '0'; byte(depth + 1); s[depth] = '1'; byte(depth + 1); } return; } int main(void) { byte(0); return EXIT_SUCCESS; }
It isn't included here because it results in 256 macro definitions--which would waste space without providing further illumination.) This implementation has a couple of properties that are good and a couple that are bad--depending on perspective. It forces each element to be a full eight bits--which is a primitive form of validation. The main concern with the above is that it wastes time doing the conversion from the special form to a string. For a small number of groups, this overhead isn't too bad, but perhaps it can be eliminated altogether....
The central point of the following implementation is that a separate special form conversion can be avoided if a new data type is defined--in which case it is no longer a special form.
The following code first implements a data structure XS
(which stands for "extensible string") and then implements BINARY
on top of that.
The XS
data structure is similar to a string except that elements can be identifiers or numbers that are greater than a single character provided an appropriate "expander" is defined.
For example,
#define EXPANDER_abc (a b c) #define EXPANDER_xyz (x y z) XS_HEAD(abc xyz) // aCHAOS_PP_CAST
(CHAOS_PP_STRING
, (XS) abc xyz \ ) // (CHAOS_PP_STRING
) a b c x y z
This data structure is extensible in the sense that user-defined "expanders" can be easily written. For example,
#define EXPANDER_Paul (P a u l) #define EXPANDER_Mensonides (M e n s o n i d e s) #define OP(s, x)CHAOS_PP_TO_UPPER
(x)CHAOS_PP_EXPR
(CHAOS_PP_TRANSFORM
( OP, (XS) Paul _ Mensonides )) // (XS) P A U L _ M E N S O N I D E S
Given such a data structure definition (and the appropriate EXPANDER_xxx
definitions), input such as 10101010 10101010
can be processed directly.
The potential downside is that the primitive validation has been lost because the XS
data type is perhaps too extensible for this purpose.
#include<chaos/preprocessor/algorithm/fold_left.h>
#include<chaos/preprocessor/arbitrary/add.h>
#include<chaos/preprocessor/arbitrary/demote.h>
#include<chaos/preprocessor/arbitrary/mul.h>
#include<chaos/preprocessor/cat.h>
#include<chaos/preprocessor/control/iif.h>
#include<chaos/preprocessor/detection/is_nullary.h>
#include<chaos/preprocessor/detection/is_unary.h>
#include<chaos/preprocessor/logical/compl.h>
#include<chaos/preprocessor/recursion/expr.h>
#include<chaos/preprocessor/string/core.h>
#include<chaos/preprocessor/tuple/rem.h>
#define XS XS #define XS_TAG(tag) tag #define XS_NIL()CHAOS_PP_STRING_NIL
() #define XS_CONS(xs, x) x xs #define XS_HEAD(xs)CHAOS_PP_STRING_HEAD
(EXPANDER(xs)) #define XS_TAIL(xs)CHAOS_PP_STRING_TAIL
(EXPANDER(xs)) #define XS_ITEM(x) x #define XS_IS_CONS(xs)CHAOS_PP_COMPL
(XS_IS_NIL(xs)) #define XS_IS_NIL(xs)CHAOS_PP_IS_NULLARY
(xs()) #define EXPANDER(xs) \CHAOS_PP_IIF
( \CHAOS_PP_IS_UNARY
(CHAOS_PP_PRIMITIVE_CAT
(EXPANDER_, xs)) \ )( \CHAOS_PP_TUPLE_REM_CTOR
( \ 1, \CHAOS_PP_PRIMITIVE_CAT
(EXPANDER_, xs) \ ), \ xs \ ) \ /**/ #define BINARY(xs) BINARY_S(CHAOS_PP_STATE
(), xs) #define BINARY_S(s, xs) \CHAOS_PP_ARBITRARY_DEMOTE
( \CHAOS_PP_EXPR_S
(s)(CHAOS_PP_FOLD_LEFT_S
( \ s, ACC, (XS) xs, (0) \ )) \ ) \ /**/ #define ACC(s, bit, x) \CHAOS_PP_ARBITRARY_ADD
( \CHAOS_PP_ARBITRARY_MUL
(x, (2)), (bit) \ ) \ /**/ #define EXPANDER_00000000 (0 0 0 0 0 0 0 0) #define EXPANDER_00000001 (0 0 0 0 0 0 0 1) #define EXPANDER_00000010 (0 0 0 0 0 0 1 0) // ... #define EXPANDER_11111111 (1 1 1 1 1 1 1 1) BINARY(00000101) // 5 BINARY(10001000) // 136 BINARY(11111111) // 255 BINARY(11111111 00000000) // 65280
(The EXPANDER_
boilerplate can be pre-generated with a small program such as the following:
#include <stdio.h> #include <stdlib.h> void expander(int depth) { static char s[9] = { 0 }; if (depth == 8) { printf( "#define EXPANDER_%s (%c %c %c %c %c %c %c %c)\n", s, s[0], s[1], s[2], s[3], s[4], s[5], s[6], s[7] ); } else { s[depth] = '0'; expander(depth + 1); s[depth] = '1'; expander(depth + 1); } return; } int main(void) { expander(0); return EXIT_SUCCESS; }
It isn't included here because it results in 256 macro definitions--which would waste space without providing further illumination.)
Without language support, there is no perfect solution to binary literals. This article provides a few different ways that they can be specified, each with various drawbacks, but no one solution is ideal. Luckily, the purpose of the article isn't to solve that problem completely. Rather, the problem is merely an example that can be used to illustrate preprocessor metaprogramming methodology and to exercise Chaos. Binary literals, though convenient, aren't really all that useful. However, if one knows how to use the tools and techniques available, there is very little that cannot be done.
The astute reader might notice that there is nothing particularly special about binary literals (as opposed to literals of other bases). The runtime model might look something like the following:
#include <ctype.h> #include <stdio.h> #include <stdlib.h> unsigned long helper(char c) { if (isdigit(c)) { return c - '0'; } else switch (tolower(c)) { case 'a': return 10; case 'b': return 11; case 'c': return 12; case 'd': return 13; case 'e': return 14; case 'f': return 15; default: return exit(EXIT_FAILURE), 0; } } unsigned long convert(const char* x, int base) { if (base > 16) exit(EXIT_FAILURE); unsigned long r = 0; while (*x) (r *= base) += helper(*x++); return r; } int main(void) { printf( "%lu\n%lu\n%lu\n%lu\n", convert("ff", 16), convert("123", 10), convert("00000010", 2), convert("00000010", 8) ); return EXIT_SUCCESS; }
The preprocessor version can be extended accordingly.
#include<chaos/preprocessor/algorithm/fold_left_aux.h>
#include<chaos/preprocessor/arbitrary/add.h>
#include<chaos/preprocessor/arbitrary/demote.h>
#include<chaos/preprocessor/arbitrary/literal.h>
#include<chaos/preprocessor/arbitrary/mul.h>
#include<chaos/preprocessor/cat.h>
#include<chaos/preprocessor/recursion/expr.h>
#include<chaos/preprocessor/string/core.h>
#include<chaos/preprocessor/string/to_upper.h>
#define CONVERT(string, base) CONVERT_S(CHAOS_PP_STATE
(), string, base) #define CONVERT_S(s, string, base) \CHAOS_PP_ARBITRARY_DEMOTE
( \CHAOS_PP_EXPR_S
(s)(CHAOS_PP_FOLD_LEFT_AUX_S
( \ s, OP, (CHAOS_PP_STRING
) string, (CHAOS_PP_ARBITRARY_LITERAL
(base)), (0) \ )) \ ) \ /**/ #define OP(s, digit, base, x) \CHAOS_PP_ARBITRARY_ADD
( \CHAOS_PP_ARBITRARY_MUL
(x, base), HELPER(digit) \ ) \ /**/ #define HELPER(digit) \CHAOS_PP_CAT
(HELPER_,CHAOS_PP_TO_UPPER
(digit)) \ /**/ #define HELPER_0 (0) #define HELPER_1 (1) #define HELPER_2 (2) #define HELPER_3 (3) #define HELPER_4 (4) #define HELPER_5 (5) #define HELPER_6 (6) #define HELPER_7 (7) #define HELPER_8 (8) #define HELPER_9 (9) #define HELPER_A (1)(0) #define HELPER_B (1)(1) #define HELPER_C (1)(2) #define HELPER_D (1)(3) #define HELPER_E (1)(4) #define HELPER_F (1)(5) CONVERT(f f, 1 6) // 255 CONVERT(1 2 3, 1 0) // 123 CONVERT(0 0 0 0 0 0 1 0, 2) // 2 CONVERT(0 0 0 0 0 0 1 0, 8) // 8


Previous: The External Environment, Up: Environment
| • decode-universal-time: | ||
| • encode-universal-time: | ||
| • get-universal-time: | ||
| • sleep: | ||
| • apropos: | ||
| • describe: | ||
| • describe-object: | ||
| • trace: | ||
| • step: | ||
| • time: | ||
| • internal-time-units-per-second: | ||
| • get-internal-real-time: | ||
| • get-internal-run-time: | ||
| • disassemble: | ||
| • documentation: | ||
| • room: | ||
| • ed: | ||
| • inspect: | ||
| • dribble: | ||
| • -: | ||
| • +: | ||
| • *: | ||
| • /: | ||
| • lisp-implementation-type: | ||
| • short-site-name: | ||
| • machine-instance: | ||
| • machine-type: | ||
| • machine-version: | ||
| • software-type: | ||
| • user-homedir-pathname: |


Experiment,Experience & Expert. Ketika kita menjadi pemakai satu barang jadi, saat itulah kita melewatkan satu proses kreasi,makin banyak makin lupa
Cliffs of Moher, by Alessandro Farese (by-nc-nd)
Don’t be afraid to try, the failure will not kill you
The Best Teacher is Experience
Success does not come with the hard work by lazed


Hi! I'm Cedar and this is my Node.js application. It has an about page (where you are now), a navigation page, a page with four dog breeds and their pictures, a page with four cat breeds and their pictures, and a page for today's work playlist, which is the playlist I was listening to while working on this. Right now the playlist is just a list of songs I was listening to with each artists that wrote the song, but maybe in the future they'll include links to the actual songs or the songs embedded in the page.
I'm 24, I like dogs and cats a lot, I love pretty much all kinds of music, I REALLY like coffee, and I spent so much time on the CSS for this page because I hate Bootstrap because I am a control freak but I'm not great at CSS. I love programming, but man, CSS is just not my thing.


Player 1
Fold
Check/Call
Bet
Player 2
Fold
Check/Call
Bet
Player 3
Fold
Check/Call
Bet
Player 4
Fold
Check/Call
Bet
this is where the messages go


orienteering
Tenzing Orienteering works from the inside out to help stakeholders discover a mutually achievable path to brand delivery. It's like a series of revival meetings for staff, leadership and influencers. The conversations are grounded in research, confidential if required, often blunt, and always engaging. We inspire brand ownership and then guide the human effort required to go to market as one. Tenzing Orienteering is to facilitation what Jackson Pollock is to paint-by-numbers.
Tenzing's Orienteering process has been applied to public organizations like The City of Mississauga and Bruce County, healthcare organizations including Hamilton Health Sciences and The Canadian Mental Health Association, and in the private sector with companies such as Baker and McKenzie LLP, CGA Canada and SNC Lavalin. Orienteering is the first step in mobilizing your human channel.


--- layout: page status: publish published: true title: Bioscience Overview author: display_name: Jessie Pechmann login: jpechmann email<EMAIL_ADDRESS>url: '' author_login: jpechmann author_email<EMAIL_ADDRESS>wordpress_id: 2773 wordpress_url: http://gis.utah.gov/?page_id=2773 date: '2011-10-19 15:24:03 -0600' date_gmt: '2011-10-19 21:24:03 -0600' categories: [] tags: - SDE - sgid - Data - utah - gis - map - mapping - dataset - download - agrc - layer - shapefile - geodatabase - metadata - shp - gdb - kml - lyr - digital - geographic - information - database - state - statewide - vector - overview - category - services - daas - arcgis - fire - bioscience - habitat - wildfire - GAP landcover - vegetation ---
| Product Name | Type | Steward(s) | Description | |
|---|---|---|---|---|
| click a product name for more information and download links | ||||
| Beaver Restoration Assessment | map data | US Fish and Wildlife Service | The Utah statewide Beaver Restoration Assessment Tool (BRAT) is a decision support and planning tool for beaver management. The backbone to BRAT is a capacity model developed to assess the upper limits of riverscapes to support beaver dam-building activities. Both existing and potential capacity were estimated with readily available spatial datasets to evaluate five key lines of evidence: 1) a perennial water source, 2) availability of dam building materials, 3) ability to build a dam at baseflow, 4) likelihood of dams to withstand a typical flood, and 5) likelihood that stream gradient would limit or completely eliminate dam building by beaver. Fuzzy inference systems were used to combine these lines of evidence while accounting for uncertainty. | |
| Dominant Vegetation | map data | Utah Division of Wildlife Resources (DWR) | Statewide distribution of dominant vegetation species in Utah. The data were derived from 1:24,000 scale orthophoto quadrangles, 1:40,000 scale aerial photos and field mapping by the Utah Division of Wildlife Resources (approximate date Jan. 2001) | |
| GAP Landcover Classification (Raster) | map data and map services | USGS GAP Analysis Program, USU RS/GIS Lab | Landcover classification for the State of Utah for the purposes of regional terrestrial biodiversity assessment. Download data files Use WMS web map service |
|
| DWR Habitat Areas | map data | DNR, Utah Division of Wildlife Resources (DWR) | Habitat areas for game species of Utah and generalized occurrence data for habitat areas of protected species. | |
| Wildfire Perimeters | map data | AGRC, SITLA, DNR, Utah Div. Emergency Management | Perimeters of wildfires in Utah. |


Hold Shift and click to exclude items from infusion calculations.
No infusable items available.Select items to infuse:
+
Will bring the gear to{{infuse.infused}}(+ {{infuse.difference}})using {{infuse.targets.length*3}} + {{infuse.targets.length}} + {{infuse.targets.length*250 | number}} + {{infuse.targets.length*10 | number}}
This calculator uses the best known algorithm for infusing. If you find any discrepancies let us know. DIM can't actually perform infusions, it can just tell you what you'll get.


Choosing a Data Distribution Style
Topics
When you load data into a table, Amazon Redshift distributes the rows of the table to each of the compute nodes according to the table's distribution style. When you run a query, the query optimizer redistributes the rows to the compute nodes as needed to perform any joins and aggregations. The goal in selecting a table distribution style is to minimize the impact of the redistribution step by locating the data where it needs to be before the query is executed.
This section will introduce you to the principles of data distribution in an Amazon Redshift database and give you a methodology to choose the best distribution style for each of your tables.
Data Distribution Concepts
Nodes and slices
An Amazon Redshift cluster is a set of nodes. Each node in the cluster has its own operating system, dedicated memory, and dedicated disk storage. One node is the leader node, which manages the distribution of data and query processing tasks to the compute nodes.
The disk storage for a compute node is divided into a number of slices. The number of slices per node depends on the node size of the cluster. For example, each DS1.XL compute node has two slices, and each DS1.8XL compute node has 16 slices. The nodes all participate in parallel query execution, working on data that is distributed as evenly as possible across the slices. For more information about the number of slices that each node size has, go to About Clusters and Nodes in the Amazon Redshift Cluster Management Guide.
Data redistribution
When you load data into a table, Amazon Redshift distributes the rows of the table to each of the node slices according to the table's distribution style. As part of a query plan, the optimizer determines where blocks of data need to be located to best execute the query. The data is then physically moved, or redistributed, during execution. Redistribution might involve either sending specific rows to nodes for joining or broadcasting an entire table to all of the nodes.
Data redistribution can account for a substantial portion of the cost of a query plan, and the network traffic it generates can affect other database operations and slow overall system performance. To the extent that you anticipate where best to locate data initially, you can minimize the impact of data redistribution.
Data distribution goals
When you load data into a table, Amazon Redshift distributes the table's rows to the compute nodes and slices according to the distribution style that you chose when you created the table. Data distribution has two primary goals:
-
To distribute the workload uniformly among the nodes in the cluster. Uneven distribution, or data distribution skew, forces some nodes to do more work than others, which impairs query performance.
-
To minimize data movement during query execution. If the rows that participate in joins or aggregates are already collocated on the nodes with their joining rows in other tables, the optimizer does not need to redistribute as much data during query execution.
The distribution strategy that you choose for your database has important consequences for query performance, storage requirements, data loading, and maintenance. By choosing the best distribution style for each table, you can balance your data distribution and significantly improve overall system performance.


As your codebase grows, it’s important to refactor your code frequently to keep it readable and maintainable over time. Add comments and refactor your app.js
to improve the code quality:
sendRequest()
function to regroup the code used in both createAccount()
and getAccount()
| Criteria | Exemplary | Adequate | Needs Improvement |
|---|---|---|---|
Code is commented, well-organized in different sections and easy to read. Constants are extracted and a factorized sendRequest() function has been created. |
Code is clean but can still be improved with more comments, constant extraction or factorization. | Code is messy, not commented, constants are not extracted and code is not factorized. |


--- title: NHS Hammersmith and Fulham layout: gb ---
| Resource | Fetch | Format | Columns | Data | Valid | Entries | Oldest | Latest | Total (GBP) | |
|---|---|---|---|---|---|---|---|---|---|---|
| Spend over £25,000 in NHS Hammersmith and Fulham | ||||||||||
| 2010 July return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 April return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 November return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 August return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 May return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 October return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 June return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 | ||||
| 2010 September return | ✘ | ✘ | ✘ | ✘ | ✘ | 0 |
| Resource/Stage | Error |


Welcome to Cajun Navy Management application. To get started use one of the links on the left. This application was created using the Angular and Bootstrap frameworks.
This application runs natively on the Openshift Container Platform as a Node.js application


Skyle_SkyleProvider
public protocol Skyle_SkyleProvider : CallHandlerProvider
To build a server, implement a class that conforms to this protocol.
-
Used to calibrate for the current user. Streams in both directions with given message types. Client needs to close the stream when done
Declaration
Swift
func calibrate(context: StreamingResponseCallContext<Skyle_CalibMessages>) -> EventLoopFuture<(StreamEvent<Skyle_calibControlMessages>) -> Void>
-
Subscribe a stream sending eye positions and quality indicators to achieve good positioning of a user. Client needs to close the stream when done
Declaration
Swift
func positioning(request: SwiftProtobuf.Google_Protobuf_Empty, context: StreamingResponseCallContext<Skyle_PositioningMessage>) -> EventLoopFuture<GRPCStatus>
-
Subscribe a gaze stream, that sends coordinates of the current user gaze on a screen. Client needs to close the stream when done
Declaration
Swift
func gaze(request: SwiftProtobuf.Google_Protobuf_Empty, context: StreamingResponseCallContext<Skyle_Point>) -> EventLoopFuture<GRPCStatus>
-
Unary call to get the button status
Declaration
Swift
func getButton(request: SwiftProtobuf.Google_Protobuf_Empty, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_Button>
-
Unary call to configure the button actions, answers with the resulting configuration
Declaration
Swift
func setButton(request: Skyle_ButtonActions, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_ButtonActions>
-
Unary call to get (OptionMessage -> empty) or set options (OptionMessage -> Options). Answers with the resulting options. Options are saved to the current user profile
Declaration
Swift
func configure(request: Skyle_OptionMessage, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_Options>
-
Unary call to get software versions
Declaration
Swift
func getVersions(request: SwiftProtobuf.Google_Protobuf_Empty, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_DeviceVersions>
-
Subscribe a profile stream of all available profiles. Host ends stream when all results are sent
Declaration
Swift
func getProfiles(request: SwiftProtobuf.Google_Protobuf_Empty, context: StreamingResponseCallContext<Skyle_Profile>) -> EventLoopFuture<GRPCStatus>
-
Unary call to get the current profile
Declaration
Swift
func currentProfile(request: SwiftProtobuf.Google_Protobuf_Empty, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_Profile>
-
Unary call to set or create a profile. Answers with a status message (success or failure)
Declaration
Swift
func setProfile(request: Skyle_Profile, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_StatusMessage>
-
Unary call to delete a profile. Answers with a status message (success or failure)
Declaration
Swift
func deleteProfile(request: Skyle_Profile, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_StatusMessage>
-
Unary call to reset specific parts
Declaration
Swift
func reset(request: Skyle_ResetMessage, context: StatusOnlyCallContext) -> EventLoopFuture<Skyle_StatusMessage>
-
serviceName
Extension methodDeclaration
Swift
public var serviceName: String { get }
-
handleMethod(_:
Extension methodcallHandlerContext: ) Determines, calls and returns the appropriate request handler, depending on the request’s method. Returns nil for methods not handled by this service.
Declaration
Swift
public func handleMethod(_ methodName: String, callHandlerContext: CallHandlerContext) -> GRPCCallHandler?


Social Impact Partners Fund (SIPF) believes:
Young women and men can deliver world-changing innovation...when their creativity is multiplied within a global, collaborative network of peers and professional mentors.
Get Started!Many notable tech innovations were first conceived by pioneering teenagers—proof that properly trained youth can change the world.
We believe more underrepresented women and minorities around the world can join this cohort of young innovation leaders with proper investment in innovation leadership development and access to a network of like-minded professionals.
Find Out MoreThe world’s finest, globally diverse early talent pipeline
Global, high ROI brand goodwill
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A globally representative network of young professionals who advance the state of the art in providing innovative solutions to problems throughout all sectors of the global economy, to the benefit of all people groups.
To train historically underrepresented women and men for innovative approaches to solving complex problems in the globally matrixed economy, as leaders of the world’s top institutions and as entrepreneurs, and to maximize the social impact of innovation in every region of the world.
SIPF invests in long-term human capital, with a focus on young women and underserved minorities, for the benefit of both humanity and our corporate partners’ brand equity.
Our "output" is an elite, globally diverse cohort of women and men superbly trained in innovation leadership development, skills universally prized across national borders and industries, which leads to enhanced brand goodwill for our Partners.
This skillset and newly developed cultural capital will prepare our alums to be leading university students, coveted job prospects, innovative entrepreneurs, and leaders across all aspects of their respective national societies.


Spiderman
Spiderman Flow
Games
(current)
Stories
Versions
Origin
Peter Parker
Miles Morales
Gwen Stacy
Music
A Spiderman Song
Click Picture to listen to Song.


Tuesday, December 9, 2014
Monday, December 9, 2014
Friday, December 5, 2014
Saturday, December 6, 2014


--- layout: page title: Bootstrap Resources description: "A comprehensive list of Bootstrap 3 and related resources maintained by Start Bootstrap." meta-title: "Bootstrap Resources and Plugins List" meta-description: "Bootstrap resources page meta description goes here." ---
| Name | Description | Link |
|---|---|---|
| Bootstrap CDN | The recommended CDN for Bootstrap, Font Awesome, and Bootswatch. | View Resource |
| Bootsnipp | A large library of free code snippets and design elements for Bootstrap. | View Resource |
| Bootstrap Accessibility Plugin | Accessibility Plugin for Bootstrap 3 and Bootstrap 3 as SubModule. | View Resource |
| Jetstrap | Not just a mock-up tool, Jetstrap is the premier interface-building tool for Bootstrap 3. | View Resource |
| Roots.io Sage | A Bootstrap driven WordPress starter theme with a modern front-end development workflow. | View Resource |
| Understrap | UnderStrap combines the Underscores starter theme (by Automattic) and the mobil-first, responsive grid framework Bootstrap (by Twitter) into a perfect open source foundation for your next WordPress theme project. | View Resource |
| TwitterBootstrapMVC | Development for ASP.NET MVC with Bootstrap made simple. | View Resource |
| Bootply | A Bootstrap code editor and builder - the Bootstrap playground. | View Resource |
| Bootlint This Page | A Chrome extension to inject the Bootlint tool into a web page and automatically scan it for common Bootstrap related errors. | View Resource |
| UI Bootstrap | Bootstrap components written in pure AngularJS by the AngularUI team. | View Resource |
| Kickstrap | Kickstrap is a boilerplate of Bootstrap, JSPM, Angular.js and Roots that can copy itself into any directory you choose. | View Resource |
| Bootstrap 3 for IE7 | Bootstrap 3 drops support for Internet Explorer 7, but you can add it back by simply adding this conditional CSS. | View Resource |
| Tablestrap | A Bootstrap table generator. | View Resource |
| BootstrapDocs | A Bootstrap documentation archive. | View Resource |
| BootSwatchr | A theme roller for Bootstrap 3. | View Resource |
| UMyProto | A visual, online Bootstrap site builder. | View Resource |
| Paintstrap | Generate beautiful Bootstrap themes using the Adobe Kuler and COLOURlovers color scheme. | View Resource |
| Lavish | Generate your own Bootstrap color scheme from an image and customize to your taste. | View Resource |
| 1pxdeep | Flat(ish) Bootstrap 3 theme generator. | View Resource |
| Hexagon | A CSS hexagon generator for Bootstrap 3. | View Resource |
| Bootdey | A gallery of free snippets and resources for Bootstrap. | View Resource |
| BThemer | A Bootstrap theme customizer with live previews. | View Resource |
| Bootpress Themeroller | A custom theme generator for Bootstrap. | View Resource |


Tiverton still a gold town after South West in Bloom award
The town won the South West in Bloom gold award for the second consecutive year
by Lewis ClarkeTiverton has once again proven to be bloomin’ beautiful.
The town won the South West in Bloom gold award for the second consecutive year.
The aim for communities that take part each year is to improve and regenerate local environments, through the imaginative planting of trees, shrubs, flowers and landscaping, conservation and recycling projects, and to sweep away the eyesores that blight streets, such as litter, graffiti and vandalism.
The results were announced to people in Tiverton at an In Bloom presentation evening.
Councillor Wally Burke who is chairman of the Tiverton in Bloom committee on Tiverton Town Council said: “We are very pleased with the result we had this year. We have retained our gold, and it shows that we’re heading upwards and in the right direction.
“Last year there was a bit of a hiccup, and they had to re-judge us when we won gold. This time we have easily retained gold, and the results of that encourage our townspeople to enter the local competition which we ran for them. It doesn’t cost them anything; it’s all free, and we had a delightful presentation night.
“The standard this year was excellent. There are a lot of people with beautiful gardens in the town, but they don’t pick up an entry form and get involved. I hope we’ll be able to encourage a lot more to enter than what we had this year.”


These are the primitives to define effect handlers and yield operations. More...
Data Structures | |
| struct | lh_optag_ |
| Operation values. More... | |
| struct | lh_operation |
| Opereation defintion. More... | |
| struct | lh_handlerdef |
| Handler definition. More... | |
| struct | yieldargs |
| Structure to pass multiple arguments from a yield. More... | |
Macros | |
| #define | lh_value_cstack_ptr(p) |
| Convert a C stack pointer to an lh_value. | |
| #define | lh_cstack_ptr_value(r, v) |
| Convert an lh_value back to an adjusted C stack pointer. More... | |
| #define | lh_value_yieldargs(y) |
| Convert a yieldargs structure to a generic value. | |
| #define | lh_yieldargs_value(r, v) |
| Convert an lh_value back to a yieldargs structure. | |
| #define | lh_effect_null |
| Null effect. | |
| #define | lh_op_null |
| The null operation tag is used for the final operation struct in a list of operations. | |
Typedefs | |
| typedef struct _lh_resume * | lh_resume |
| A "resume" continuation. More... | |
| typedef const char *const * | lh_effect |
| Effect values. More... | |
| typedef const struct lh_optag_ * | lh_optag |
| Operation values. More... | |
| typedef lh_value() | lh_opfun(lh_resume r, lh_value local, lh_value arg) |
Operation functions are called when that operation is yield ed to. | |
Enumerations | |
| enum | lh_opkind { LH_OP_NULL, LH_OP_FORWARD, LH_OP_NORESUMEX, LH_OP_NORESUME, LH_OP_TAIL_NOOP, LH_OP_TAIL, LH_OP_SCOPED, LH_OP_GENERAL } |
| Operation kinds. More... | |
Functions | |
| lh_value | lh_handle (const lh_handlerdef *def, lh_value local, lh_actionfun *body, lh_value arg) |
| Handle a particalur effect. More... | |
| lh_value | lh_yield (lh_optag optag, lh_value arg) |
| Yield an operation to the nearest enclosing handler. | |
| lh_value | lh_yield_local (lh_optag optag) |
lh_yield_local yields to the first enclosing handler for operation optag and returns its local state. More... | |
| lh_value | lh_scoped_resume (lh_resume r, lh_value local, lh_value res) |
| Resume a continuation. More... | |
| lh_value | lh_tail_resume (lh_resume r, lh_value local, lh_value res) |
| Final resumption of a scoped continuation. More... | |
| void | lh_release (lh_resume r) |
| Explicitly release a first-class continuation without resuming. | |
| lh_value | lh_call_resume (lh_resume r, lh_value local, lh_value res) |
| Resume a first-class contiunation with a specified result. | |
| lh_value | lh_release_resume (lh_resume r, lh_value local, lh_value res) |
| Resume a first-class contiunation with a specified result. More... | |
| void * | lh_cstack_ptr (lh_resume r, void *p) |
| Adjust a C stack pointer. More... | |
| lh_value | lh_yieldN (lh_optag optag, int argcount,...) |
| Yield with multiple arguments. More... | |
| const char * | lh_optag_name (lh_optag optag) |
| Get the name of an operation tag. | |
| const char * | lh_effect_name (lh_effect effect) |
| Get the name of an effect tag. | |
These are the primitives to define effect handlers and yield operations.
| struct lh_optag_ |
Operation values.
An operation is identified by an effect and index in that effect. There are defined automatically using LH_DEFINE_OPn
macros and can be referred to using LH_OPTAG(effect,opname)
.
| Data Fields | ||
|---|---|---|
| lh_effect | effect | |
| long | opidx |
| struct lh_operation |
Opereation defintion.
An operation
has a kind, an identifying tag, and an associated operation function.
| Data Fields | ||
|---|---|---|
| lh_opfun * | opfun |
The operation function; use NULL (with LH_OP_FORWARD) to have the operation forwarded to the next enclosing effect (i.e. a direct tail-resume with the same arguments). |
| lh_opkind | opkind | Kind of the operation. |
| lh_optag | optag | The identifying tag. |
| struct lh_handlerdef |
Handler definition.
| Data Fields | ||
|---|---|---|
| lh_effect | effect | The Effect being handled. |
| lh_acquirefun * | local_acquire | Called when the local state needs to be acquired. Can be NULL. |
| lh_releasefun * | local_release | Called when the local state is released. Can be NULL. |
| const lh_operation * | operations |
Definitions of all handled operations ending with an operation with lh_opkind LH_OP_NULL . Can be NULL to handle no operations; Note: all operations must be in the same order here as in the effect definition! (since each operation has a fixed index). |
| lh_resultfun * | resultfun | Invoked when the handled action is done; can be NULL in which case the action result is passed unchanged. |
| struct yieldargs |
Structure to pass multiple arguments from a yield.
| Data Fields | ||
|---|---|---|
| int | argcount | guaranteed to be >= 0 |
| lh_value | args[1] |
allocated to contain argcount arguments |
| #define lh_cstack_ptr_value | ( | r, | |
| v | |||
| ) |
Convert an lh_value back to an adjusted C stack pointer.
The pointer is adjusted to now pointing into the heap allocated resumption. This can be used inside operation handlers but use with care.
| typedef const char* const* lh_effect |
Effect values.
Operations are identified by a constant string pointer. They are compared by address though so they must be declared as static constants (using #LH_NEWOPTAG)
Operation values.
An operation is identified by an effect and index in that effect. There are defined automatically using LH_DEFINE_OPn
macros and can be referred to using LH_OPTAG(effect,opname)
.
| typedef struct _lh_resume* lh_resume |
A "resume" continuation.
This is first-class, and can be stored in data structures etc, and can survive the scope of an operation function. It can be resumed through lh_resume() or lh_release_resume().
| enum lh_opkind |
Operation kinds.
When defining the operations that a handler can handle, these are specified to make the handling of operations more efficient. If you are not sure, LH_OP_GENERAL is always safe to use :-) At this point LH_OP_TAIL and LH_OP_NORESUME are most efficient since they do not need to set up a jump point.
| void* lh_cstack_ptr | ( | lh_resume | r, |
| void * | p | ||
| ) |
Adjust a C stack pointer.
Inside an operation handler, adjust a pointer that was pointing to the C stack at capture time to point inside the now captured stack. This can be used to pass values by stack reference to operation handlers. Use with care.
| lh_value lh_handle | ( | const lh_handlerdef * | def, |
| lh_value | local, | ||
| lh_actionfun * | body, | ||
| lh_value | arg | ||
| ) |
Handle a particalur effect.
Handles operations yielded in body(arg)
with the given handler definition def
.
Resume a first-class contiunation with a specified result.
Also releases the continuation and it cannot be resumed again!
Resume a continuation.
Use this when not resuming in a tail position.
Final resumption of a scoped continuation.
Only call lh_tail_resume
as the last action of an operation function, i.e. it must occur in tail position of an operation function.
lh_yield_local
yields to the first enclosing handler for operation optag
and returns its local state.
This should be used with care as it violates the encapsulation principle but works well for implicit parameters and to reduce the number of explicit operations for many effects. Note, still forwards through effect handlers that use an lh_opfun
of NULL
, and, more precisely, returns the state for the innermost enclosing handler that does not have a NULL
operation.


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