Collaboration 3.0
I recently took part in an online panel on collaboration, organized by Alex Schiff, founder of Fetchnotes. Was a fun experience, getting out my own thoughts and hearing from people in other companies like Asana, Yammer, Quip, Wunderlist, Any.do, Do, etc say on the topic. Full post is below, just click on the image.
My original response was too long for the panel, so thought I’d paste it here. Some of the points I’ve brought up before in different posts, but here it is in its entirety.
When I think about collaboration tools, there are 3 things that really come to mind - mobile, distributed working, and the internet of things.
Mobile
When talking about short term trends in collaboration, mobile is top of mind. It’s not so much an upcoming trend, but something that is already happening. I recently wrote a post, Mobile First in the Enterprise, that talks about this. As traditional desktop software went online, we got a taste of working outside of the office. Now with mobile, we’re pushing that even further and we’re demanding high quality tools so we can do our jobs anywhere & anytime.
Mobile is a unique form factor in that screen real estate is small, there are built in sensors not available via a browser, and simplicity/single function are dominant. Collaboration reimagined from a mobile first perspective will yield very different tools and experiences than we’re familiar with. Prescient companies are taking this very seriously, and a quick look at popular collaboration tools all treat high quality stand alone mobile apps as a base requirement.
Distributed Working
A related point is distributed working. As mentioned above, modern tools allow us to do quality work outside of the office. We’re pushing this further than we have before with distributed or remote working. As commonly said, there is more talent outside of your locale than in it. And although companies have been adopting this mentality, the tools for distributed working still feel second rate. Lots of these tools help remote teams contribute and communicate, but they feel like individualized solutions under a bigger problem.
Better ways of sharing knowledge, documents, code, etc are certainly important, but another aspect that has been largely ignored is the culture and team building around remote workers. The available tools don’t facilitate and capture the same effect as in person work - the camaraderie, teamwork, excitement, visibility, and other culture building things. These are still largely solved from in person visits and spending time with each other. I’m looking forward to tools and solutions that are built for distributed teams first, and not tools to just help remote teams better contribute to those working in person.
Connected Devices
The last trend that I think is really important is the Internet of Things. I’m a bit a averse to that phrase as it’s been a bit overused, but I am genuinely excited for the notion of ‘devices talking to devices’. While software has greatly improved in general, what has not dramatically improved is how we interact with software - input has and continues to be manual. We still have to manually type details into Salesforce, type your receipts into a system to create expense reports, etc.
With the advent of smartphones coupled with the declining cost of sensors, we’re getting a taste of what life is like with sensors embedded everywhere, capturing and inputting data in for us. A small example of this is something I noticed in Taiwan - inbound buses auto send notifications about arrival time to those in the proximity of the bus stop. That’s a small example of what can be done when devices talk to other devices, and if we think about this and apply it in a workplace setting, amazing solutions can then be created – ie auto logging details of a call into Salesforce, context sensitive time tracking tools, automatically creating/prioritizing/closing tasks on a todo list, and lots of other things that I haven’t even thought of.
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Protected Member Functions | |
| virtual void | writerEditorAttributes (HtmlTextWriter writer, string ctlType) |
| override void | writeColumnInnerContents (HtmlTextWriter writer, string ctlType, bool isLiveData) |
Protected Attributes | |
| string | m_dataSourceId = null |
| string | m_dataSource = null |
| string | m_displayFields = null |
| string | m_valueField = null |
| string | m_getHandler = null |
| List< Column > | m_columns = new List<Column>() |
Properties | |
| List< Column > | Columns [get] |
| KeyColumn | KeyColumns [get] |
| string | GetDataUrl [get, set] |
| The URL of the data handler to make the Ajax get data request call to obtain the data needed by the control. You mus talso specify the DataSourceid for the Ajax call to function properly. | |
| string | DataSourceId [get, set] |
| The id to pass when requesting the data using the Ajax get data request. You must also specify the GetDataUrl property for the Ajax call to function properly. | |
| string | LocalData [get, set] |
| A specially formatted string in the JSON format that contains all of the data needed by the child columns. | |
| string | ValueField [get, set] |
| defines which field from the child row data to use for the value of the main row data being edited. | |
| string | ColumnNames [get] |
| abstract string | EditorName [get] |
Used only by the Grid control, ColumnListColumn type classes can have their own list of columns specified within their inner body, which this class maintains.
All child classes of this class need a data source for rows of data that it uses. Data can be provided to the column by either using the DataSourceId property (which will cause an Ajax Get data request to happen to get the actual data) or the LocalData property which is a specially formated string containing all of the data for small datasets. /remarks>
| virtual void Nitobi.ColumnListColumn.writerEditorAttributes | ( | HtmlTextWriter | writer, | |
| string | ctlType | |||
| ) | [protected, virtual] |
Reimplemented in Nitobi.CheckboxColumn.
| override void Nitobi.ColumnListColumn.writeColumnInnerContents | ( | HtmlTextWriter | writer, | |
| string | ctlType, | |||
| bool | isLiveData | |||
| ) | [protected, virtual] |
string Nitobi.ColumnListColumn.m_dataSourceId = null [protected] |
string Nitobi.ColumnListColumn.m_dataSource = null [protected] |
string Nitobi.ColumnListColumn.m_displayFields = null [protected] |
string Nitobi.ColumnListColumn.m_valueField = null [protected] |
string Nitobi.ColumnListColumn.m_getHandler = null [protected] |
List<Column> Nitobi.ColumnListColumn.m_columns = new List<Column>() [protected] |
List<Column> Nitobi.ColumnListColumn.Columns [get] |
Implements Nitobi.IColumnCollection.
KeyColumn Nitobi.ColumnListColumn.KeyColumns [get] |
Implements Nitobi.IColumnCollection.
string Nitobi.ColumnListColumn.GetDataUrl [get, set] |
The URL of the data handler to make the Ajax get data request call to obtain the data needed by the control. You mus talso specify the DataSourceid for the Ajax call to function properly.
string Nitobi.ColumnListColumn.DataSourceId [get, set] |
The id to pass when requesting the data using the Ajax get data request. You must also specify the GetDataUrl property for the Ajax call to function properly.
Implements Nitobi.IColumnCollection.
string Nitobi.ColumnListColumn.LocalData [get, set] |
A specially formatted string in the JSON format that contains all of the data needed by the child columns.
This is very useful for small data sets to avoid excessing Ajax calls after the grid control is initialized during a page load. The following examples show of the format expected for this property:
[{value:'True',display:''},{value:'False',display:''}]
[{firstName:'John', lastName:'Adams'},{firstName:'Matthew', lastName: 'Smith'}]
string Nitobi.ColumnListColumn.ValueField [get, set] |
defines which field from the child row data to use for the value of the main row data being edited.
string Nitobi.ColumnListColumn.ColumnNames [get] |
Implements Nitobi.IColumnCollection.
abstract string Nitobi.ColumnListColumn.EditorName [get, protected] |
Reimplemented in Nitobi.ComboColumn, and Nitobi.CheckboxColumn.


Waste storage at Africa's only nuclear plant brimming
CAPE TOWN: Spent fuel storage at South Africa's Koeberg nuclear plant will reach full capacity by April as state power utility Eskom awaits regulatory approval for new dry storage casks, the company said on Monday (Nov 25).
Storage of high-level radioactive waste is a major environmental concern in the region, as South Africa looks to extend Koeberg's life for another two decades and mulls extra nuclear power plants.
Koeberg, Africa's only nuclear facility, is situated about 35km from Cape Town and was connected to the grid in the 1980s under apartheid.
"The Koeberg spent fuel pool storage capacity is currently over 90 per cent full. (These) pools will reach (their) capacity by April 2020," Eskom told Reuters in a statement.
Koeberg produces about 32 tonnes of spent fuel a year. Fuel assemblies, which contain radioactive materials including uranium and plutonium that can remain dangerous for thousands of years, are cooled for a decade under water in spent fuel pools.
Three years ago Eskom paid an estimated 200 million rand (US$13.60 million) for an initial batch of seven reinforced dry storage casks from US energy company Holtec International to help keep Koeberg running beyond 2018.
Eskom now has nine new unused casks on site, each with an individual capacity of 32 spent fuel assemblies, with another five expected to be delivered soon.
"These casks are presently stored empty on the Koeberg site while Eskom is in the process of applying for a usage licence from the National Nuclear Regulator (NNR)," Eskom said.
The 14 casks should ensure there is sufficient storage in the spent fuel pool until 2024, Eskom said, ahead of a tender for an extra 30 casks.
The NNR said Eskom only had permission to store four dry casks at Koeberg and that the power utility had applied for a licence change request justifying the use of 14 additional dry storage casks.
"Eskom indicated that the safety case will be submitted to the NNR in 2020," said regulator spokesman Gino Moonsamy.
Anti-nuclear lobby group Earthlife Africa said South Africa could not afford the social, environmental and economic costs associated with nuclear waste.
"We have a ticking bomb with high-level waste and fuel rods at Koeberg," said Makoma Lekalakala, Earthlife Africa's director.


SPHERE
USA. 1998. Director - Barry Levinson, Screenplay - Paul Attanasio & Stephen Hauser, Adaption - Kurt Wimmer, Based on the Novel by Michael Crichton, Producers - Crichton, Levinson & Andrew Wald, Photography - Adam Greenberg, Music - Elliot Goldenthal, Visual Effects - Cinesite (Supervisor - Carlos Aguello), Visual Effects Miniatures - Grant McCune Design (Supervisor - Grant McCune), End Sequence - Sony Pictures Imageworks (Supervisor - Walt Hyneman), Special Effects Supervisor - Ken Pepiot, Prosthetic/Animatronic Effects - Steve Johnson's XFX Inc (Supervisor - Sean Taylor), Production Design - Norman Reynolds. Production Company - Baltimore Pictures/Constant c Productions/Punch Productions. Dustin Hoffman (Dr Norman Goodman), Sharon Stone (Dr Beth Halperin), Samuel L. Jackson (Harry Adams), Peter Coyote (Barnes), Liev Schreiber (Dr Ted Fielding)
Plot: A team of scientists are brought to the middle of the Pacific where they are informed they have been selected as first contact specialists to investigate a crashed UFO that has been discovered on the ocean floor. Entering the craft they discover it is really a ship from Earth's future that has been thrown back in time through a black hole. At the heart of the ship is a mysterious sphere. After one of the team recklessly enters the sphere, they find themselves in contact with an alien entity and their habitat under attack by jellyfish and giant squids which appear to have been manifested from out of their worst fears.
Nobody, with the exception of John Travolta, has quite made a career comeback in recent years like Michael Crichton has. In the 1970s Crichton had big hits with the film adaption of his novel `The Andromeda Strain' in 1971 and further successes as a director with the likes of `Westworld' (1973), `Coma' (1978) and `The Great Train Robbery' (1979). But after that point Crichton's star began to wane - the film adaption of his best-selling novel `The Terminal Man' in 1974 was barely seen, and his other directorial efforts - `Looker' (1981), `Runaway' (1984) and `Physical Evidence' (1989) - were ignored by all and sundry. Crichton's appeal was always founded in the post-`2001' view of the future as a soullessly sterile, antisceptic world where we have come to be crowded out by our technology or where our technology is in imminent danger of going out of control. But after `Star Wars' in 1977 the vision of a cold, sterile future was suddenly replaced by a gee-whiz enthusiasm for all things wondrous and Crichton's technological alarmism became outmoded.
In `The Encyclopedia of Science Fiction' (1992), Peter Nicholls accuses Crichton's novels of reading like potential film scripts. Nicholls' slightly cynical tone notwithstanding, there is some truth to the comment in that both Crichton's novels of `Sphere' (1987) and `Jurassic Park' (1990) were originally designed as film scripts. It is a measure of just how far Crichton was out of grace at the time in that none of these attracted any attention. Crichton also had the further ignominy of seeing a substantial part of `Sphere' stolen by James Cameron in `The Abyss' (1989).
`Jurassic Park' was however a best-seller and attracted the eyes of Steven Spielberg and the rest, as they say, is history. Crichton's middle name has suddenly become "author of `Jurassic Park'" and he has found himself in the midst of a major career revival even bigger than the success he had had in the 1970s. Although Crichton has yet to reoccupy the director's chair, there have been major film adaptions of all his books - `Rising Sun' (1993), `Disclosure' (1994), `Congo' (1995), `The Lost World: Jurassic Park' (1997) - and he has provided the original screenplays for `Twister' (1996) and created the hit tv series `ER' (1994- ). The `Jurassic Park' credit alone has been enough to propel him from has-been film-maker to one of the most cinematically popular contemporary novelists, rivalled possibly only by John Grisham. (As of this writing with `The Thirteenth Warrior', adapted from Crichton's `Eaters of the Dead' (1976), awaiting release later this year that makes only one Crichton novel - `Airframe' - that has not been filmed and that is being planned for next year).
Certainly `Sphere' is probably Crichton's weakest book. In it Crichton seemed undecided whether he was telling an alien contact story or a monsters from the id drama, and the ending where the protagonists simply wished the problem away was so absurd I threw the book across the room. Crichton's novels are fine for the scientific extrapolation and the depth of research Crichton places into them but when it came to characters, Crichton is utterly flat. To return to Nicholls' comment above, it is not hard to see why one might think that as Crichton's novels tend to make better films than books - film allows Crichton's nondescript characters to be fleshed out with actors. `Jurassic Park' is an enjoyable page-turner but what really made it as a film and phenomenon was seeing the dinosaurs in all their ferocious, living-breathing CGI glory.
`Sphere' comes directed by Barry Levinson, of `Diner', `Toys' and `Wag the Dog' fame, as well as director of Crichton's `Disclosure'. The script adaption is from Paul Attanasio, creator with Levinson of the finest series on tv at the moment, `Homicide: Life on the Streets', and who also adapted (and improved) Crichton's `Disclosure' for Levinson. And `Sphere' is really quite an impressively well-made film - the unfolding of the alien contact scenes and the revelation of the alien's identity are eerie and suspenseful. There is perhaps a little too much running around between ships, but the science and underwater scenes are conducted with an impeccable and impressive realism. There is also an excellent score. Levinson and photographer Adam Greenberg invest the story with an increasingly dark, claustrophobic tone that quite begins to grip the imagination. And the combined efforts of all allow a story that seemed fairly naff on the page to gain considerable credibility on screen. Levinson and Attanasio even manage to tone down and make the ending quite believable.
But oddly `Sphere' has been the only Crichton film so far to have been a relative box-office disappointment. It is puzzling as to why `Sphere' died a box-office death as it is really quite a good film. One suspects the reason for such is that it eschews big-budget special effects which are synonymous with sf these days in favour of cerebral, psychological drama. There are no show-stopping scenes of mass destruction and the monsters that do appear are psychological not physical.
Crichton is an oddly divided writer. On one hand he has a fascination with technology - all his books come accompanied with graphs and diagrams - yet he is deeply sceptical of all this technology getting out of control. Underneath all of Crichton's work runs a single strand of pessimism. Crichton fears that human nature or simple human error will invariably cause things to go awry - be it a single strand of jammed computer tape nearly causing an entire viral containment facility to self-destruct in `The Andromeda Strain'; a epileptic becoming addicted to the electric shocks that are supposed to control him in `The Terminal Man'; or human greed causing unforeseen system foul-ups in both `Disclosure' and `Jurassic Park'; and machine error in `Westworld'. In `Jurassic Park' Crichton even manages to turn chaos theory - which is simply a mathematical paradigm for the impossibility of predicting behaviour in complex systems - into a kind of Murphy's Law where things will invariably go out of control. And in `Sphere' Crichton's themes are writ at their most visible. One film that makes interesting comparison here to `Sphere' is `Contact'. Both are films about alien contact and human prejudice. But where `Contact' says that alien contact can offer the possibility of a consciousness-expanding entry into a wider universe but that to accept it we must overcome small-mindedness; `Sphere', writ through with Crichton's usual doubts about human nature, is utterly pessimistic - holding the end view that humanity, given the miraculous ability to wish anything into being, will only manifest its deepest darkest fears and that we are better off without such a gift.
People have rushed to make comparisons between `Sphere' and other past sf films. There are undeniable comparisons that can be made to `Forbidden Planet' (1956) which involved a similar alien device which conjured forth repressed psychological fears, and `Solaris' (1972) with scientists aboard a space station being driven crazy by a sentient planet's manifesting forms from their unconscious in an attempt to communicate with them. A further point of comparative interest might also be last year's `Event Horizon' which inside its thorough muddle of ideas really wanted to be what `Sphere' emerges as. Of course the one film that most rushed to compare `Sphere' to was `The Abyss', being unaware that `Sphere' the novel predated `The Abyss'. But `Sphere' and `The Abyss' do make for interesting comparison. It may be heretical in light of the public disfavour given to `Sphere' to suggest that it actually works better as a story than `The Abyss' does but it is a case I am willing to argue. `The Abyss' had some grippingly intensive moments of human drama but the alien contact angle seemed awkwardly jammed onto the end, and the final scene (in both the original cinematic release and the 1992 `Special Edition') of the alien ship rising to the surface was a big anti-climax. `Sphere' works to a far more dramatically satisfying conclusion and certainly gives its alien contact theme a far more rigorous workout than `The Abyss' with its bunch of glowing, ethereal Spielberg castoffs who have come merely to wave nuclear disarmament flags does. Possibly this a film whose merit will undergo reevaluation in a few years time.
Copyright 1998 Richard Scheib
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Apache Avalon Mission
Apache Avalon is a collaborative software development project dedicated to providing a high-quality freely available component architecture according to the principles of the Apache Software Foundation [ASF]. This charter briefly describes the mission, history, organization, and processes of the Apache Avalon project. MISSION ======= Apache Avalon exists to promote and facilitate Component Based Design. Component Based Design is a proven practice that helps create systems that are loosely coupled and easy to maintain. Component Based Design requires a rigid software framework to function properly. Apache Avalon provides a specification for such a framework, an implementation of that specification and a compliance testing suite, and tools and components to facilate development using that framework. The software developed by the Apache Avalon project must be high performance, reliable, secure, and easy to use. The individual software components must be part of an underlying architectural orchestration that will allow them to work together without major negotiations or breakage. The process followed for the development of Apache Avalon software is the same as the process followed by other ASF projects: individuals and corporations collaborate on the best possible infrastructure, APIs, code, testing, and release cycles. In order to achieve a coherent architecture between Apache Avalon components and other components and applications, standards (formal or de facto) will be used as much as possible for both protocols and APIs. We will also allow the innovation of new protocols, APIs, and components in order to seed new concepts not yet defined by standards. HISTORY ======= This project was established under the direction of the Apache Software Foundation in November 2002 to facilitate joint open-source development. Prior to November 2002, Apache Avalon has been a part of the Apache Java project and the Apache Jakarta project. THE PROJECT MANAGEMENT COMMITTEE ================================ The Apache Avalon project is managed by a small, core group of contributors known as the Project Management Committee [PMC]. The PMC must have at least one ASF Officer, who will also be the PMC Chairperson and who will report to the ASF Board. See http://www.apache.org/foundation/bylaws.html for reference. The PMC has the following responsibilities: o Facilitating code or other donations by individuals or companies. o Resolving license issues and other legal issues. o Approving new committers. o Ensuring that administrative and infrastructure work is completed. o Overseeing Apache Avalon to ensure that the mission defined in this document is being fulfilled. o Resolving conflicts within the project. To become a member of the PMC, an individual must be nominated by a contributor, unanimously approved by all PMC members, and approved by a two-thirds majority of committers. In most cases, developers will have actively contributed to development for at least six months before being considered for membership on the PMC. The PMC is responsible for maintaining and updating this charter. Development must follow the process outlined in this charter, so any change to the development process necessitates a change to the charter. Changes must be unanimously approved by all members of the PMC. A contributor may challenge a change to the charter at any time and ask for a vote of all committers, in which case a two-thirds majority must approve the change. COMMITTERS ========== Committers are developers who have read/write access priviledges to the source code repository. New committers are added when a developer is nominated by a committer and approved by at least 50 percent of the existing committers with no opposing votes. In most cases, new committers will already be participating in the development process by submitting suggestions and/or fixes via the bug report page or mailing lists. CONTRIBUTORS ============ Anyone is allowed and encouraged to participate in the development of the Apache Avalon software products. Occasional contributors will be able to report bugs, participate in the mailing lists, and submit patches. Specific changes to a product proposed for discussion or voting on the appropriate development mailing list should be presented in the form of patches. When sent to the mailing list, the message should contain a subject beginning with [PATCH] and include a clear summary that describes the effect of that patch. Like all Apache projects, the Avalon project is a meritocracy -- the more work you do, the more you are allowed to do. Developers who make regular and substantial contributions may become committers as described above. LICENSING ========= All contributions to the Apache Avalon project adhere to the "ASF Source Code License." All contributions must be made under those terms. All contributions must contain the following copyright notice and license: ============================================================================ The Apache Software License, Version 1.1 ============================================================================ Copyright (C) 1997-2003 The Apache Software Foundation. All rights reserved. Redistribution and use in source and binary forms, with or without modifica- tion, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. The end-user documentation included with the redistribution, if any, must include the following acknowledgment: "This product includes software developed by the Apache Software Foundation (http://www.apache.org/)." Alternately, this acknowledgment may appear in the software itself, if and wherever such third-party acknowledgments normally appear. 4. The names "Apache", "Avalon", "Excalibur", "Fortress", "Phoenix", "Merlin" and "Apache Software Foundation" must not be used to endorse or promote products derived from this software without prior written permission. For written permission, please contact<EMAIL_ADDRESS>5. Products derived from this software may not be called "Apache", nor may "Apache" appear in their name, without prior written permission of the Apache Software Foundation.   This software consists of voluntary contributions made by many individuals on behalf of the Apache Software Foundation. For more information on the Apache Software Foundation, please see http://www.apache.org/. THE DEVELOPMENT PROCESS ======================= The development process is intentionally lightweight and follows the same guidelines as other ASF projects. The project committers decide which changes may be committed to the repository. Three +1 ('yes' votes) with no -1 ('no' votes or vetoes) are needed to approve a code change. For efficiency, some code changes from some contributors (e.g. feature additions, bug fixes) may be approved in advance, in which case they may be committed first and changed as needed, with conflicts resolved by majority vote of the committers. PRODUCT REQUIREMENTS ==================== All software products developed by Apache Avalon must have a set of requirments as well as an up-to-date release plan and architecture design. All software products developed by Apache Avalon must have a test system to verify their correct functioning and are ideally subject to continous integration testing, regression testing and unit testing. RELATIONSHIP TO OTHER APACHE PROJECTS ===================================== The Apache Avalon project should work closely with other Apache projects, such as Jakarta and Apache HTTP Server, to avoid redundancy and achieve a coherent architecture among Apache Avalon and these projects.


I spent the last three days talking to dozens of people about pooping.
The ease with which I can discuss the act of defecation is somewhat of a paradox — because I am exceedingly bathroom shy. Silent office restrooms with stall doors that end a foot and a half off the ground are my worst enemy, while the best workspace toilet experience I’ve ever had was, oddly, at a WeWork, where the barriers were floor to ceiling, there was always music playing, and each stall came equipped with its own bottle of air freshener spray.
Yet such restrooms are rare. In the United States, at least, we’re far more likely to encounter cramped, quiet bathrooms with terrible two-ply toilet paper and dribble on the seat. Even at home, where our bathrooms are typically more comfortable than what you’ll find at the mall or an office building, we’re limited to a basic setup: a plain porcelain bowl, with maybe two flush settings, beside a roll of whatever toilet paper you’re willing to invest in. God help you if you run out.
“Imagine a world where you only need to wipe once”
But it doesn’t have to be this way! All over the world, restrooms are blessed with more humane configurations. In some places, they come equipped with hoses so the user can more easily cleanse themselves after use. In others, such as France , bathrooms have bidets which perform the same function as the hose, only hands-free. And in some regions of Asia, most notably Japan, high-tech toilets with sound effects, heated seats, several bidet functions, and air dryers are as ubiquitous as automatic faucets, as Jane, a New York-based freelance calligrapher who lived in the Kagawa region of Japan for four years and requested that only her first name be used, told me.
“Imagine a world where you only need to wipe once, and that’s to take care of the excess water,” she says. “Where you’re not shocked in the morning by cold porcelain. Where you can let your bowels howl in public and face your co-workers at the sink because the bathroom is filled with sounds of artificial flushing (or whatever cute melody that given toilet is programmed to play) and you can hardly hear anything else.
In the U.S., though, such features are rare. I just used my first bidet, and it was such a revelation that I even more firmly believe that high-tech toilets — or, at the very least, bidets — should become the norm here in the States. Certain cultural and logistical barriers prevent Americans from fully embracing the high-tech toilet, but as we increasingly adopt other high-tech home items, such as smart air conditioners and even refrigerators , it’s possible that advanced toilets will follow.
“My first encounter with a Japanese water squirting toilet was a revelation,” says @jammy_sod, a Twitter user and fan of high-tech toilets who asked to remain anonymous to speak in detail about his bathroom habits. He was at a Japanese restaurant in New York called Sakagura, when he decided to “try out the waterworks,” that his friends were excitedly discussing at the table. He found it soothing and somewhat pleasurable, and the experience reinforced his lifelong belief that using toilet paper to wipe is insufficient.  The experience was so profound that he wanted to retrofit his toilet at home with a similar contraption, but his wife wasn’t on board.
The actual health benefits of bidets are up for debate, mostly because, as Wirecutter described, studies need a control group to show that the treatment in question is better than a placebo — and it’s really difficult to spray water at people’s butts without them noticing. Still, there’s some evidence that bidets are better for people with hemorrhoids or “pruritus ani,” also known as irritated buttholes, as the stream of water produces less friction that a wad of toilet paper. And some people who recently gave birth may find that bidets can be gentler on the entire bottom region.
It isn’t only the cleansing, potentially healthier bidet features that people love about high-tech toilets. Tori, a New York-based marketing consultant, told me she likes the sound effects that many high-tech toilets have. “I feel like that would make pooping at work a little less time consuming if you like to be alone for that,” she says. And Chié Dambara, who grew up in Japan and now owns Yoko Matcha, a matcha bar in Miami, says that “cold toilet seats in the winter are so sad.” She doesn’t have a high-tech toilet at her home in Miami, though. “Japan is simply a more advanced country,” she says.
American cultural stigma against the bidet has historically stalled its popularity here. As Maria Teresa Hart reported in a fascinating 2018 Atlantic feature on the history of the bidet, most Americans first encountered the appliance in brothels during WWII, forever cementing in their minds the association between sex work and bidets. And for many years, bidets were regarded as a form of birth control — to be clear, they aren’t — which convinced Americans that the devices were immoral.
“Cold toilet seats in the winter are so sad”
This cultural roadblock extends to the way houses are designed, which makes it difficult to integrate high-tech toilets or toilet seats in American bathrooms, as several acquaintances who wish they could install their own told me. Many homes in the States lack the toilet-adjacent outlets critical for those looking to install high-tech toilets powered by electricity. And then, of course, Americans often live in homes with multiple bathrooms, and aren’t willing to spend a lot of money on multiple toilets.
“Here in the U.S., we have lots of land, where we’ll live in a 3,500-square-foot home, and have bedrooms and parts of the home we’ll visit every 3–4 months,” says Bill Strang, president of corporate strategy and e-commerce for Japanese toilet brand TOTO. “There’s a plus side to that — more toilets — but the downside is that they put a lot of less expensive products into those spaces.” In Japan, he says, many people live in smaller homes and, because there’s less space to fill, they’re more willing to spend money on the items they need to purchase.
Still, Strang says, when he manages to convince Americans, even “rough and tumble guys” who are “a little anxious about getting sprayed somewhere in their nether regions” to at least try a high-tech TOTO toilet, they often end up purchasing one. Part of TOTO’s growth strategy in the United States is partnering with hotels, restaurants, and nightclubs so that potential consumers have the chance to experience their products. These people often leave reviews on Yelp , TripAdvisor , and other websites extolling the virtues of the toilets, post photos on Instagram of the blinged-out restroom, and tell their friends.
It works out for the restaurants, too, as Joe Conti, owner of New York-based Japanese restaurant Shuraku, knows all too well. He says that on the first night of opening, he witnessed a couple at the chef’s counter whispering excitedly about the restaurant’s TOTO toilet. “You’re thinking about the menu, the drinks, the colors, the smells, and everything, and one of the first things I hear is people talking about the toilet,” he says. “It’s been very consistent. We have people who post Instagram pics of our toilet, because it kind of lights up and the seat moves up by itself, it greets you.”
These efforts appear to be working: TOTO is now the number three toilet company in the U.S., Strang tells me. And according to the BRG Building Solutions’ October 2018 North American Shower Toilet & Bidet Seat Markets report, bidet seat and toilet sales are expected to grow 15% each year through 2021.
It’s a hopeful future for people like me, who have anxiety or troubled bowels and appreciate the sound effects many high-tech toilets make, as well as the heightened feeling of cleanliness that bidets bring. While I personally won’t be attaching a TOTO washlet to my own toilet anytime soon (my apartment, which I otherwise adore, only has a single outlet on the opposite side of the space as the toilet) I envy those who have the ability. They’re not cheap — the beginning TOTO is $250 , and a lower-end “SmartBidet” goes for $200 — and there are significant cultural and architectural hurdles to their full, nationwide adoption. But I’m crossing my fingers that as other pricey home appliances increase in popularity, high-tech toilets won’t be far behind.


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Introduction
Welcome to the Appia API. You can use our API to access Appia endpoints, which can query balances and transactions and tell you which of our users are cat people (jk, we deliberately don't know anything about our users).
We have language bindings in Shell, Ruby, Python, and JavaScript. BOOM. You can view code examples in the dark area to the right, and you can switch the programming language of the examples with the tabs in the top right.

- Should we rather just use terms like "where" (institution) and "what" (asset)?
Authentication
Update 15 Jan 2019: not yet implemented
To authorise, use this code:
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
import appia
api = appia.authorize('mypersonalapikey')
# With shell, you can just pass the correct header with each request
curl "api_endpoint_here"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
Make sure to replace
mypersonalapikey
with your API key.
Appia uses API keys to allow access to the API. To register a new API key, buy Kenny a beer and hope that he takes pity on you.
Appia expects for the API key to be included in all API requests to the server in a header that looks like the following:
Authorization: mypersonalapikey
Prices
Update 15 Jan 2019: implemented but not saved to a database
Price data of a set of assets / symbols (from_symbols) in a chose currency / symbol (to_symbol), gathered through our price aggregation.
Currently it calls the source(s) in real-time, but soon we will start caching the answers and do scheduled refreshes
curl "http://api.lettuce.money/prices?to_symbol=ZAR&from_symbols=BTC,USD,MSFT"
-H "Authorization: mypersonalapikey"
The above command returns JSON structured like this:
{
"timestamp": "2019-01-01T00:00:01.001Z",
"toSymbol": "ZAR",
"fromSymbols": [
{
"fromSymbol": "BTC",
"lastUpdated": "2018-12-31T11:59:01.001Z",
"price": 0.000021,
"source": "Crypto Compare"
},
{
"fromSymbol": "USD",
"lastUpdated": "2018-12-31T11:58:01.001Z",
"price": 0.07,
"source": "Crypto Compare"
},
{
"fromSymbol": "MSFT",
"last_updated": "2018-12-31T11:57:01.001Z",
"price": 1535.01,
"source": "Alpha Vantage"
}
]
}
Users
Update 15 Jan 2019: implemented only in the front-ends
We do not store any personal information about our users.
Every user is given a unique ID when the account is created.
In the future, users will be able to belong to groups. This is not available in our MVP, though, so set all "groups" to "null".
Get All Users
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.users.get
import appia
api = appia.authorize('mypersonalapikey')
api.users.get()
curl "http://example.com/api/users"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let users = api.users.get();
The above command returns JSON structured like this:
[
{
"id": 12345678,
"groups": null,
"deleted": false,
"baseCurrency": "ZAR",
"baseCurrencySymbol": "R",
"lastActivity": "2012-04-23T18:25:43.511Z",
"latestBalance": {
"amount": 203232.39,
"debitOrCredit": "debit",
"currency": "ZAR",
"time": "2012-04-23T18:25:43.511Z"
}
},
{
"id": 22345679,
"groups": null,
"deleted": false,
"baseCurrency": "BTC",
"baseCurrencySymbol": "Ƀ",
"lastActivity": "2017-04-23T18:25:43.511Z",
"latestBalance": {
"amount": 2.39,
"debitOrCredit": "debit",
"currency": "BTC",
"time": "2012-04-23T18:25:43.511Z"
}
}
]
This endpoint retrieves all users.
HTTP Request
GET http://inves.technology/api/users
Query Parameters
| Parameter | Default | Description |
|---|---|---|
| include_deleted | false | If set to true, the result will also include deleted users. |
Get a Specific User
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.users.get(12345678)
import appia
api = appia.authorize('mypersonalapikey')
api.users.get(12345678)
curl "http://inves.technology/users/212345678"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let max = api.users.get(12345678);
The above command returns JSON structured like this:
{
"id": 12345678,
"groups": null,
"deleted": false,
"baseCurrency": "ZAR",
"baseCurrencySymbol": "R",
"lastActivity": "2012-04-23T18:25:43.511Z",
"latestBalance": {
"amount": 203232.39,
"debitOrCredit": "debit",
"currency": "ZAR",
"time": "2012-04-23T18:25:43.511Z"
}
}
This endpoint retrieves a specific user.
HTTP Request
GET http://inves.technology/users/<ID>
URL Parameters
| Parameter | Description |
|---|---|
| ID | The ID of the user to retrieve |
Delete a Specific User
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.users.delete(12345678)
import appia
api = appia.authorize('mypersonalapikey')
api.users.delete(12345678)
curl "http://inves.technology/api/users/12345678"
-X DELETE
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let max = api.users.delete(12345678);
The above command returns JSON structured like this:
{
"id": 12345678,
"deleted": true
}
This endpoint deletes a specific user.
HTTP Request
DELETE http://inves.technology/users/<ID>
URL Parameters
| Parameter | Description |
|---|---|
| ID | The ID of the user to delete |
Portfolios
Update 15 Jan 2019: not yet implemented
A user can have multiple portfolios. A portfolio is a collection of accounts. By defualt, every user has 1 portfolio called "My Moneh".
Users can add up to 3 portfolios on the free tier, and can add up to 100 portfolios on the paid tier (TBC).
NOTE:
- Should be able to retrieve all portfolios for a single user.
- In the future, a portfolio could belong to a group.
Get All Portfolios
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.portfolios.get
import appia
api = appia.authorize('mypersonalapikey')
api.portfolios.get()
curl "http://example.com/api/portfolios"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let portfolios = api.portfolios.get();
The above command returns JSON structured like this:
[
{
"id": 12345678,
"name": "My Moneh",
"user": 12345678,
"accounts": [2392392, 2301938, 2938218],
"latestBalance": {
"amount": 2.39,
"debitOrCredit": "debit",
"currency": "BTC",
"time": "2012-04-23T18:25:43.511Z"
}
},
{
"id": 12345679,
"name": "Genesis Mining Income",
"user": 12345678,
"accounts": [2392393, 2301938],
"latestBalance": {
"amount": 1.39,
"debitOrCredit": "debit",
"currency": "ETH",
"time": "2012-04-23T18:25:43.511Z"
}
}
]
This endpoint retrieves all portfolios.
Accounts
Update 15 Jan 2019: implemented on the front-ends only
An account has a balance. A balance is a record of the current state of the account. An account can only have one type of asset inside it. That asset could be a currency, cryptocurrency, units of a fund, value of a house, or many other things. You cannot have a single account that is made up of two different currencies - as far as our system is concerned, those are two different accounts. It might, however, be helpful to sometimes group similar accounts for our users.
An account is somewhere, usually at an institution (e.g. Luno, Barclays) but sometimes on a paper wallet or in the deeds office (if I own a house). For consistency, our data structure will refer to all of these "wheres" as institutions even if it's a leather wallet in the user's backpack.
All balances are made up of a quantity of an asset that has a current price in the user's base currency. The quantity is the result of the sum of transactions that occured on an account.
Sometimes we know a lot about an account, so we can derive the current balance ourselves. For instance, say I have an account with Luno, and I own 10 ETH and 2 Bitcoins on that platform. I like to see everything converted back to South African Rands (this is my base currency). The price of BTC at this moment is R 90,000 and the price of ETH is R 2 000. Appia sees this as me having two accounts:
- A Luno (institution) ETH (asset) account with a quantity of 10 at a current price in my base currency of R 2 000. The balance of my account is therefore R 20 000. The asset type is "cryptocurrency".
- A Luno (institution) BTC (asset) account with a quantity of 2 at a current price in my base currency of R 90 000. The balance of my account is therefore R 180 000. The asset type is "cryptocurrency".
Say I also have an international share portfolio through EasyEquities. I own 15 shares in the S&P 500 that are worth R 100 each, and 3 shares of Netflix that are worth R 50 each. IF I am able to scrape all of this data with Appia, then Appia will see this as 2 accounts:
- A EasyEquities (institution) S&P 500 (asset) account with a quantity of 15 at a current price in my base currency of R 100. The balance of my account is therefore R 1 500. The asset type is "international equities".
- A EasyEquities (institution) Netflix (asset) account with a quantity of 3 at a current price in my base currency of R 50. The balance of my account is therefore R 150. The asset type is "international equities".
However, I may not be able to get this level of detail back from EasyEquities. In that case, Appia might see this as one account that we don't know a lot about:
- A EasyEquities (institution) account with a balance of R 1 650. I might know that the asset type is "international equities" but I may not know exactly what assets are held in that account.
Sometimes the asset held in a user's account will be identical to their base currency. It is still important to track the quantity separately to the balance where possible, though, because the user can change their base currency at any time.
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.accounts.get
import appia
api = appia.authorize('mypersonalapikey')
api.accounts.get()
curl "http://example.com/api/accounts"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let accounts = api.accounts.get();
The above command returns JSON structured like this:
[
{
"id": 12345678,
"where": "Ledger Nano",
"type": "tracked", // Can be "tracked" or "manual", in future releases, could be "linked"
"assetSymbol": "ETH",
"assetName": "Ethereum",
"assetType": "cryptocurrency",
"portfolios": [
// Optional: this account is listed in 2 portfolios
129302,
230199
],
"latestBalance": {
"debitOrCredit": "debit",
"price": 10, // In that user's base_currency
"quantity": 2.39,
"value": 20.9,
"currency": "ZAR",
"time": "2012-04-23T18:25:43.511Z",
"source": "Crypto Compare"
}
},
{
"id": 12345679,
"where": null,
"type": "tracked", // Can be "tracked" or "manual", in future releases, could be "linked"
"assetSymbol": "VOD.JS",
"assetName": "Vodacom South Africa",
"assetType": "equity",
"latestBalance": {
"value": 20.9, // For some accounts, we only return a value
"currency": "ZAR",
"time": "2012-04-23T18:25:43.511Z",
"source": "Alpha Vantage"
}
},
{
"id": 12345674,
"where": "Botswana",
"type": "manual", // Can be "tracked" or "manual", in future releases, could be "linked"
"assetSymbol": "ZAR",
"assetName": "4 cows",
"assetType": "manual",
"latestBalance": {
"value": 2000,
"currency": "ZAR",
"time": "2012-04-23T18:25:43.511Z",
"source": "manual"
}
}
]
Balances
Update 15 Jan 2019: not yet implemented
The historical and current balance of each user for each account, portfolio, and user overall. These balances are calculated at midnight for each user and stored historically. Today's balance is stored temporarily in this database if it's requested by a front-end, but it is over-written at midnight.
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.balances.get
import appia
api = appia.authorize('mypersonalapikey')
api.balances.get()
curl "http://example.com/api/balances"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let balances = api.balances.get();
The above command returns JSON structured like this:
[
{
"id": 12345678, // Can we rather use User-Date as the primary key?
"user": 12345678,
"day": "20180812",
"baseCurrency": "GBP", // all values below are expressed in this baseCurrency
"totalBalance": {
"amount": 39293.29,
"currency": "GBP"
},
"portfolioBalances": [
{
"portfolio": 230293,
"value": 239.23
},
{
"portfolio": 330293,
"value": -2939.29
}
],
"accountBalances": [
{
"manual": false,
"account": 230293,
"asset": "BTC",
"amount": 1.3,
"value": 29293.23
},
{
"manual": true,
"account": 320323,
"asset": null,
"amount": null,
"value": 3923.23
}
]
}
]
Events
Update 15 Jan 2019: not yet implemented
A log of all of the events that change the values of any account in the system. What occured, at what time, for what user. These events are things like: a transaction or trade was initiated, processed, rejected, failed or reversed. A new account was created or deleted.
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.events.get
import appia
api = appia.authorize('mypersonalapikey')
api.events.get()
curl "http://example.com/api/events"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let events = api.events.get();
The above command returns JSON structured like this:
[
{
"id": 12345678,
"user": 12345678,
"time": "2012-04-23T18:25:43.511Z",
"event": "New account linked"
}
// More events //
]
Assets
Update 15 Jan 2019: not yet implemented
A dictionary of all available assets.
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.assets.get
import appia
api = appia.authorize('mypersonalapikey')
api.assets.get()
curl "http://example.com/api/assets"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let users = api.assets.get();
The above command returns JSON structured like this:
[
{
"symbol": "ETH",
"name": "Ethereum",
"assetType": "cryptocurrency",
"displaySymbol": "Ξ",
"region": "United States"
}
// More assets //
]
Asset Types
Update 15 Jan 2019: not yet implemented
A dictionary of all available asset types, and arrays of the asset symbols included in that type.
require 'appia'
api = Appia::APIClient.authorize!('mypersonalapikey')
api.assetTypes.get
import appia
api = appia.authorize('mypersonalapikey')
api.assetTypes.get()
curl "http://example.com/api/assetTypes"
-H "Authorization: mypersonalapikey"
const appia = require("appia");
let api = appia.authorize("mypersonalapikey");
let assetTypes = api.assetTypes.get();
The above command returns JSON structured like this:
[
{
"assetType": "cryptocurrency",
"assets": ["ETH", "BTC", "LTC"]
}
// More asset types //
]
Errors
Update 15 Jan 2019: not yet implemented
The Appia API uses the following error codes:
| Error Code | Meaning |
|---|---|
| 400 | Bad Request -- Your request is invalid. |
| 401 | Unauthorized -- Your API key is wrong. |
| 403 | Forbidden -- You do not have the right permissions to view this record. |
| 404 | Not Found -- The specified record could not be found. |
| 405 | Method Not Allowed -- You tried to access a record with an invalid method. |
| 406 | Not Acceptable -- You requested a format that isn't json. |
| 410 | Gone -- The record requested has been removed from our servers. |
| 418 | I'm a teapot! |
| 429 | Too Many Requests -- You're requesting too many things! Slow down! |
| 500 | Internal Server Error -- We had a problem with our server. Try again later. |
| 503 | Service Unavailable -- We're temporarily offline for maintenance. Please try again later. |


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|
NUC029FAE BSP
V3.01.002
The Board Support Package for NUC029FAE
|
Macros | |
| #define | WDT ((WDT_T *) WDT_BASE) |
| Pointer to WDT register structure. More... | |
| #define | TIMER0 ((TIMER_T *) TIMER0_BASE) |
| Pointer to Timer 0 register structure. More... | |
| #define | TIMER1 ((TIMER_T *) TIMER1_BASE) |
| Pointer to Timer 1 register structure. More... | |
| #define | I2C ((I2C_T *) I2C_BASE) |
| Pointer to I2C register structure. More... | |
| #define | SPI ((SPI_T *) SPI_BASE) |
| Pointer to SPI register structure. More... | |
| #define | PWM ((PWM_T *) PWM_BASE) |
| Pointer to PWM register structure. More... | |
| #define | UART ((UART_T *) UART_BASE) |
| Pointer to UART register structure. More... | |
| #define | ADC ((ADC_T *) ADC_BASE) |
| Pointer to ADC register structure. More... | |
| #define | ACMP ((ACMP_T *) ACMP_BASE) |
| Pointer to ACMP register structure. More... | |
| #define | SYS ((SYS_T *) SYS_BASE) |
| Pointer to SYS register structure. More... | |
| #define | CLK ((CLK_T *) CLK_BASE) |
| Pointer to CLK register structure. More... | |
| #define | INT ((INT_T *) INT_BASE) |
| Pointer to INT register structure. More... | |
| #define | P0 ((GPIO_T *) P0_BASE) |
| Pointer to GPIO port 0 register structure. More... | |
| #define | P1 ((GPIO_T *) P1_BASE) |
| Pointer to GPIO port 1 register structure. More... | |
| #define | P2 ((GPIO_T *) P2_BASE) |
| Pointer to GPIO port 2 register structure. More... | |
| #define | P3 ((GPIO_T *) P3_BASE) |
| Pointer to GPIO port 3 register structure. More... | |
| #define | P4 ((GPIO_T *) P4_BASE) |
| Pointer to GPIO port 4 register structure. More... | |
| #define | P5 ((GPIO_T *) P5_BASE) |
| Pointer to GPIO port 5 register structure. More... | |
| #define | GPIO ((GPIO_DBNCECON_T *) GPIO_DBNCECON_BASE) |
| Pointer to GPIO de-bounce register structure. More... | |
| #define | GPIOBIT0 ((GPIOBIT_T *) GPIOBIT0_BASE) |
| Pointer to GPIO port 0 bit access register structure. More... | |
| #define | GPIOBIT1 ((GPIOBIT_T *) GPIOBIT1_BASE) |
| Pointer to GPIO port 1 bit access register structure. More... | |
| #define | GPIOBIT2 ((GPIOBIT_T *) GPIOBIT2_BASE) |
| Pointer to GPIO port 2 bit access register structure. More... | |
| #define | GPIOBIT3 ((GPIOBIT_T *) GPIOBIT3_BASE) |
| Pointer to GPIO port 3 bit access register structure. More... | |
| #define | GPIOBIT4 ((GPIOBIT_T *) GPIOBIT4_BASE) |
| Pointer to GPIO port 4 bit access register structure. More... | |
| #define | GPIOBIT5 ((GPIOBIT_T *) GPIOBIT5_BASE) |
| Pointer to GPIO port 5 bit access register structure. More... | |
| #define | FMC ((FMC_T *) FMC_BASE) |
| Pointer to FMC register structure. More... | |
The Declaration of NUC029FAE Peripheral
Pointer to ACMP register structure.
Definition at line 3225 of file NUC029FAE.h.
Pointer to ADC register structure.
Definition at line 3224 of file NUC029FAE.h.
Pointer to CLK register structure.
Definition at line 3228 of file NUC029FAE.h.
Pointer to FMC register structure.
Definition at line 3243 of file NUC029FAE.h.
| #define GPIO ((GPIO_DBNCECON_T *) GPIO_DBNCECON_BASE) |
Pointer to GPIO de-bounce register structure.
Definition at line 3236 of file NUC029FAE.h.
| #define GPIOBIT0 ((GPIOBIT_T *) GPIOBIT0_BASE) |
Pointer to GPIO port 0 bit access register structure.
Definition at line 3237 of file NUC029FAE.h.
| #define GPIOBIT1 ((GPIOBIT_T *) GPIOBIT1_BASE) |
Pointer to GPIO port 1 bit access register structure.
Definition at line 3238 of file NUC029FAE.h.
| #define GPIOBIT2 ((GPIOBIT_T *) GPIOBIT2_BASE) |
Pointer to GPIO port 2 bit access register structure.
Definition at line 3239 of file NUC029FAE.h.
| #define GPIOBIT3 ((GPIOBIT_T *) GPIOBIT3_BASE) |
Pointer to GPIO port 3 bit access register structure.
Definition at line 3240 of file NUC029FAE.h.
| #define GPIOBIT4 ((GPIOBIT_T *) GPIOBIT4_BASE) |
Pointer to GPIO port 4 bit access register structure.
Definition at line 3241 of file NUC029FAE.h.
| #define GPIOBIT5 ((GPIOBIT_T *) GPIOBIT5_BASE) |
Pointer to GPIO port 5 bit access register structure.
Definition at line 3242 of file NUC029FAE.h.
Pointer to I2C register structure.
Definition at line 3220 of file NUC029FAE.h.
Pointer to INT register structure.
Definition at line 3229 of file NUC029FAE.h.
Pointer to GPIO port 0 register structure.
Definition at line 3230 of file NUC029FAE.h.
Pointer to GPIO port 1 register structure.
Definition at line 3231 of file NUC029FAE.h.
Pointer to GPIO port 2 register structure.
Definition at line 3232 of file NUC029FAE.h.
Pointer to GPIO port 3 register structure.
Definition at line 3233 of file NUC029FAE.h.
Pointer to GPIO port 4 register structure.
Definition at line 3234 of file NUC029FAE.h.
Pointer to GPIO port 5 register structure.
Definition at line 3235 of file NUC029FAE.h.
Pointer to PWM register structure.
Definition at line 3222 of file NUC029FAE.h.
Pointer to SPI register structure.
Definition at line 3221 of file NUC029FAE.h.
Pointer to SYS register structure.
Definition at line 3227 of file NUC029FAE.h.
| #define TIMER0 ((TIMER_T *) TIMER0_BASE) |
Pointer to Timer 0 register structure.
Definition at line 3218 of file NUC029FAE.h.
| #define TIMER1 ((TIMER_T *) TIMER1_BASE) |
Pointer to Timer 1 register structure.
Definition at line 3219 of file NUC029FAE.h.
Pointer to UART register structure.
Definition at line 3223 of file NUC029FAE.h.
Pointer to WDT register structure.
Definition at line 3217 of file NUC029FAE.h.


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The PointGenerator class This class wraps the implementation of algorithms in order to generate point cloud data from a given surface.
More...
#include <point_generation.h>
|
| pcl::PointCloud< pcl::PointXYZ >::Ptr | randomlySampling (pcl::PolygonMesh mesh) |
| | Generate point cloud through randomly sampling. More...
|
| |
The PointGenerator class This class wraps the implementation of algorithms in order to generate point cloud data from a given surface.
◆ PointGenerator()
| benchmark::PointGenerator::PointGenerator |
( |
| ) |
|
|
inline |
◆ ~PointGenerator()
| benchmark::PointGenerator::~PointGenerator |
( |
| ) |
|
|
inline |
◆ generatePointCloud()
| void benchmark::PointGenerator::generatePointCloud |
( |
| ) |
|
Perform cloud generation.
◆ getPointCloud()
| pcl::PointCloud< pcl::PointXYZ >::Ptr benchmark::PointGenerator::getPointCloud |
( |
| ) |
|
Get the resulted point cloud.
- Returns
- Resulted point cloud
◆ inputPolygonMesh()
| void benchmark::PointGenerator::inputPolygonMesh |
( |
pcl::PolygonMesh |
mesh | ) |
|
Input a polygon mesh for point cloud generation.
- Parameters
-
| mesh | Triangle mesh representing the surface reconstruction |
◆ randomlySampling()
| pcl::PointCloud< pcl::PointXYZ >::Ptr benchmark::PointGenerator::randomlySampling |
( |
pcl::PolygonMesh |
mesh | ) |
|
|
private |
Generate point cloud through randomly sampling.
- Parameters
-
| mesh | Input mesh representing the surface reconstruction |
- Returns
- Resulted point cloud data
◆ setSampleSize()
| void benchmark::PointGenerator::setSampleSize |
( |
size_t |
size | ) |
|
Set the sample size.
- Parameters
-
◆ input_mesh
| pcl::PolygonMesh benchmark::PointGenerator::input_mesh |
|
private |
Triangle mesh representing the surface reconstruction
◆ output_cloud
| pcl::PointCloud<pcl::PointXYZ>::Ptr benchmark::PointGenerator::output_cloud {new pcl::PointCloud<pcl::PointXYZ>} |
|
private |
◆ sample_size
| size_t benchmark::PointGenerator::sample_size |
|
private |
The documentation for this class was generated from the following files:


IN DREAMS (M). (Paramount/Dreamworks) Director: Neil Jordan Stars: Annette bening, Robert Downey jr, Aidan Quinn, Stephen Rea, Paul Guilfoyle, Margo Martindale, Dennis Boutsikaris.
The best films from director Neil Jordan are those set in his native Ireland (The Crying Game, Michael Collins, etc), while his big budget Hollywood entertainments (We're No Angels, etc) are bland and disappointing. His latest film In Dreams falls into this latter category. Co-written by Bruce Robinson (the cult classic Withnail And I, The Killing Fields, etc) this bleak psychological thriller is adapted from the book by Bari Wood (who wrote the novel upon which David Cronenberg's creepy Dead Ringers was based).
The tormented heroine of the piece is Claire Cooper (Annette Bening), who writes and illustrates fairy tale books for a living. She is having terrible dreams and nightmares, most of them featuring a young boy in a room filling with water. It seems she has established a psychic connection with serial nutcase psychopath Vivian (Robert Downey jr), and witnesses some particularly gruesome murders. The only trouble is that no-one, including the local cops and her frequently absent airline pilot husband (Aidan Quinn, in a thankless role), will believe her.
When her own daughter becomes the killer's latest victim, Claire has a nervous breakdown and is institutionalised. It becomes apparent to Claire that the killer is deliberately passing messages to her, and she feels compelled to escape from prison and track him down to end her traumatic experience. But her dreams increasingly become blurred with reality.
Jordan deftly establishes an unsettling atmosphere that is reminiscent of far better thrillers (Don't Look Now, etc), but In Dreams is ultimately disappointing. This sort of thing has been done before (e.g.; The Eyes Of Laura Mars, etc), but unfortunately the potentially fascinating scenario is never quite convincing.
Jordan borrows much of the film's dark and forbidding structure from the very fairy tales that Claire illustrates. Jordan also imbues the film with plenty of surreal imagery and rich symbolism, particularly focusing on the colour red and apples, but it all becomes too messy and obscure. However, ace cinematographer Darius Khondji (Seven, etc) creates some memorable and evocative images.
Bening's performance has a nicely hysterical and over wrought edge that suits the grim mood of the material. There is a nicely ironic touch to the casting of Downey, especially given his recent legal troubles and his confessions to the tabloids, but he gives a performance that is enigmatic rather than malevolent and genuinely unnerving. Regular Jordan collaborator Stephen Rea is wasted in a stereotypical role as the haunted looking and sympathetic psychiatrist who tries to puzzle out the true meaning of Claire's strange dreams.
In Dreams leaves a nasty aftertaste in the mouth, and will have audiences feeling vaguely unsatisfied.
** greg king http://www.netau.com.au/gregking
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Related links: index of all rec.arts.movies.reviews reviews


Tabloid Proteome is a database of protein association network generated using publically available mass spectrometry based experiments in PRIDE.These associations represent a broad scala of biological associations between pairs of proteins that goes well beyond mere binary protein interactions. More info
Please upload a file that contains protein pairs and edge annotaion (if available) in the following file formats: xls, xlsx, csv. The first two columns should be Uniprot accessions of the proteins. If you have edge annotation, you can add it to the 3rd column. The file should not include any title.
Select file to upload:
Please upload a file that contains protein UniProt accessions (if available) in the following file formats: xls, xlsx, csv. When you click on the search button, you will have all possible 2 protein combinations from the list you provide by considering Jaccard Similarity Threshold. The file should not include any title.
Select file to upload:
Please upload a file that contains gene names (if available) in the following file formats: xls, xlsx, csv. The file should not include any title.
Select file to upload:


{% extends 'base.html' %} {% block content %} {% include "includes/inline_form.html" %}
No Puppet/Mcollective system information.
Please initiate a task to get system information first.
{% else %} {% include "ajax_templates/system_info_table.html" %} {% endif %}


Swift has another way of building complex data types called classes. They look similar to structs, but have a number of important differences, including:
All three of those are massive differences, so I'm going to cover them in more depth before continuing.
If we were to convert our Person
struct into a Person
class, Swift wouldn't let us write this:
class Person {
var clothes: String
var shoes: String
}
This is because we're declaring the two properties to be String
, which if you remember means they absolutely must have a value. This was fine in a struct because Swift automatically produces a memberwise initializer for us that forced us to provide values for the two properties, but this doesn't happen with classes so Swift can't be sure they will be given values.
There are three solutions: make the two values optional strings, give them default values, or write our own initializer. The first option is clumsy because it introduces optionals all over our code where they don't need to be. The second option works, but it's a bit wasteful unless those default values will actually be used. That leaves the third option, and really it's the right one: write our own initializer.
To do this, create a method inside the class called init()
that takes the two parameters we care about:
class Person {
var clothes: String
var shoes: String
init(clothes: String, shoes: String) {
self.clothes = clothes
self.shoes = shoes
}
}
There are two things that might jump out at you in that code.
First, you don't write func
before your init()
method, because it's special. Second, because the parameter names being passed in are the same as the names of the properties we want to assign, you use self.
to make your meaning clear – "the clothes
property of this object should be set to the clothes
parameter that was passed in." You can give them unique names if you want – it's down to you.
Important: Swift requires that all non-optional properties have a value by the end of the initializer, or by the time the initializer calls any other method – whichever comes first.
The second difference between classes and structs are that classes can build on each other to produce greater things, known as class inheritance. This is a technique used extensively in Cocoa Touch, even in the most basic programs, so it's something you should get to grips with.
Let's start with something simple: a Singer
class that has properties, which is their name and age. As for methods, there will be a simple initializer to handle setting the properties, plus a sing()
method that outputs some words:
class Singer {
var name: String
var age: Int
init(name: String, age: Int) {
self.name = name
self.age = age
}
func sing() {
print("La la la la")
}
}
We can now create an instance of that object by calling that initializer, then read out its properties and call its method:
var taylor = Singer(name: "Taylor", age: 25)
taylor.name
taylor.age
taylor.sing()
That's our basic class, but we're going to build on it: I want to define a CountrySinger
class that has everything the Singer
class does, but when I call sing()
on it I want to print "Trucks, guitars, and liquor" instead.
You could of course just copy and paste the original Singer
into a new class called CountrySinger
but that's a lazy way to program and it will come back to haunt you if you make later changes to Singer
and forget to copy them across. Instead, Swift has a smarter solution: we can define CountrySinger
as being based off Singer
and it will get all its properties and methods for us to build on:
class CountrySinger: Singer {
}
That colon is what does the magic: it means "CountrySinger
extends Singer
." Now, that new CountrySinger
class (called a subclass) doesn't add anything to Singer
(called the parent class, or superclass) yet. We want it to have its own sing()
method, but in Swift you need to learn a new keyword: override
. This means "I know this method was implemented by my parent class, but I want to change it for this subclass."
Having the override
keyword is helpful, because it makes your intent clear. It also allows Swift to check your code: if you don't use override
Swift won't let you change a method you got from your superclass, or if you use override
and there wasn't anything to override, Swift will point out your error.
So, we need to use override func
, like this:
class CountrySinger: Singer {
override func sing() {
print("Trucks, guitars, and liquor")
}
}
Now modify the way the taylor
object is created:
var taylor = CountrySinger(name: "Taylor", age: 25)
taylor.sing()
If you change CountrySinger
to just Singer
you should be able to see the different messages appearing in the results pane.
Now, to make things more complicated, we're going to define a new class called HeavyMetalSinger
. But this time we're going to store a new property called noiseLevel
defining how loud this particular heavy metal singer likes to scream down their microphone.
This causes a problem, and it's one that needs to be solved in a very particular way:
Singer
class doesn't have a noiseLevel
property.HeavyMetalSinger
that accepts a noise level.name
and age
of the heavy metal singer, so it can pass it onto the superclass Singer
.noiseLevel
) then pass on the other parameters for the superclass to use.That might sound awfully complicated, but in code it's straightforward. Here's the HeavyMetalSinger
class, complete with its own sing()
method:
class HeavyMetalSinger: Singer {
var noiseLevel: Int
init(name: String, age: Int, noiseLevel: Int) {
self.noiseLevel = noiseLevel
super.init(name: name, age: age)
}
override func sing() {
print("Grrrrr rargh rargh rarrrrgh!")
}
}
Notice how its initializer takes three parameters, then calls super.init()
to pass name
and age
on to the Singer
superclass - but only after its own property has been set. You'll see super
used a lot when working with objects, and it just means "call a method on the class I inherited from.” It's usually used to mean "let my parent class do everything it needs to do first, then I'll do my extra bits."
Class inheritance is a big topic so don't fret if it's not clear just yet. However, there is one more thing you need to know: class inheritance often spans many levels. For example, A could inherit from B, and B could inherit from C, and C could inherit from D, and so on. This lets you build functionality and re-use up over a number of classes, helping to keep your code modular and easy to understand.
When you copy a struct, the whole thing is duplicated, including all its values. This means that changing one copy of a struct doesn't change the other copies – they are all individual. With classes, each copy of an object points at the same original object, so if you change one they all change. Swift calls structs "value types" because they just point at a value, and classes "reference types" because objects are just shared references to the real value.
This is an important difference, and it means the choice between structs and classes is an important one:
If I were to summarize this key difference between structs and classes, I'd say this: classes offer more flexibility, whereas structs offer more safety. As a basic rule, you should always use structs until you have a specific reason to use classes.


Dual-search and Plot
Search using Audio Commons two keywords and see how results are distributed
1st keyword
2nd keyword
Search
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Processing data with model...


Workshop Material
All videos of the workshop are available at slideslive.
All accepted papers are availabe at openreview.
Workshop Summary
Learning-based methods, and in particular deep neural networks, have emerged as highly successful and universal tools for image and signal recovery and restoration. They achieve state-of-the-art results on tasks ranging from image denoising, image compression, and image reconstruction from few and noisy measurements. They are starting to be used in important imaging technologies, for example in GEs newest computational tomography scanners and in the newest generation of the iPhone.
The field has a range of theoretical and practical questions that remain unanswered. In particular, learning and neural network-based approaches often lack the guarantees of traditional physics-based methods. Further, while superior on average, learning-based methods can make drastic reconstruction errors, such as hallucinating a tumor in an MRI reconstruction or turning a pixelated picture of Obama into a white male.
This virtual workshop aims at bringing together theoreticians and practitioners in order to chart out recent advances and discuss new directions in deep neural network-based approaches for solving inverse problems in the imaging sciences and beyond.
Schedule
The workshop schedule is aligned with 7:30 AM to 4 PM PT; please see this converter for conversion to your specific time zone.
The workshop is livestreamed at the NeurIPS workshop webpage. To access this website you need to register for the conference at https://neurips.cc/ and be logged in.
The videos of the talk can also be previewed as of now through the NeurIPS workshop webpage. The livestream will play the videos, and each of the talks is followed by a live discussion. You can attend the live discussion either through the live stream or you can join the zoom session. Questions should be asked through rocketchat, and a co-organizer will moderate.
During the designated discussion sessions you can talk to the respective speakers in gather.town. To get the gather.town link, visit the official NeurIPS schedule at the NeurIPS workshop webpage.
The poster session is also on gather.town. The gather.town link is accessible through the the NeurIPS workshop webpage.
| Time | Event |
|---|---|
| 7:30 | Newcomer presentation |
| 7:55 | Opening Remarks |
| 8:00 | Victor Lempitsky (Skoltech): Generative Models for Landscapes and Avatars |
| 8:30 | Thomas Pock (TU Graz): Variational Networks |
| 9:00 | Contributed talk 1: Vineet Edupuganti, Morteza Mardani, Shreyas Vasanawala, John M. Pauly: Risk Quantification in Deep MRI Reconstruction |
| 9:15 | Contributed talk 2: Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon: GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images |
| 9:30 | Break and Discussion with Victor Lempinsky, Thomas Pock, and Erich Kobler |
| 10:00 | Rebecca Willett (University of Chicago): Model Adaptation for Inverse Problems in Imaging |
| 10:30 | Stefano Ermon (Stanford): Generative Modeling via Denoising |
| 11:00 | Contributed talk 3: Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price: Compressed Sensing with Approximate Priors via Conditional Resampling |
| 11:15 | Chris Metzler: Approximate Message Passing (AMP) Algorithms for Computational Imaging |
| 11:30 | Discussion with Rebecca Willett and Stefano Emron |
| 12:00 | Break |
| 1:00 | Poster session |
| 2:00 | Peyman Milanfar (Google) - Denoising as Building Block Theory and Applications |
| 2:30 | Rachel Ward (UT Austin) |
| 3:00 | Larry Zitnick (Facebook AI Reseach) - fastMRI |
| 3:30 | Discussion with Peyman Milanfar, Rachel Ward, and Larry Zitnick |
| 4:00 | End of official program |
Accepted papers
All accepted papers are available on openreview:
-
Approximate Probabilistic Inference with Composed Flows
Jay Whang, Erik Lindgren, Alex Dimakis -
Bayesian Inference in Physics-Driven Problems with Adversarial Priors
Dhruv V Patel, Deep Ray, Harisankar Ramaswamy, Assad Oberai -
Compressed Sensing with Approximate Priors via Conditional Resampling
Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price -
Compressed Sensing with Invertible Generative Models and Dependent Noise
Jay Whang, Qi Lei, Alex Dimakis -
Deep Learning for Plasma Tomography in Nuclear Fusion
Diogo R. Ferreira, Pedro J. Carvalho -
Deep Learning Initialized Phase Retrieval
Raunak Manekar, Zhong Zhuang, Kshitij Tayal, Vipin Kumar, Ju Sun -
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems
Zaccharie Ramzi, Benjamin Remy, Francois Lanusse, Jean-Luc Starck, Philippe Ciuciu -
GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images
Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon -
Generative Tomography Reconstruction
Matteo Ronchetti, Davide Bacciu -
Generator Surgery for Compressed Sensing
Jung Yeon Park, Niklas Smedemark-Margulies, Max Daniels, Rose Yu, Jan-Willem van de Meent, Paul Hand -
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Joseph Dean, Giannis Daras, Alex Dimakis -
Learning Spectral Regularizations for Linear Inverse Problems
Hartmut Bauermeister, Martin Burger, Michael Moeller -
Learning to Sample MRI via Variational Information Maximization
Cagan Alkan, Morteza Mardani, Shreyas Vasanawala, John M. Pauly -
Likelihood-Free Inference with Deep Gaussian Processes
Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski -
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction
Riccardo Barbano, Zeljko Kereta, Chen Zhang, Andreas Hauptmann, Simon Arridge, Bangti Jin -
Risk Quantification in Deep MRI Reconstruction
Vineet Edupuganti, Morteza Mardani, Shreyas Vasanawala, John M. Pauly -
Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser
Zahra Kadkhodaie, Eero Peter Simoncelli -
Towards Neurally Augmented ALISTA
Freya Behrens, Jonathan Sauder, Peter Jung -
Uncertainty-Driven Adaptive Sampling via GANs
Thomas Sanchez, Igor Krawczuk, Zhaodong Sun, Volkan Cevher -
Unlocking Inverse Problems Using Deep Learning: Breaking Symmetries in Phase Retrieval
Kshitij Tayal, Chieh-Hsin Lai, Raunak Manekar, Zhong Zhuang, Vipin Kumar, Ju Sun
Call for Papers and Submission Instructions
We invite researchers to submit anonymous papers of up to 4 pages (excluding references and appendices) which will be considered for contributed workshop papers. No specific formatting is required. Authors are encouraged to use the workshop edition of the NeurIPS style file, but they may use any other style as long as it has standard font size (11pt) and margins (1in). The paper can have an appendix of unlimited lenght.
Submission at OpenReview will be open from Sep. 1 until the submission deadline on October 9, 2020.
We welcome all submission in the intersection of inverse problems and deep learning including contributions related to robustness and biases, neural network architectures, regularization, optimization methods, datasets, theoretical foundations (including rigorous recovery guarantees, provable convergence, and bounds on representation errors), untrained methods, generative models, end-to-end methods, and applications in imaging, time series, and beyond. We especially encourage submissions related to the following questions:
-
Deep learning based approaches can make drastic reconstruction errors and may introduce biases. How common are such issues, can such reconstruction difficulties be alleviated, and if yes, how?
-
Deep learning based approaches often lack the guarantees of the traditional physics based methods. What theoretical results are necessary and possible?
-
Untrained neural networks such as the deep image prior have shown that neural networks alone, without any learning, can give excellent reconstruction performance. How important is training on the target distribution for imaging performance and is it possible to achieve state-of-the art performance without training?
Important Dates
- Submit the final version and poster by December 1, 2020 at OpenReview
- Submission Deadline: Extended to October 12, 2020 (this is the final deadline).
- Notification: October 23, 2020.
- Workshop: Friday December 11
Organizers
- Reinhard Heckel (TUM)
- Paul Hand (Northeastern)
- Soheil Feizi (UMD)
- Lenka Zdeborova (CEA/SACLAY)
- Richard Baraniuk (Rice University)
Please email<EMAIL_ADDRESS>with any questions.


Flags unvisited/unread (opened in the background, usually with the middle click) tabs, so it is easy to recognise what tabs still need to be read/visited.
You will easily know what tab you opened but have not yet looked into it. It is especially useful when you are searching for something on the internet, opening many links in the background. After a while you may be confused what tabs you have read and what you still need to look into. This extenstion solves the issue. You will always know what tabs was never visited.
The given version is based on the original Unread Tab 1.3 by Adam Grodzki and inspired by Anton Marchenko's needs 😉 and his experience in using “Yandex.Browser”.
The main differences of this version are:
:
The project is open-source and public at GitHub.


Home to the Empire State Building, Times Square, Statue of Liberty and other iconic sites, New York City is a fast-paced, globally influential center of art, culture, fashion and finance. The city’s 5 boroughs sit where the Hudson River meets the Atlantic Ocean, with the island borough of Manhattan at the “Big Apple's" core.
London, England’s capital, set on the River Thames, is a 21st-century city with history stretching back to Roman times. At its centre stand the imposing Houses of Parliament, the iconic ‘Big Ben’ clock tower and Westminster Abbey, site of British monarch coronations. Across the Thames, the London Eye observation wheel provides panoramic views of the South Bank cultural complex, and the entire city.
Dubai is a city in the United Arab Emirates known for luxury shopping, ultramodern architecture and a lively nightlife scene. Burj Khalifa, an 830m-tall tower, dominates the skyscraper-filled skyline. At its foot lies Dubai Fountain, with jets and lights choreographed to music. On man-made islands just offshore is Atlantis, the Palm, a resort with water and marine-animal parks.
Paris, France's capital, is a major European city and a global center for art, fashion, gastronomy and culture. Its picturesque 19th-century cityscape is crisscrossed by wide boulevards and the River Seine. Beyond such landmarks as the Eiffel Tower and the 12th-century, Gothic Notre-Dame cathedral, the city is known for its cafe culture, and designer boutiques along the Rue du Faubourg Saint-Honoré.
Toronto, the provincial capital of Ontario, Canada, is a large, ethnically diverse city sprawling along Lake Ontario’s northwestern shore. A dynamic metropolis with a core of soaring skyscrapers, all dwarfed by the iconic CN Tower, it also features abundant green spaces, from the orderly oval of Queen’s Park to 400-acre High Park and its trails, sports facilities and zoo.
Malaysia is a Southeast Asian country occupying the Malaysian Peninsula and part of the island of Borneo. It's known for its beaches, rainforests and mix of Malay, Chinese, Indian and European influences. The sprawling capital, Kuala Lumpur, is home to colonial buildings, busy shopping districts such as Bukit Bintang and skyscrapers including the iconic, 451m-tall Petronas Twin Towers.


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ES&CS
Home
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I was on a free holiday/trip on a course i am doing, when on one day while we were doing abseiling i saw a boy (M) who took his medication (i didnt know he was an ex-heroin user at the time) and he looked really messed up and feeling a decent high and said to me i should try it, being away from home with no substances whatsoever it looked like a fun time.
So later on when we got back to the big house we were staying i asked M for one, he told me he'd give me one tomorrow.
The next day i awoke with a 7 mile walk across mountains on a really hot day ahead of us, just before we left M called me into his room where he gave me two 4mg subutex tablets (i didnt know they where them at the time i was told it was methadone or something)and he told me to put them under my toungue and let them dissolve, i did and they tasted pretty bad but we all went on with the walk.
I was really looking forward to this high at the time and after about one hour and maybe a bit more i started to get a really nice warm feeling inside this continued for awhile. We walked about 1 or 2 miles when we stopped for a break and lunch i smoked a cigarette and lay down in the sun and felt nice, but from after this point when i wasnt laying down i felt really sick and this was annoying knowing i still had a good 5 miles left.
I managed to force myself through this sickness for a very long time with one or two breaks which were amazing peaking laying down in the sun not feeling sick, but the second i stood up again it'd just get worse. I had no food and everyones water supply was on ration mode as everyone didnt bring enough so it was becoming very annoying.
By about 5-6 miles someone let me have a sip of there oasis drink, we got to the next break point but by now i just needed to get back as the sickness was getting worse and worse so i got pissed off and walked off throwing by bag on the floor and sat away from the group knowing being sick was pretty close.
The next 2 miles were just me feeling really sick and being sick a couple more times without being seen luckily.

I stumbled out of the van by now to many of my group was around so i tried to find a sly place to be sick in this carpark which was really hard so i just walked around a car and sat on the floor and proceeded to be really sick when a few of my group saw me and the leaders where all informed. I managed to blag them earlier i was ill and they thought i had lack of water and heat stroke so didnt have to make any excuses just annoying and embarrasing situation. I went into the supermarkets toilet and sorted myself out and stared at my pinprick pupils as i am not used to seeing them like this as i have never got high on an opiate before. I got to sit next to the window with a bottle of water on the way back this made me feel much better with the fresh air blowing on me.
I got back to the house and slept for a few hours and woke up still feeling quite spaced out for quite awhile.

All in all i thought it was quite a funny experience accept for the really bad sickness and some instructers on the walk being dickheads to me but i got them back on the last day of the trip when i was making everyones sandwiches i flemmed and spat all over theres. Also the day after this was my first time i tried salvia(10x) after a ketamine, Weed and mdma session, pretty classic week.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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IAN TEDA
Hi, I am Ian Teda and this my story so far:
I enjoy a good adventure, and cannot help but wonder what is around the next corner. My most exciting adventure at the moment is raising my two young boys – Austin and Dillan – with my beautiful wife Laura.
I have been fortunate to work as a Civil Engineer on some amazing infrastructure projects within NSW and ACT Australia. Some highlights from that work, that I am proud to say I was involved in include: balanced cantilever segmental bridges; dry well intake tower and new RCC dam; bulk earthworks; the manufacture of pre-tensioned bridge elements such as pile caps, Super T beams, planks and Reinforced Concrete Box Culverts; the Sydney Light Rail design.
My hard work and determination has come with the satisfaction of seeing large infrastructure projects being born, projects that I am proud to tell my boys I have worked on.
To find out more about my work, checkout my LinkedIn Profile
To find out what I am up to right now, checkout my now page.
What I am trying to live by:
My curiosity has lead to skills in:
Project Management, Cost Management, Scheduling, Estimating, Community, & Contract Management.
Bridges, Drainage, Dams, Water, Precast, Bulk Earthworks, Drill & Blast, Diaphragm Wall Tunnels, Structures & Light Rail, Engineering Rule Book.
Some ideas (thoughts) that I have put a URL to recently:
Keep up date with the latest happenings:


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Hi, I am You, I enjoy writing Java-Spring & React.
Technologies I use for building systems.
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Feature Extraction¶
Temporal Features¶
- deeg.features.skewness(array)¶
Calculate the feature “skewness” of the EEG signal. We support both 1d array input and DEEG standard input (p,m,e). For the later format, we calculate SKEW on dim “e” and return a (p,m) numpy array.
- Parameters
array (numpy array) – the temporal signal for feature extraction. 1d or with multiple dimensions
- Returns
int or numpy array, depends on the input shape
- deeg.features.kurtosis(array)¶
Calculate the feature “kurtosis” of the EEG signal. We support both 1d array input and DEEG standard input (p,m,e). For the later format, we calculate KURT on dim “e” and return a (p,m) numpy array.
- Parameters
array (numpy array) – the temporal signal for feature extraction. 1d or with multiple dimensions
- Returns
int or numpy array, depends on the input shape
- deeg.features.mean_absolute_deviation(array)¶
Calculate the mean_absolute_deviation on EEG data
- Parameters
array (numpy array) – the temporal signal for feature extraction. 1d or with multiple dimensions
- Returns
int or numpy array, depends on the input shape
Frequency Features¶
- deeg.features.differential_entropy(array)¶
Calculate the feature Differential Entropy with hypothesis that processed signal is normal-distributed. We support both 1d array input and DEEG standard input (p,m,e). For the later format, we calculate DE on dim “e” and return a (p,m) numpy array.
- Parameters
array (numpy array) – the temporal signal for feature extraction. 1d or with multiple dimensions
- Returns
int or numpy array, depends on the input shape
- deeg.features.power_spectral_density(array, signal_frequency, window_size)¶
Calculate the power spectral density on EEG signal. We support both 1d array input and DEEG standard input (p,m,e). For the later format, we calculate PSD on dim “e” and return a (p,m) numpy array.
- Parameters
array (numpy array) – the temporal signal for feature extraction. 1d or with multiple dimensions
signal_frequency (original frequency of the signal) – int
window_size (int) – size of the window
- Returns
band tuple or numpy array of power, depends on the input shape
Mutichannel Features¶
- deeg.features.rational_asymmetry(array, channel_name)¶
Calculate the rational asymmetry, of EEG signal.
- Parameters
array (numpy array) – the temporal signal(>=2d) for feature extraction.
channel_name (list or 1d array) – the names of all the channels of the EEG signal
- Returns
numpy array.
- deeg.features.differential_asymmetry(array, channel_name)¶
Calculate the differential asymmetry of EEG signal.
- Parameters
array (numpy array) – the temporal signal (>=2d) for feature extraction
channel_name (list or 1d array) – the names of all the channels of the EEG signal
- Returns
numpy array
- deeg.features.differential_caudality(array, channel_name)¶
Calculate the differential caudality of EEG signal.
- Parameters
array (numpy array) – the temporal signal (>=2d) for feature extraction
channel_name (list or 1d array) – the names of all the channels of the EEG signal
- Returns
numpy array