| DOSE: T+ 0:00 |
200 seeds |
oral |
Morning Glory |
(ground / crushed) |
| T+ 1:20 |
7 hits |
smoked |
Cannabis |
(tar / resin) |
Alright, well I'll start by saying that I am 16 and am a somewhat healthy person. I am a very frequent marijuana user, about 1-3 times a day. I take no medication, and have tried DXM a few times, shrooms once, alcohol, and pot. I go to therapy because I am facing a few relationship troubles in my life along with school and the law. I am basically a reasonable person and am mostly level headed. On this particular day, I hadn't planned on doing the seeds that night, but I was in a good mood all day.
Preparation:
About a month prior, I picked up 5 packets of Burpee Heavenly Blue Morning Glory Seeds at $1.79 a pack weighing apx. 1.5 g each. Total, there were 272 seeds exactly. I was unaware if the seeds were coated with pesticides, etc., so I put them in a tuperware dish with a little bit of washing detergent and water. I shook them for about a minute, washed them, and repeated. I let them sit overnight on a paper towel to dry. The next day, I dumped the seeds into our Mr. Coffee coffee grinder. I ground the seeds almost to powder. They were milky yellow looking and smelled a little like nuts, but very unique. I dumped them all onto a plate and seperated the chunkier parts from the powder because I planned on grinding up the chunks more, but I didn't bother.
Setting:
My room in late March in the Chicago suburbs after my mom fell asleep. I stayed in my room the almost the entire time until I fell asleep.
T-0:00 hrs:
The time was about 10:15 when I poured the powdered seeds into a cup of bottled water. I decided to try and avoid tap water because of the extra ions and chemicals found in it that I heard could break down the LSA. I didn't put the chunky seeds in simply because I didn't know how strong the effects were. I regret that. The water looked kinda gross, but I downed it. It didn't taste bad at all and went down pretty easily. I went downstairs to drink a few glasses of orange juice; I heard that vitamin C can aid in psychedelic experiences.
T-0:30 hrs:
I went outside to have a cigarette behind my garage and noticed that there was a kind of light distortion in my peripheral vision. The ground seemed to be somewhat glowing. Very subtle, but I got excited.
T-1:00 hrs:
After about half the video is done, I didn't really feel any effects. My pupils were pretty dialated and my eyes were somewhat bloodshot. My eyes get shot really easily. I became a little disappointed because I thought onset was supposed to arrive at about 1 hour.
T-1:20 hrs:
Believing that I had made a dud mixture, I decided to take out my bowl. I didn't have any weed, so I scraped the sides of my piece and got about 7 nice resin hits off of it.
T-1:30 hrs:
I felt a nice high from smoking, and got excited again. I looked at my eyes and they were almost fully dialated. I started laughing at the insane look on my face. I laid back down and closed my eyes to see some cool visuals.
T-1:45 hrs:
I saw that it is almost a half hour since I smoked and I still felt pretty blitzed. Usually after only a few hits I am coming down after about 15-20 min. Things started to have a sort of psychedelic feel to them. My sense of touch was intensified because I remember sliding my hands across my bed and feeling really good.
T-2:10 hrs:
The effects were definitely set in by this point. Smoking was the perfect entrance into the trip, though I'd really classify this more as a high than a trip. I put on some Electric Light Orchestra and Pink Floyd and laid back down in my bed. The music was very visual behind my eyes. I was able to 'see' the guitar's notes in Shine On You Crazy Diamond. Everything seemed so wonderful.  In the dark my walls seemed to have a colored dotting effect and were quite translucent. I thought about a lot of issues in my life and didn't exactly resolve any of them, but I felt good about where I stood on many of them. It seemed like it was impossible for the trip to turn bad. With shrooms, I had a terrible trip (I thought that my friends were my hallucinations and were actually police). Overall I felt great
T-3:00-5:00 hrs:
During this time I was grooving pretty good to the music I was listening to: ELO, Pink Floyd, Polyphonic Spree (very psychedelic, especially 'Soldier Girl'), Led Zeppelin, and The Beattles. I put my CD (about 1 hr. long) on repeat. Every time I heard a song it felt like the first time I had ever heard it and I was transfixed on the glowing rhythms of it all. I laughed at myself because I knew that it was just silly, but that thought just made everything hilarious. My visuals were a little blurred, but everything was very colorful. My sense of touch was very intense and I tried to touch just about every texture I could find.
T-6:00 hrs:
I got a little tired of my music and decided that I should probably go to sleep (about 4:30 am).  I closed my eyes and tried to fall asleep, but found it more difficult than I had imagined. It probably took me about 45 min. to eventually fall into a deep sleep.
 I felt no hangover effects at all. I felt groggy due to the fact that I only got 5 hrs. of good sleep, but again, nothing out of the ordinary.
In the future I plan on taking about 350 ground seeds using the same preparation method that I used before. On another note, I felt minimal to no nausea. I think the only nausea I felt was because I was aware that MG could cause nausea. I think that if I hadn't known that, it would have been completely fine. I compare this to a light shroom trip, but I think it would have been better if I had taken all of my seeds and if I had been in a more stimulating environment than my bedroom.
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.


2 overrides of ProcessNewEvent
System.Management.Automation (2)
engine\EventManager.cs (2)
916
protected override void
ProcessNewEvent
(PSEventArgs newEvent, bool processInCurrentThread)
1634
protected override void
ProcessNewEvent
(PSEventArgs newEvent, bool processInCurrentThread)


The target Attribute
Visit W3schools!
If target="_blank", the link will open in a new browser window or tab.


eBay Begins Black Friday Sale Early – Here Are the Best Deals
The online marketplace is offering a massive 20% off loads of brands including Playstation, Converse, Samsung and Apple.
by PCMag StaffWe review products independently, but we may earn affiliate commissions from buying links on this page. Terms of use.
eBay has kicked off its Black Friday sale two weeks early by slashing prices on popular products from Playstation, Converse, Samsung, Xbox, Apple and more.
How To Activate The Coupon
Shoppers can take advantage of this deal by using eBay’s special 20% off coupon. The code is PRIZE20. You’ll just need to enter this at the checkout, when prompted.
SEE ALSO: Black Friday UK 2019: The Best Deals on Laptops, TVs, Gaming, and Tech
The maximum discount you can score is £75 per sale, and you’re only able to use the code once. There’s also a minimum spend of £25, so you’ll have to get strategic with your shopping.
The coupon is valid until 11.59pm on Thursday, November 21, so it might be smart to get your eBay Watch List sorted in advance.
Items On Offer
Given the variety of brands you can use the coupon on, you’re looking at bagging bargains on a range of must-have items this Black Friday and Cyber Monday.
Perhaps a versatile new pair of sneakers, an exciting console to help get you through the dragging winter months, or a new TV for the whole family.
Here are some of the items that will be eligible for the 20% discount:
Samsung Ultra HD Smart 4K HDR TV for £279.20 (was £349.00)
Apple Watch Series 4 (GPS Only) for £246.96 (was £308.70)
Dolce & Gabbana 50ml The Only One Eau De Parfum for £42.80 (was £53.50)
Hotpoint Double Oven Cooker in White for £275.99 (was £344.99)
Xbox One S 1TB Gears 5 Console Bundle for £175.99 (was £219.99)
What Other Deals Will eBay Release?
While the online marketplace has kicked off its Black Friday sale early with this sensational offer, this is far from the end of eBay's deals. More bargains are due to be released, particularly as it gets closer to November 29.
Last year, eBay released new deals every day in the lead up to the big day. Buyers could take advantage of massive reductions on tech, clothing, toys, and home items from big brands like Dyson, Samsung and Lenovo, as well as savings across the branded outlet stores of Very, Currys and Argos.
Some stand out deals included a £174 saving on a Samsung 43-inch Smart TV, and the Ultra Ears megaboom speaker discounted to only £99.
Other fantastic deals included 20% off everything at Boohoo, a Simba Hybrid refurbished mattress for £152, and a KitchenAid Artisan stand mixer for £274 (down from £599).
New users to Quidco could also grab themselves a £15 cashback bonus when they signed up to Quidco and made a £10 purchase at eBay.
This article was originally published on BlackFriday.co.uk


Teen slashed in the face, leg outside Bronx high school
by WABCNORWOOD, Bronx (WABC) -- A teenager was slashed multiple times outside a school complex in the Bronx Wednesday afternoon.
The 16-year-old victim was wounded in the face and leg around 2:30 p.m. outside 100 West Mosholu Parkway, a building that has several high schools including Dewitt Clinton High School in the Norwood section.
Several suspects fled the scene, and no arrests have been made.
The teen was rushed to Jacobi Medical Center in stable condition with non-life threatening injuries.
The investigation is ongoing.
The Department of Education issued the following statement:
"NYPD and EMS immediately responded to a serious incident which occurred after dismissal outside of the building, and the student is in stable condition. School staff accompanied the student to the hospital and we will provide any needed additional support."


|
AAX SDK
2.3.1
Avid Audio Extensions Development Kit
|
#include <AAX_IACFComponentDescriptor.h>
Versioned description interface for an AAX plug-in algorithm callback.
Public Member Functions | |
| virtual AAX_Result | Clear ()=0 |
| Clears the descriptor. More... | |
| virtual AAX_Result | AddReservedField (AAX_CFieldIndex inFieldIndex, uint32_t inFieldType)=0 |
| Subscribes a context field to host-provided services or information. More... | |
| virtual AAX_Result | AddAudioIn (AAX_CFieldIndex inFieldIndex)=0 |
| Subscribes an audio input context field. More... | |
| virtual AAX_Result | AddAudioOut (AAX_CFieldIndex inFieldIndex)=0 |
| Subscribes an audio output context field. More... | |
| virtual AAX_Result | AddAudioBufferLength (AAX_CFieldIndex inFieldIndex)=0 |
| Subscribes a buffer length context field. More... | |
| virtual AAX_Result | AddSampleRate (AAX_CFieldIndex inFieldIndex)=0 |
| Subscribes a sample rate context field. More... | |
| virtual AAX_Result | AddClock (AAX_CFieldIndex inFieldIndex)=0 |
| Subscribes a clock context field. More... | |
| virtual AAX_Result | AddSideChainIn (AAX_CFieldIndex inFieldIndex)=0 |
| Subscribes a side-chain input context field. More... | |
| virtual AAX_Result | AddDataInPort (AAX_CFieldIndex inFieldIndex, uint32_t inPacketSize, AAX_EDataInPortType inPortType)=0 |
| Adds a custom data port to the algorithm context. More... | |
| virtual AAX_Result | AddAuxOutputStem (AAX_CFieldIndex inFieldIndex, int32_t inStemFormat, const char inNameUTF8[])=0 |
| Adds an auxiliary output stem for a plug-in. More... | |
| virtual AAX_Result | AddPrivateData (AAX_CFieldIndex inFieldIndex, int32_t inDataSize, uint32_t inOptions=AAX_ePrivateDataOptions_DefaultOptions)=0 |
| Adds a private data port to the algorithm context. More... | |
| virtual AAX_Result | AddDmaInstance (AAX_CFieldIndex inFieldIndex, AAX_IDma::EMode inDmaMode)=0 |
| Adds a DMA field to the plug-in's context. More... | |
| virtual AAX_Result | AddMIDINode (AAX_CFieldIndex inFieldIndex, AAX_EMIDINodeType inNodeType, const char inNodeName[], uint32_t channelMask)=0 |
| Adds a MIDI node field to the plug-in's context. More... | |
| virtual AAX_Result | AddProcessProc_Native (AAX_CProcessProc inProcessProc, IACFUnknown *inProperties, AAX_CInstanceInitProc inInstanceInitProc, AAX_CBackgroundProc inBackgroundProc, AAX_CSelector *outProcID)=0 |
| Registers an algorithm processing entrypoint (process procedure) for the native architecture. More... | |
| virtual AAX_Result | AddProcessProc_TI (const char inDLLFileNameUTF8[], const char inProcessProcSymbol[], IACFUnknown *inProperties, const char inInstanceInitProcSymbol[], const char inBackgroundProcSymbol[], AAX_CSelector *outProcID)=0 |
| Registers an algorithm processing entrypoint (process procedure) for the native architecture. More... | |
| virtual AAX_Result | AddMeters (AAX_CFieldIndex inFieldIndex, const AAX_CTypeID *inMeterIDs, const uint32_t inMeterCount)=0 |
| Adds a meter field to the plug-in's context. More... | |
| Public Member Functions inherited from IACFUnknown | |
| virtual BEGIN_ACFINTERFACE ACFRESULT ACFMETHODCALLTYPE | QueryInterface (const acfIID &iid, void **ppOut)=0 |
| Returns pointers to supported interfaces. More... | |
| virtual acfUInt32 ACFMETHODCALLTYPE | AddRef (void)=0 |
| Increments reference count. More... | |
| virtual acfUInt32 ACFMETHODCALLTYPE | Release (void)=0 |
| Decrements reference count. More... | |
|
pure virtual |
Clears the descriptor.
Clears the descriptor and readies it for the next algorithm description
|
pure virtual |
Subscribes a context field to host-provided services or information.
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
| [in] | inFieldType | Type of field that is being added |
|
pure virtual |
Subscribes an audio input context field.
Defines an audio in port for host-provided information in the algorithm's context structure.
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
|
pure virtual |
Subscribes an audio output context field.
Defines an audio out port for host-provided information in the algorithm's context structure.
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
|
pure virtual |
Subscribes a buffer length context field.
Defines a buffer length port for host-provided information in the algorithm's context structure.
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
|
pure virtual |
Subscribes a sample rate context field.
Defines a sample rate port for host-provided information in the algorithm's context structure.
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
|
pure virtual |
Subscribes a clock context field.
Defines a clock port for host-provided information in the algorithm's context structure.
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
|
pure virtual |
Subscribes a side-chain input context field.
Defines a side-chain input port for host-provided information in the algorithm's context structure.
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
|
pure virtual |
Adds a custom data port to the algorithm context.
Defines a read-only data port for plug-in information in the algorithm's context structure. The plug-in can send information to this port using AAX_IController::PostPacket().
The host guarantees that all packets will be delivered to this port in the order in which they were posted, up to the point of a packet buffer overflow, though some packets may be dropped depending on the inPortType
and host implementation.
| [in] | inFieldIndex | Unique identifier for the port, generated using AAX_FIELD_INDEX |
| [in] | inPacketSize | Size of the data packets that will be sent to this port |
| [in] | inPortType | The requested packet delivery behavior for this port |
|
pure virtual |
Adds an auxiliary output stem for a plug-in.
Use this method to add additional output channels to the algorithm context.
The aux output stem audio buffers will be added to the end of the audio outputs array in the order in which they are described. When writing audio data to a specific aux output, find the proper starting channel by accumulating all of the channels of the main output stem format and any previously-described aux output stems.
The plug-in is responsible for providing a meaningful name for each aux outputs. At the very least, individual outputs should be labeled "Output xx", where "xx" is the aux output number as it is defined in the plug-in. The output name should also include the words "mono" and "stereo" to support when users are looking for an output with a specific stem format.
| [in] | inFieldIndex | DEPRECATED: This parameter is no longer needed by the host, but is included in the interface for binary compatibility |
| [in] | inStemFormat | The stem format of the new aux output |
| [in] | inNameUTF8 | The name of the aux output. This name is static and cannot be changed after the descriptor is submitted to the host |
|
pure virtual |
Adds a private data port to the algorithm context.
Defines a read/write data port for private state data. Data written to this port will be maintained by the host between calls to the algorithm context.
| [in] | inFieldIndex | Unique identifier for the port, generated using AAX_FIELD_INDEX |
| [in] | inDataSize | Size of the data packets that will be sent to this port |
| [in] | inOptions | Options that define the private data port's behavior |
|
pure virtual |
Adds a DMA field to the plug-in's context.
DMA (direct memory access) provides efficient reads from and writes to external memory on the DSP. DMA behavior is emulated in host-based plug-ins for cross-platform portability.
For more information, see Direct Memory Access .
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
| [in] | inDmaMode | AAX_IDma::EMode that will apply to this field |
|
pure virtual |
Adds a MIDI node field to the plug-in's context.
The resulting MIDI node data will be available both in the algorithm context and in the plug-in's data model via UpdateMIDINodes().
To add a MIDI node that is only accessible to the plug-in's data model, use AAX_IEffectDescriptor::AddControlMIDINode()
| [in] | inFieldIndex | The ID of the port. MIDI node ports should formatted as a pointer to an AAX_IMIDINode. |
| [in] | inNodeType | The type of MIDI node, as AAX_EMIDINodeType |
| [in] | inNodeName | The name of the MIDI node as it should appear in the host's UI |
| [in] | channelMask | The channel mask for the MIDI node. This parameter specifies used MIDI channels. For Global MIDI nodes, use a mask of AAX_EMidiGlobalNodeSelectors |
|
pure virtual |
Registers an algorithm processing entrypoint (process procedure) for the native architecture.
| [in] | inProcessProc | Symbol for this processing callback |
| [in] | inProperties | A property map for this processing callback. The property map's values are copied by the host and associated with the new ProcessProc. The property map contents are unchanged and the map may be re-used when registering additional ProcessProcs. |
| [in] | inInstanceInitProc | Initialization routine that will be called when a new instance of the Effect is created. See Algorithm initialization. |
| [in] | inBackgroundProc | Background routine that will be called in an idle context within the same address space as the associated process procedure. See Background processing callback |
| [out] | outProcID |
|
pure virtual |
Registers an algorithm processing entrypoint (process procedure) for the native architecture.
| [in] | inDLLFileNameUTF8 | UTF-8 encoded filename for the ELF DLL containing the algorithm code fragment |
| [in] | inProcessProcSymbol | Symbol for this processing callback |
| [in] | inProperties | A property map for this processing callback. The property map's values are copied by the host and associated with the new ProcessProc. The property map contents are unchanged and the map may be re-used when registering additional ProcessProcs. |
| [in] | inInstanceInitProcSymbol | Initialization routine that will be called when a new instance of the Effect is created. Must be included in the same DLL as the main algorithm entrypoint. See Algorithm initialization. |
| [in] | inBackgroundProcSymbol | Background routine that will be called in an idle context within the same address space as the associated process procedure. Must be included in the same DLL as the main algorithm entrypoint. See Background processing callback |
| [out] | outProcID |
|
pure virtual |
Adds a meter field to the plug-in's context.
Meter fields include an array of meter tap values, with one tap per meter per context. Only one meter field should be added per Component. Individual meter behaviors can be described at the Effect level.
For more information, see Plug-in meters .
| [in] | inFieldIndex | Unique identifier for the field, generated using AAX_FIELD_INDEX |
| [in] | inMeterIDs | Array of 32-bit IDs, one for each meter. Meter IDs must be unique within the Effect. |
| [in] | inMeterCount | The number of meters included in this field |


I've always suspected Sherlock Holmes to be a bit of a fluke. His remark "You see but you do not observe" always rang a bit hollow with me. Sherlock hardly seemed to be a type of person who would have the patience to observe things. He was a sort of fellow who at one instant was quietly playing a mournful tune on his violin and at another jumping on to his chemistry set trying to decipher the composition of tobacco ash. It all seemed a bit fantastic. Which is why I was very excited at the idea of watching without a clue, a documentary of sorts, exposing the truth behind Sherlock Holmes. Many layers of Holmes' personality were revealed to me that helped me understand the great "detective" better.
On the last point I would like to point out that Sherlock Holmes should not be seen as an old pervert. He was true a gentleman. Sure he had some flaws of character but no one is perfect. There were some pluses and some minuses but on the whole he came out to be a very sober sort of a fellow.
Most of the times that is. He liked to drink. Make no mistake about it. He used to enjoy his time at the bar where, after indulging in a few drinks at the expense of his friend Dr Watson, he went about dancing and pinching women on their bums. He wouldn't normally behave in this way. But what was the poor man to do? Mrs Hudson, his landlady, had prohibited alcohol in her premises.
To his credit most of the time Mr Holmes was a very composed man and also a good story teller. Sometimes he got his facts mixed up but he never let minor inconsistencies get in the way of a gripping narrative. For example consider the "Adventure of the dancing Mamba" (or was it mambo? I'm not too sure about it) that he relates to his friends at the bar:-
"It was a night like any other, when suddenly a knock came at the door. I opened it, and there were these Manchurians, doing a rather festive Caribbean dance... "
Thinking was not really his speciality. He was however good actor and he usually let Watson "fill in the details" while he applied an artistic finishing touch to the explanation by ending it with "indeed", "precisely" and "exactly". It was quite absorbing to see Holmes perform these feats.
On an occasion entire village gathered around him when he began questioning an eye witness. Every inquiry was met with an enthusiastic applause from the crowd and a nervous wide eyed gulp by the witness. After he managed to elicit an appropriate response there was a even a procession to celebrate his victory.
That is not to say that Holmes was bad at deduction. He often performed quite admirably. For example when Ms. Leslie wonders who abducted her father Holmes promptly replies "Abductors". One has to admit that the man was good thinking on his feet. Even though nature of his work demanded him to be on his knees, he never shrank from his duty which, I feel, is a mark of a true gentleman. Overall it could be said that Holmes had the makings of a good detective.
Holmes and Watson, they had their little tiffs from time to time. Once Watson even threw him out of his apartment. But the two were made for each other. Watson discovered that he can not really make a living as a "Crime Doctor" even though he was quite sharp. Similarly Holmes discovers that he was pretty much useless without his friend. They both needed each other.
While Sherlock and Watson from the main attraction in Without a clue there are many many things to like about in the movie. The charming villages of England and the old fashioned streets of 18th century London, bustling with activity, are beautifully depicted. I could almost smell the cake in the corner shop! Even though the film is mainly comical no effort was spared in making it as true to the original books as possible. The only place where it differs from the books is in the interpretation of Sherlock's genius. While the original stories were happy to make him look like an incredibly clever detective, somehow I got the impression that the movie makers best understood Holmes as a bumbling buffoon. That is the effect of great literature I suppose. It attracts very contradictory but equally plausible explanations from people who care to read.
The supporting cast is hilarious. Inspector Lestrade, as expected, is portrayed as a very uptight police officer of the Scotland yard. Holmes never misses a chance to insult him. In one instance he makes him hold his overcoat and hat while he investigates the crime scene. Then there are the baker street irregulars, the miscreants of baker street who are employed by Holmes to spy for him. My favourite among the supporting cast was the, previously mentioned, poor villager who was absolutely terrified at the prospect of being interrogated by Holmes. For a bit of moral support he asks his wife to be present during the questioning to which she gladly agrees. She gives him a few suggestions like to "take off his hat" while Mr Holmes was questioning him and overall making sure that her husband was on his best behaviour. I must say she succeeded in her endeavour.
Michael Caine and Ben Kingsly play the roles of Sherlock Holmes and Watson, respectively, to perfection. I however liked the portrayal of Mrs Hudson as a strict but caring landlady the best. All in all without a clue is, without a doubt, my favorite Sherlock Holmes movie.
The game is a foot?


The Guelder Valley layout is made out of {{ costSummary.totalItems }} parts that I’ve sorted into {{ costSummary.categories.length }} groups. Choose a group below to see photos and more details.
You can jump straight to the locomotives, coaches or wagons sections for a summary of the rolling stock on the layout.
If you’re more interested in the composition of the collection, take a look at this high-level overview.
I’m keeping track (pun not originally intended) of the estimated cost of the layout while building it – these values are currently
The estimated cost is simply a loose guideline to understand which elements have cost the most and is not intended to act as a reference for the price of the layout. Since it is still being built, it is very likely these numbers will likely change!
Costs are calculated using the price I paid for an item or the retail price. If neither of these are known, the average price on second-hand sites is used.
Some items have unknown prices as they were bought over 20 years ago. They may require further research to convert their prices to modern day equivalents.


"You might belong in Gryffindor,
Where dwell the brave at heart,
Their daring, nerve, and chivalry
Set Gryffindors apart"
Godric Gryffindor
Professor Godric Gryffindor was a wizard of medieval times and one of the four Founders of Hogwarts School of Witchcraft and Wizardry. He was good friends with Salazar Slytherin but opposed him when he later thought that they should not accept Muggle-born students at Hogwarts. It is unknown when he died. Gryffindor's birthplace became known as Godric's Hollow, in his honour. Godric Gryffindor's portrait still remains at Hogwarts.


Sarah
There be an issue, cap'n
MOTIVATED / INSPIRED / F**KING C**L
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ABOUT THE CREATORS
Sarah is coming to codefellows with a background in drawing and painting. She has enjoyed learning a new skill and getting to know her classmates... who have made all the frustrations of merge conflicts, linter errors and miss placed parentheses more bearable.
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MYSTIC PIZZA A film review by Mark R. Leeper Copyright 1988 Mark R. Leeper
Capsule review: The lives of two sisters and a friend, pizza parlor waitresses, is not original and the individual stories are predictable, but as a whole it is a satisfying slice-of-life film and worth seeing. Rating: low +2.
MYSTIC PIZZA is a sort of a THE BEST OF EVERYTHING for the Eighties. I guess that in itself is something of a surprise: that someone is making a THE BEST OF EVERYTHING in the Eighties. It is not a film with much flash. It is just a quiet (dare I say it?) soap opera about three young women who waitress together in a pizza parlor and share each other's lives. There are the two sisters Kat and Daisy and their friend Jojo. Kat is the serious sort. She is holding down several jobs to try to earn enough to take advantage of a scholarship from Yale. Her sister Daisy is affable, attractive, and shoots a mean game of pool. She is looking to have a little bit of fun and to live a little. Jojo wants to be like Daisy.  MYSTIC PIZZA is really three stories, one for each woman, braided together into a single story.
Of the three stories the film concentrates mostly on the sisters' stories; neither is particularly original. Kat babysits for the daughter of a handsome young architect who happens to be a Yale graduate and whose wife is off in Europe. You can plot this one yourself. Daisy has a relationship with a rich law student with a checkered past and a bigoted family. Perhaps you cannot plot this one yourself, but it is unlikely you will be very surprised either.
So the individual stories are not much to see the film for. But this is one of those films where the whole is considerably more than the sum of its parts. For one thing, there are few enough films that show women who are friends and how their friendship works, and at times does not work.
MYSTIC PIZZA is not one of the year's best films--though I think at least one critic was claiming that it was--but at a time when so many films look alike it is a surprisingly satisfying film to watch and enjoy and hopefully is a sign of more adult films (no, I mean *literally* adult films) being made. Rate it a low +2 on the -4 to +4 scale.
(Oh, a side note: New York City restaurants offered a dinner to go with viewing BABETTE'S FEAST, but it was about $100 a plate. After seeing TAMPOPO I could not find a Japanese noodle house nearby. For those of you who want to coordinate a movie and dinner, this is the film!)
Mark R. Leeper att!mtgzz!leeper<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


---
layout: presentation
title: Introduction
permalink: /01s-intro/
---
layout: true
---
.skip[
# Softwarearchitektur
]
.skip[
Prof. Dr.-Ing. Korbinian Riedhammer
]
---
# Introduction
- Software Architecture: mandatory class for CS majors
- materials
- https://ohm-softa.github.io
- Github organization: https://github.com/ohm-softa (BIO)
- ...in English! ☺
- slides, lecture notes, assignments (with READMEs)
- class: Fridays at 11.30a **(HW.303)** (updated Mar 18)
- tutorials:
- Tuesdays at *9.45a* in HQ.306, starting Mar 21.
- Thursdays at *9.45a* on Zoom (until May), Starting Mar 23.
- Fridays at *9.45a* in HQ.406, starting Mar 24.
- _nota bene: assignments typically take longer than 90'!_
???
https://github.com/gnab/remark/wiki/Formatting
Materialien auf Englisch, Vorlesung aber auf Deutsch.
Github orga ist closed/BIO--by invitation only
Office hours: Übungen kann man nicht in 90' Programmieren.
---
# Credits (Leistungsnachweis)
- written exam (90') at the end of the term
- you may bring three (3) pages notes (stapled and signed)
- you must sign up for the exam
- theoretical and coding questions
---
# Review (what you should know by now!)
## Programmieren 1 (now: Prozedurale Programmierung)
- imperative programming
- constants, variables, expressions, functions, I/O
- basic data structures (fields, arrays, lists)
- pointers ☺
## Programmieren 2 (now: Objektorientierte Programmierung)
- OOP, classes and objects (and references! ☺)
- basic data structures (lists, maps, etc.)
- interfaces and inheritance
- errors, exceptions and how to deal with them
---
# Agenda for Software Architecture
See https://ohm-softa.github.io/ (Syllabus)
- modularity and component based development
- UML, mostly class, component and sequence diagrams
- programming patterns: idioms, design, architecture
- assignments: tools and toolkits
Assignments are one week "behind".
---
# About this Class
### I'd like you to become better programmers
### Some slides, but mostly hands-on live coding (plus lecture notes!)
.skip[
All examples are found in the `/examples/` directory of the [site's repository](https://github.com/ohm-softa/ohm-softa.github.io/tree/master/examples).
]
---
# A note on (programming) languages
- class materials are in English (so is most of the internet/SO)
- examples are (mostly) in Java...
- ...but translate to C#, C++, Python, Scala, etc.
- we'll focus on the concept, not the language
---
# Software Architecture
...is a craft.
- takes practice
- takes patience
- takes diligence
- takes experience
---
# Don't be that guy...
.center[
![Goto](/assets/xkcd292-goto.png)
]
.right[
]
---
# Speaking of `goto`
## Why would you use `goto`?
## Is it possible in C#?
## Is it possible in Java?
???
c#: yes, emulate while, break outer loops
Java: no; but break out of outer loops with labelled loops and labeled break/continue
---
.center[
]
.right[
]
---
# Agenda today
1. What is software architecture?
2. What is abstraction?
3. What is decomposition?
4. Clean Code
5. Tools
---
# Software Architecture
Thoughts?
---
# Software Architecture
## Complexity
- Ideal: linear process (analysis, draft, implementation, test, maintenance)
- Constrained by: features, budget, time
- Real world: somethings changes along the way...
## Architecture
- Result of the software development process
- Components, systems, subsystems, etc.
- V-model, agile, ..., typically recurrent at some stage
---
# Abstraction
Thoughts?
---
# Abstraction
## high level → low level
- drive to the airport
- → go straight, right, straight, left, ...
- →→ clutch, brake, ignition, put in drive, ...
.skip[
- reduce complexity by removing details
- goal: model a system from a specific point of view
]
???
see: H. Stachowiak: Allgemeine Modelltheorie, Springer Verlag, 1973
---
# Abstraction
## Example: programming
- hardware instructions
- assembler (low-level)
- c, fortran, java (high-level)
- code generators
---
# Decomposition
Thoughts?
---
# Stepwise Refinement
> [...] a sequence of design decisions concerning the decomposition of a task into subtasks and of data into data structures
N. Wirth, "[Program Development by Stepwise Refinement](https://dl.acm.org/citation.cfm?id=362577)", Comm. ACM, 1971
→ break problem down in simpler problems until solvable
---
# Functional Decomposition
- Thoughts follow the process
- Bottom-up/top-down
### Example: Withdraw cash at ATM
- insert debit card
- enter pin
- select amount
- process cash
- ...
---
# Object Oriented Decomposition
> it is almost always incorrect to begin the decomposition of a system into modules on the basis of a flowchart. We propose instead that one begins with a list of difficult design decisions or design decisions which are likely to change. Each module is then designed to hide such a decision from the others. Since, in most cases, design decisions transcend time of execution, modules will not correspond to steps in the processing.
D.L. Parnas, "[On the Criteria used in Decomposing Systems into Modules](https://dl.acm.org/citation.cfm?id=361623)", Comm. ACM, 1972
### Modularization and Encapsulation
> Every module [...] is characterized by its knowledge of a design decision which it hides from all others. Its interface or definition was chosen to reveal as little as possible about its inner workings.
→ Coherence and loose/tight coupling
???
probably one of the reasons OOP became so popular...
---
# Some Guidelines for Good (OO) Architecture
## High Cohesion, Low Coupling
There should be high cohesion within classes and packages, but low coupling between objects and across packages.
## Law of Demeter
In simple words: "Each unit should have only limited knowledge about other units: only units "closely" related to the current unit.".
K. Liebherr, I. Holland and A. Riel: "[Object-oriented programming: an objective sense of style](https://dl.acm.org/citation.cfm?id=62113)", Proc. OOPSLA, 1988
## High Fan-In, Low Fan-Out
---
# A Bit of "Historic" Context
- early days of programming (pre 60s!) focused on procedures
- the 1970s layed the ground work (see previously cited papers!)
- 1970: Smalltalk (Xerox PARC; object oriented language)
- 1973: ML (U Edinburgh; functional language)
- 90s and 2000s: OOP widely taught as "gold standard", FP often considered "academic"
- 2010s and onwards: heavy parallelization reintroduced FP (almost hype!)
- "old" languages introduce functional elements (Java, C++, ...)
- Scala
- Actor frameworks, e.g. Akka
---
# Clean Code
---
# Clean Code
- Choose good naming conventions
- Methods should be short, concise and with few paramters
- Comments only where needed; rewrite bad code
- Java conventions?
- [Google Java Format](https://github.com/google/google-java-format)
- [Elasticsearch](https://github.com/elastic/elasticsearch/blob/master/CONTRIBUTING.md#contributing-to-the-elasticsearch-codebase)
- Please read "Clean Code" by Prof. Tavakoli (`Teams > General > Files`)
---
# Tools
- Your preferred search engine
- Your preferred interactive generative information system*)
- [Stack Overflow](https://stackoverflow.com/questions/tagged/java)
- [Java documentation](https://docs.oracle.com/javase/11/docs/)
- JetBrains [IntelliJ](https://www.jetbrains.com/idea/), Community Edition (free!*)
- [Git version control](https://git-scm.com/)
*) Mind you: assignments are not mandatory — copying a solution typically has zero benefit


How would you rate the overall conversation with Pepper on scale from 1(lowest) to 5(highest)?
1
2
3
4
5
Next


The following code shows a method of reading analogue sensors on the digital input only Pi. A Light Dependent Resistor (LDR) varies its resistance according to the incident light intensisty.
Here P1-1 is used for 3V3, P1-20 is used for ground, and gpio 18
(P1-12) is used for the gpio.
#include <stdio.h>
#include <pigpio.h>
/*
-----------------------------------------------------------------------
3V3 ----- Light Dependent Resistor --+-- Capacitor
----- Ground
|
+-- gpio
cc -o LDR LDR.c -lpigpio -lpthread -lrt
sudo ./LDR
*/
#define LDR 18
/* forward declaration */
void alert(int pin, int level, uint32_t tick);
int main (int argc, char *argv[])
{
if (gpioInitialise()<0) return 1;
gpioSetAlertFunc(LDR, alert); /* call alert when LDR
changes state */
while (1)
{
gpioSetMode(LDR, PI_OUTPUT); /*
drain capacitor */
gpioWrite(LDR, PI_OFF);
gpioDelay(200); /* 50 micros is
enough, 200 is overkill */
gpioSetMode(LDR, PI_INPUT); /* start
capacitor recharge */
gpioDelay(10000); /* nominal 100
readings per second */
}
gpioTerminate();
}
void alert(int pin, int level, uint32_t tick)
{
static uint32_t inited = 0;
static uint32_t lastTick, firstTick;
uint32_t diffTick;
if (inited)
{
diffTick = tick - lastTick;
lastTick = tick;
if (level == 1) printf("%u %d\ ",
tick-firstTick, diffTick);
}
else
{
inited = 1;
firstTick = tick;
lastTick = firstTick;
}
}
cc -o LDR LDR.c -lpigpio -lrt -lpthread
sudo ./LDR >LDR.dat &
pigs no
pig2vcd </dev/pigpio0 >LDR.vcd &
pigs nb 0 0x40000 # set bit for gpio 18
Change the light falling on the LDR for a few seconds (e.g.
shine a torch on it or shade it with your hands).
pigs nc 0
The file LDR.vcd will contain the captured waveform, which can be viewed using GTKWave.
Overview
Reading circa every 10ms
One reading, circa 400us
The file LDR.dat will contain pairs of timestamps and recharge
time (in us). The following script will convert the
timestamps into seconds.
awk '{print $1/1000000, $2}' LDR.dat
>LDR-secs.dat
Gnuplot is a useful tool to graph data.
Gnuplot readings 14-24 seconds


--- layout: page title: About header-img: "img/about-bg.png" ---
Specifically random words chosen to formulate ramblings about coding, web development and sometimes music.


@* * Copyright 2019 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @(utr: String, previousTaxYear: String)(implicit pertaxContext: PertaxContext, messages: play.api.i18n.Messages) @scriptElem = { } @main(Messages("label.we_are_processing_your-details"), Some(Messages("label.your_personal_tax_account")), scriptElement = Some(scriptElem)) {
@Messages("label.this_may_take_up_to_30_seconds")
@Html(Messages("label.if_you_are_not_redirected_in_", pertaxContext.configDecorator.ssoToSaAccountSummaryUrl(utr, previousTaxYear)))


Left-click to start. SPACE to play. Left-click to restart.
Left-click
SPACE
Made by Patrick Lindsay in 2015.


⚡ Lightning on Demand |
|||
|---|---|---|---|
Science |
Projects |
Events |
Contribute |
Many electrical events in Nature seem to defy conventional theory, such as superlong discharges and the creation point of lighting in storm clouds.
Our goal is to build a set of Tesla towers that can actually trigger these large-scale phenomena, and discover how they get around existing theoretical limits.
The towers need to be 121 feet tall and deliver over 15 times the power of the largest Tesla tower ever built, but we believe this is possible... so to test this, we’ve just completed a fully operational, 40 foot high scale prototype!
We’re now seeking funding to build the 121 foot towers and to begin research. Click on Contribute to support this work.
Visit the Science link to find out more, and our Events link for upcoming public demonstrations.


WolfTrack
Logout
Akhil Kumar
Gender
Male
Location
Raleigh, NC
{% block content %}{% endblock %}
Harper Hillsborough
×
Comments
Send Email
Elliot Anderson
David Baker


API model information
An error that has occurred on the marketplace API
| Property | Required | Data Type | Description |
|---|---|---|---|
| ID | True | ErrorID | The ErrorID (string or int value acceptable) |
| ErrorCode | False | string | The error code you want sent to the seller |
| Message | False | string | The error message you want sent to the seller |
Use the JSON code below as an example of how this model will be serialized.
- {
- "ID": "ProductFailedDataValidation",
- "ErrorCode": "126",
- "Message": "HTML tags are not allowed in the product description field."
- }


OpenHiven.py
v.0.0.7
Introduction
A small Intro to OpenHiven.py
Quick Start
Contributing
Core Functionality
Class HivenClient
Websocket
Data Models
Attatchment
Deleted Message
Embed
House
Invite
Message
Private Group Room
Private Room
Room
User
OpenHiven.py
»
Index
Index
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
I
|
J
|
L
|
M
|
N
|
O
|
P
|
R
|
S
|
T
|
U
|
W
A
attatchment
author
B
bot
built-in function
create_invite()
create_room()
delete()
edit()
,
[1]
,
[2]
get_member()
leave()
mark_message_as_read()
send()
,
[1]
,
[2]
C
code
content
create_invite()
built-in function
create_room()
built-in function
created_at
D
deactivate_print_output() (openhivenpy.Client.HivenClient method)
delete()
built-in function
description
,
[1]
E
edit()
built-in function
,
[1]
,
[2]
edited_at
embed
emoji
F
filename
G
get_member()
built-in function
H
header
house
,
[1]
,
[2]
house_id
house_members
I
icon
,
[1]
id
,
[1]
,
[2]
,
[3]
,
[4]
,
[5]
image
J
joined_at
L
last_message_id
,
[1]
leave()
built-in function
location
M
mark_message_as_read()
built-in function
max_age
max_uses
media_url
members
mentions
message_id
N
name
,
[1]
,
[2]
,
[3]
,
[4]
O
openhivenpy.Client.HivenClient (built-in class)
owner_id
P
position
presence
R
raw
recipient
,
[1]
roles
room
room_id
S
send()
built-in function
,
[1]
,
[2]
T
title
type
U
url
,
[1]
user
,
[1]
username
users
W
website


c/g
Hello, my name is
Max Lukin
.
I'm a software engineer at
Facewatch
and CEO at
CustomGears
What I do:
— work as a full-stack developer with
Ruby on Rails
and
ReactJS
/
ReduxJS
— help startups grow, consult and support
— open for partnership based on great project ideas
Last blog posts
25 Oct 2015
Principles for Writing Maintainable Code
21 Oct 2015
How to install Ruby on Rails application on Ubuntu
15 Oct 2015
Our first post


|
Table 1
|
Inclusion and exclusion criteria considered in the selection ... |
|
Table 2
|
Characteristics of the materials included in the review. |
|
Table 3
|
Health Impacts of Urban Heat Island (UHI) on Outdoor Workers ... |
|
Table 4
|
Potential impact of climate change on occupational sectors b ... |


Learn the basics of Census 2020 data privacy, from noise injection to census blocks.
Learn about how the 2020 Census uses "noise" to protect the privacy of individuals' data, and how noise relates to accuracy at different geographic levels.
Visualize the privacy-accuracy tradeoff and understand the idea of the privacy loss budget in relation to noise.


|
||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
See:
Description
| Interface Summary | |
|---|---|
| FieldCache | Expert: Maintains caches of term values. |
| ScoreDocComparator | Expert: Compares two ScoreDoc objects for sorting. |
| Searchable | The interface for search implementations. |
| SortComparatorSource | Expert: returns a comparator for sorting ScoreDocs. |
| Weight | Expert: Calculate query weights and build query scorers. |
| Class Summary | |
|---|---|
| BooleanClause | A clause in a BooleanQuery. |
| BooleanQuery | A Query that matches documents matching boolean combinations of other
queries, typically TermQuery s or PhraseQuery s. |
| DefaultSimilarity | Expert: Default scoring implementation. |
| Explanation | Expert: Describes the score computation for document and query. |
| FieldCache.StringIndex | Expert: Stores term text values and document ordering data. |
| FieldDoc | Expert: A ScoreDoc which also contains information about how to sort the referenced document. |
| Filter | Abstract base class providing a mechanism to restrict searches to a subset of an index. |
| HitCollector | Lower-level search API. |
| Hits | A ranked list of documents, used to hold search results. |
| IndexSearcher | Implements search over a single IndexReader. |
| PhraseQuery | A Query that matches documents containing a particular sequence of terms. |
| Query | The abstract base class for queries. |
| ScoreDoc | Expert: Returned by low-level search implementations. |
| Scorer | Expert: Implements scoring for a class of queries. |
| Searcher | An abstract base class for search implementations. |
| Similarity | Expert: Scoring API. |
| Sort | Encapsulates sort criteria for returned hits. |
| SortComparator | Abstract base class for sorting hits returned by a Query. |
| SortField | Stores information about how to sort documents by terms in an individual field. |
| TermQuery | A Query that matches documents containing a term. |
| TopDocs | Expert: Returned by low-level search implementations. |
| TopFieldDocs | Expert: Returned by low-level sorted search implementations. |
| Exception Summary | |
|---|---|
| BooleanQuery.TooManyClauses | Thrown when an attempt is made to add more than BooleanQuery.getMaxClauseCount() clauses. |
Search over indices.
Applications usually call org.apache.lucene.search.Searcher#search(Query)
or org.apache.lucene.search.Searcher#search(Query,Filter)
.
|
||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |


Qt Quick Controls Overview
The Qt Quick Controls provide a set of UI controls to create user interfaces in Qt Quick.
Getting Started
The QML types can be imported into your application using the following import statement in your .qml
file.
import QtQuick.Controls 1.2
Creating a basic example
A basic example of a QML file that makes use of controls is shown here:
import QtQuick.Controls 1.2 ApplicationWindow { title: "My Application" width: 640 height: 480 visible: true Button { text: "Push Me" anchors.centerIn: parent } }
For an overview of the controls provided by Qt Quick Controls, you can look at the Gallery example.
Setting Up Controls from C++
Although we have traditionally used a QQuickView window to display QML files in a C++ application, doing this means you can only set window properties from C++.
With Qt Quick Controls, declare an ApplicationWindow as the root item of your application and launch it by using the QQmlApplicationEngine instead. This ensures that you can control top level window properties from QML.
A basic example of a source file that makes use of controls is shown here:
#include <QApplication> #include <QQmlApplicationEngine> int main(int argc, char *argv[]) { QApplication app(argc, argv); QQmlApplicationEngine engine("main.qml"); return app.exec(); }
Note: We are using QApplication and not QGuiApplication in this example. Though you can use QGuiApplication instead, doing this will eliminate platform-dependent styling. This is because it is relying on the widget module to provide the native look and feel.
Using C++ Data From QML
If you need to register a C++ class to use from QML, you can call, for example, qmlRegisterType() before declaring your QQmlApplicationEngine. You can find the list of all registering functions here.
If you need to expose data to QML components, you need to set them to the context of the current QML engine. See QQmlContext for more information.
Deploying Qt Quick Controls
Since Qt 5.2, the Qt Quick Controls JavaScript and QML files are embedded into the plugin using Qt resources (.qrc) for the QtQuick.Controls and QtQuick.Controls.Styles imports. It is only necessary to deploy the qtquickcontrolsplugin C++ library and its qmldir file found in the plugin directory qml/QtQuick/Controls.
The .js/.qml files are still placed into the plugin directory though for keeping the development tasks convenient, debugging and autocompletion capabilities remain unchanged. For deployment, these files can be ignored. In practice, the Styles and Private subfolders can be deleted as well as all .js and .qml files present under qml/QtQuick/Controls.
Note: On Windows, the Windows Deployment Tool only deploys the Qt Quick Controls plugin and its qmldir file.
Using resources facilitates the deployment of the Qt Quick Controls though it has limitations that still need to be addressed.
Note: On iOS, the qmlimportscanner tool is used to parse the required qml imports so they can be deployed accordingly. The files embedded in resources are not scanned by this tool though and when linking statically, some required imports used by the Qt Quick Controls can be forgotten. This is a known limitation and a workaround is to add potentially missing imports in one of the qml files of the application using the controls.
Testing Desktop and Mobile behavior of the controls
You can test how the controls on your application or style will behave on a mobile platform by setting the environment variable QT_QUICK_CONTROLS_MOBILE, to force a behavior optimized for mobile devices.


RASH RELIEF CLEAR - petrolatum and dimethicone liquid
Touchless Care Concepts LLC
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
- Do not use over deep or puncture wounds, infections, or lacerations. For external use only.
- When using this product do not get into eyes. If contact occurs, rinse eyes throughout with water.
- Stop use and ask a doctor if condition worsens or does not improve with 7 days.
- Change wet and soiled diapers promptly, cleanse the diaper area, and allow to dry.
- Shake bottle well before use.
- Spray 4-6 inches from skin. No rub-in is required.
- Apply liberally as often as necessary, with each diaper change, and especially at bedtime or anytime exposure to we diapers is prolonged.
Cyclomethicone, Hexamethyldisiloxane, Lanolin, Light Mineral Oil, Microcrystalline Wax, Vitamin A Palmitate, Vitamin D3, Water
|
RASH RELIEF CLEAR
petrolatum dimethicone liquid | ||||||||||||||||||||
| ||||||||||||||||||||
| ||||||||||||||||||||
| ||||||||||||||||||||
| ||||||||||||||||||||
|
| Labeler - Touchless Care Concepts LLC (083459334) |
| Registrant - Touchless Care Concepts LLC (083459334) |


Please wait while data is loaded and the visualization is prepared.
Yes, the stacked area is not a good candidate for this data. The visualization is very busy, and not much can be decerned from it.
None the less, I wanted to excerise the stacked area and compare the D3 and Google Charts approaches.


Hello there.
I am called Nixon.
I am an Engineer & a developer.
I like watching anime.
I code daily like a good boi.
I am called Nixon.
I am an Engineer & a developer.
I like watching anime.
I code daily like a good boi.
A 3rd year undergrad Civil Engineering
student who loves to code, design cool stuff
and learn new things.
I like coding, anime, food &
sleep, yeah in that order.
I also teach people how to <'code'>


Birth of the DMB/DS group
Image by palomaironique
First colloquium of the Data Management and Biometrics (aka Data Science?) group
A poem
-
roses are red
violets are blue
in surveillance capitalism
a poem reads you
and shows you ads
for flower shops
and tracks your clicks
and never stops
...
-<EMAIL_ADDRESS>Why?
1. To improve the service
2. To show targeted advertisements
Searsia
Query autocompletions considered harmful
Lawsuits over damaging autocompletions
- Lawsuit France (2010): "cnfdi arnaque"
- Lawsuit Italy (2011): "[name] truffatore"
- Lawsuit Germany (2012): "bettina wulff prostituierte"
- Lawsuit Japan (2012): a search shows crimes committed by a man with the same name...
- Google update (2013) filters offensive completions for person names.
Autocompletion Stereotypes
Query recommendations without tracking
Experiment:
Autocompletions from web content
anchor texts from the ClueWeb09 web crawl
Autocompletions from user data
query log by Pass et al. (2006)
G. Pass, A. Chowdhury and C. Torgeson (2006) A Picture of Search. In:
Proceedings of the 1st international conference on Scalable information systems (InfoScale), 1-7
Searsia
Query: master degree
Photo by: Pals - Krukkert, K.M.M. (M&C)
Targeted advertisements by Searsia
-
Based on the query, not on the person
-
Local (proxied) banners and images
-
No third party Javascript, Cookies, or web beacons
-
No HTTP referrer with query terms
Affiliate programs and networks
Connect to APIs of big affiliate programs (e.g. Amazon)
Local search in data from affiliate networks (e.g. ShareASale)
(Shows ads for charities if no results)
Conclusion
-
Federated Search
Query is forwarded to search engines in the federation.
-
Autocompletions; No tracking
Autocompletions based on anchor texts, not on people's queries.
-
Targeted ads; No tracking
Ads based on the search term, not on the person.
Thanks
/


{%extends "base.html" %} {%block title%} Register {%endblock%} {%block titleH1%}Register{%endblock%} {%block body%}


{% load static %}
Profile
Hi,
{{ user.username }}
Your Profile
Name
Email
Address
Password
Change Password
Save Changes
Change Password
Current Password
New Password
Confirm Password
Save Changes


Freighter Daisy:
??, ??, ?? -- my beloved siblings, all 3 of them, though they can be a handful! Ah well, I wouldn't trade them for their weight in gold. You know, it is very rare for the whole family to be posted to the same place, even within the same guild. We owe our good fortune to Uncle ???.
Family is so very important, don't you think.  You can use our warehouse freight service -- we deliver promptly even over long distances!
Private Warehouse
Clan Warehouse
Learn skills.
Ask about Skill Enchanting.
Quest


2.2 Library contents
The PSBLAS library consists of various classes of subroutines:
-
Computational routines
- comprising:
- Sparse matrix by dense matrix product;
- Sparse triangular systems solution for block diagonal matrices;
- Vector and matrix norms;
- Dense matrix sums;
- Dot products.
-
Communication routines
- handling halo and overlap communications;
-
Data management and auxiliary routines
- including:
- Parallel environment management
- Communication descriptors allocation;
- Dense and sparse matrix allocation;
- Dense and sparse matrix build and update;
- Sparse matrix and data distribution preprocessing.
-
Preconditioner routines
-
-
Iterative methods
- a subset of Krylov subspace iterative methods
The following naming scheme has been adopted for all the symbols internally defined in
the PSBLAS software package:
- all symbols (i.e. subroutine names, data types...) are prefixed by psb_
- all data type names are suffixed by _type
- all constants are suffixed by _
- all top-level subroutine names follow the rule psb_xxname where xx can be
either:
- ge: the routine is related to dense data,
- sp: the routine is related to sparse data,
- cd: the routine is related to communication descriptor (see 3).
For example the psb_geins, psb_spins and psb_cdins perform the same
action (see 6) on dense matrices, sparse matrices and communication
descriptors respectively. Interface overloading allows the usage of the same
subroutine names for both real and complex data.
In the description of the subroutines, arguments or argument entries are classified
as:
-
global
- For input arguments, the value must be the same on all processes
participating in the subroutine call; for output arguments the value is
guaranteed to be the same.
-
local
- Each process has its own value(s) independently.
To finish our general description, we define a version string with the constant
whose current value is 3.8.0


Coronation Street actor returns to Cobbles for fifth time as new character
The actor has played four other people throughout the years
by Sophie McCoidCoronation Street viewers recognised a familiar face this week, as an actor returned to Weatherfield for his fifth stint playing a new character.
Mark Chatterton is on his fifth stint and fourth role on the Cobbles after first appearing as Neville Hawthorne in a few episodes in 1986.
He returned for a run in 1992 and 1993 when he was cast as Gordon Blinkhorn, Raquel Wolstenholme’s admirer - reports Mirror Online.
And after a one-off appearance as Gerry Burton in 2003, he returned as Neville in 2005 and 2007.
But Corrie fans recognised the actor, as he appeared on screen playing his fourth character - pawn shop owner Barry Morgan.
Mark has also appeared in Emmerdale and Casualty as well as roles in The Cops and My Parents Are Aliens.
Several viewers recognised the actor straight away, while others wondered where they'd seen him before.
One fan said: “Classic Corrie guest star alert! That was Raquel’s ex-boyfriend Gordon-slash-Norris’s son in law Neville — actor Mark Chatterton — as the pawn shop owner.”
Another said: “He's been in Corrie on and off for years. So funny to see him reappear in yet another guise!”
And fans were very grateful to vigilant Corrie lovers for reminding them why Chatterton’s face was so familiar.
But this is not the first time Coronation Street devotees have noticed reoccurring actors on the soap.

The actress, played by actress Olwen May had been in the ITV soap before, filming alongside Carla and Peter in 2011 after her harrowing rape ordeal at the hands of evil ex Frank Foster.
But in this era, she played a different character and portrayed the role of DC Joyce Malone who was leading the investigation into the allegations against Frank.
This wasn’t the only character Olwen has played on the ITV soap though, with the actress having been on the show in a whopping five different roles.
Before her stint in 2011, the actress played Jessica Lundy in 1999 and 2000.
In this stint she was a reverend, and she married Hayley and Roy Cropper.
Prior to this, Olwen played another detective on the soap, portraying DC Chapman in 1991.
Finally, her other role in the soap was in 1990, when she played a character named Christine Woods who was a recruitment agent.


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Vitamin D is essential for healthy bones, and a lack of it can lead to health problems, including cardiovascular disease. Explore the places to get enough sun for soul and body.
Current Temperature 18°C
Boa tarde! Some clouds but mostly sunny!Lisbon is Portugal’s
hilly, coastal capital city. From imposing São Jorge Castle,
the view encompasses the old city’s pastel-colored buildings,
Tagus Estuary and Ponte 25 de Abril suspension bridge. Nearby,
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beaches, from Cascais to Estoril.
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Rome, Italy’s capital, is a
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Ancient ruins such as the Forum and the Colosseum evoke the
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Without ASLR in the mix, Ret2LibC is quite a bit easier. Offsets are no longer needed, so only the actual address of LibC SYSTEM, EXIT, and /bin/sh are needed.
These can be calculated pretty much the same way as with ASLR.
Finding LibC SYSTEM:
While debugging the program with gdb and peda:
(gdb) p system
This will output the address similar to
$1 = {<text variable, no debug info>} 0xf7e4c060 <system>
Finding LibC EXIT:
While debugging the program with gdb and peda:
(gdb) p exit
This will output the address similar to
$2 = {<text variable, no debug info>} 0xf7e3faf0 <exit>
Finding LibC /bin/sh:
While debugging the program with gdb and peda:
(gdb) find &system,+99999999,"sh"
This is using gdb find, so you have to have a start and end address and then the search string "sh"


{% extends 'base.html' %} {% block content %} {{super()}}
Hi [redacted for privacy], I saw your post in [private Facebook group] a while back asking for pitches for the Ideas Section of Quartz. Here’s a pitch for you to consider. Voters are creating an election echo chamber Voters today are embracing presidential candidates who appeal to their specific passions and ideals much like they only trust news sources that align with their ideological views. Our ability to self-select our newsfeed via Facebook, Twitter and even whether our main source of news is MSNBC or Fox News is creating an echo chamber for voters. As a result, the only news voters get about their candidate is favorable and the news about the candidates they don’t like is always negative. This piece would focus on how voters are no longer receiving balanced (and, in some cases, accurate) news about election candidates. This is not because the media is biased but because voters have an unprecedented ability to self-select the news they receive. This article that would include interviews with: Tom Rosenstiel, executive director of API and former director of the Project for Excellence in Journalism at the Pew Research Center in Washington, D.C. Carroll Doherty, director of political research at Pew Research Center My articles have appeared in Fast Company, Men’s Journal and Daily Worth. Please let me know if I can provide you any additional information or clips, or if you have any feedback for me. Thanks.


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Syntax:
symbol-function symbol => contents
(setf (symbol-function symbol) new-contents)
Arguments and Values:
symbol---a symbol.
contents--- If the symbol is globally defined as a macro or a special operator, an object of implementation-dependent nature and identity is returned. If the symbol is not globally defined as either a macro or a special operator, and if the symbol is fbound, a function object is returned.
new-contents---a function.
Description:
Accesses the symbol's function cell.
Examples:
(symbol-function 'car) => #<FUNCTION CAR> (symbol-function 'twice) is an error ;because TWICE isn't defined. (defun twice (n) (* n 2)) => TWICE (symbol-function 'twice) => #<FUNCTION TWICE> (list (twice 3) (funcall (function twice) 3) (funcall (symbol-function 'twice) 3)) => (6 6 6) (flet ((twice (x) (list x x))) (list (twice 3) (funcall (function twice) 3) (funcall (symbol-function 'twice) 3))) => ((3 3) (3 3) 6) (setf (symbol-function 'twice) #'(lambda (x) (list x x))) => #<FUNCTION anonymous> (list (twice 3) (funcall (function twice) 3) (funcall (symbol-function 'twice) 3)) => ((3 3) (3 3) (3 3)) (fboundp 'defun) => true (symbol-function 'defun) => implementation-dependent (functionp (symbol-function 'defun)) => implementation-dependent (defun symbol-function-or-nil (symbol) (if (and (fboundp symbol) (not (macro-function symbol)) (not (special-operator-p symbol))) (symbol-function symbol) nil)) => SYMBOL-FUNCTION-OR-NIL (symbol-function-or-nil 'car) => #<FUNCTION CAR> (symbol-function-or-nil 'defun) => NIL
Side Effects: None.
Affected By:
Exceptional Situations:
Should signal an error of type type-error if symbol is not a symbol.
Should signal undefined-function if symbol is not fbound and an attempt is made to read its definition. (No such error is signaled on an attempt to write its definition.)
See Also:
fboundp, fmakunbound, macro-function, special-operator-p
Notes:
symbol-function cannot access the value of a lexical function name produced by flet or labels; it can access only the global function value.
setf may be used with symbol-function to replace a global function definition when the symbol's function definition does not represent a special operator.
(symbol-function symbol) == (fdefinition symbol)However, fdefinition accepts arguments other than just symbols.


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/expr.html ---
Does anyone know the behaviour of meta constant expr.replace : expr → (expr → nat → option expr) → expr
?
(I have an expression that has a single mvar
somewhere in it; I would like to replace that with an expr.var 0
.)
You could try implementing it as e.replace $ λ e' _, if e'.is_mvar then expr.var 0 else none
It might not work if replace
does not proceed recursively but your attempt should help us decide what to do next.
you should probably use the n
variable though
e.replace $ λ e' n, if e'.is_mvar then expr.var n else none
Ooooooh! Is that what it's for? That's so cool!
Neat!
Do you guys have an expr.is_mvar
that I'm missing?
no, looks like you will have to roll your own
I thought it was in mathlib
Ah! In tactic.basic
, there it is called is_meta_var
Thanks.
should we be more regular in the naming there?
Probably, yes
Is there any documentation anywhere on what all the constructors to expr
mean?
Not that I know of. It would be worth writing. What do you want to know?
I would love to have a paragraph on each. I have to re-remember the order of arguments to expr.pi every time I see it.
Essentially what Scott's talking about. What each of the arguments to each constructor represents.
Didn't Ed Ayers write this at some point? He had a draft of some docs on meta stuff, but I think it was never PR'd.
Are expr tt
s allowed to contain metavariables?
yes
as far as I understand, expr tt
means that the expression has been typechecked and fully elaborated.
meta inductive expr (elaborated : bool := tt) /- A bound variable with a de-Bruijn index. -/ | var {} : nat → expr /- A type universe: `Sort u` -/ | sort {} : level → expr /- A global constant. These include definitions, constants and inductive type stuff present in the environment as well as hard-coded definitions. -/ | const {} : name → list level → expr /- [WARNING] Do not trust the types for `mvar` and `local_const`, they are sometimes dummy values. Use `tactic.infer_type` instead. -/ /- An `mvar` is a 'hole' yet to be filled in by the elaborator or tactic state. -/ | mvar (pretty : name) (unique : name) (type : expr) : expr /- A local constant. For example, if our tactic state was `h : P ⊢ Q`, `h` would be a local constant. -/ | local_const (pretty : name) (unique : name) (bi : binder_info) (type : expr) : expr /- Function application. -/ | app : expr → expr → expr /- Lambda abstraction. eg ```(λ a : α, x)`` -/ | lam (var_name : name) (bi : binder_info) (var_type : expr) (body : expr) : expr /- Pi type constructor. eg ```(Π a : α, x)`` and ```(α → β)`` -/ | pi (var_name : name) (bi : binder_info) (var_type : expr) (body : expr) : expr /- An explicit let binding.-/ | elet (var_name : name) (type : expr) (assignment : expr) (body : expr) : expr /- A macro, see the docstring for `macro_def`. The list of expressions are local constants and metavariables that the macro depends on. -/ | macro : macro_def → list expr → expr
@Scott Morrison yeah I should PR it at some point.
I build Lean from source with extra docstrings.
binder_info
is only used by the elaborator.
Thanks for this.
What does tactic.generalize
do?
If you have ⊢ x + 1 ≤ y + 2
, generalize ``(y + 2) `z
will turn the goal into ⊢ x + 1 ≤ z
Okay thanks.
The interactive version offers more options like adding an assumption h : y + 2 = z
@Edward Ayers An expr tt
may not actually have been typechecked, but it is presumed to at least have the structure to be typechecked
Ok so does expr tt
just mean that there are no placeholders?
Well, technically yes since "placeholder" is the name used for the macro that represents the _
syntactical form. But both expr ff
and expr tt
can have metavariables.
The big difference between expr ff
and expr tt
is whether implicit arguments are present. For example the equality x = x
is represented in expr ff
as app (app (const `eq _) x) x
while in expr tt
it is represented as app (app (app (const `eq _) t) x) x
(one more argument).
What is the difference between implicit
and strict_implicit
?
For binder_info
default
= (x : α)
, implicit
= {x : α}
, strict_implicit
= ⦃x : α⦄
, inst_implicit
= [x : α]
, I believe aux_decl
is used as a tag for the _match
hypotheses but I could be completely mistaken.
The difference between {}
and ⦃⦄
is how implicit arguments are treated that are not followed by explicit arguments. {}
arguments are applied eagerly, while ⦃⦄
arguments are left partially applied:
def foo {x : ℕ} : ℕ := x def bar ⦃x : ℕ⦄ : ℕ := x #check foo -- foo : ℕ #check bar -- bar : Π ⦃x : ℕ⦄, ℕ
In C++ it says that aux_decl
is "used to mark local constants representing recursive functions
in recursive equations and match
statements."
aux_decl
is used for _match
, _fun_match
, _let_match
and the self reference that appears in recursive pattern matching
these are not real local constants, but rather trigger recursive compilation when used
If pexpr
and expr
are more or less the exact same inductive type how are they different? Is it just because in practice we never define them from constructors ourselves and always use the inbuilt functions which treat pexpr
and expr
differently even though the type doesn't force them to?
As Gabriel said above, the same term is represented differently as an pexpr
than as an expr
. Moreover, for both structures there are some constants such as expr.mk_sorry
, pexpr.mk_placeholder
and pexpr.mk_explicit
which only exist in one of the two variants, but not the other. These are not represented by the inductive structure. But mk_placeholder
and mk_explicit
will be used (for example) by the tactic to_expr
.
Is there an easy way of printing an expr
in terms of the constructors of expr
?
expr.to_raw_fmt
Thanks
If I'm writing a tactic and I have e : expr
, which is a proof of equality, how would I do rw e at *
say, or simp [e] at *
as part of a tactic?
You can rw
another arbitrary expr
using rewrite_core
. I would have to read the tactic.interactive.rw
definition to see how it replaces local hypotheses, too, but that's the idea.
For simp
you need to call mk_simp_set
and then add your lemma to it. Then you need to pass that data to the built-in function tactic.simplify
.
often a cheap way to do these sorts of things is using tactic quotations, e.g. `[simp at *]
I'm guessing you can use antiquotations, and write something like `[simp [%%e] at *]
.
Last updated: Apr 24 2020 at 19:02 UTC


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--- layout: post title: Heap queue tagline: " algorithm dissection" permalink: /python/stdlib/heapq.html categories: [emacs, Python, algorithms, heap, literate programming] tags: [heap queue, stdlib, heapq] ---
Priority Queue
Implements a set
S
of elements, each of elements associated with a key.
S
S
with a largest keyS
Figure 1: Max-heap
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|---|---|---|---|---|---|---|---|---|
| 100 | 19 | 36 | 17 | 3 | 25 | 1 | 2 | 7 |
The key of a node >= the keys of its childen
produces a max heap from an unsorted array
correct a single violation of the heap property in a subtree's root
Elements A[n/2+1 … n] are all leaves O(nlgn) simple analysis
Observe:
max_heapify
takes O(1) for nodes that are one level above the leaves and in general O(l) time for nodes that are l levels above the leaves
Wikipedia article
Heapq.heapyfy(x)
ransform list x into a heap, in-place, in linear time
The heap is an integral component in many algorithms — a data structure that keeps elements organised so that it is always easy to find the smallest value. We'll show you how you can use the heapq module to implement heaps in Python in just a few lines of code.
Lets take an attempt to disclose much unique and useful heapq features.
from heapq import heapify h1 = [-1, 3, 5, 7, 9, 2, 4, 6, 8, 0] heapify(h1) print(h1)
>>> >>> >>> [-1, 0, 2, 6, 3, 5, 4, 7, 8, 9]
h2 = [-2.2, 3.8, 1.1, -5] heapify(h2) print(h2)
>>> [-5, -2.2, 1.1, 3.8]
h3 = ['f', 'd', 'q', 'g', 'b'] heapify(h3) print(h3)
>>> ['b', 'd', 'q', 'g', 'f']
h4 = ['break', 'border', 'backer', 'bachelor', 'baccara'] heapify(h4) print(h4)
>>> ['baccara', 'bachelor', 'backer', 'break', 'border']
The latter output looks a bit odd, but it's a heap
by
its definition (!)
In the same manner, nlargest
& nsmallest
wouldn't work as expected:
from heapq import nlargest, nsmallest, heappush print(nlargest(3, h4)) # for clarity heappush(h4, 'baby') print(h4) print('\n') print(nsmallest(3, h4))
>>> ['break', 'border', 'backer'] ... >>> ['baby', 'bachelor', 'baccara', 'break', 'border', 'backer'] ['baby', 'baccara', 'bachelor']
Seems like nlargest
return the largest values in a descendant order,
but nsmallest
do it in a rising one.
from heapq import heappop h = [] heappush(h, (5, 'write code')) heappush(h, (7, 'release product')) heappush(h, (1, 'write spec')) heappush(h, (3, 'create tests')) print(type(h),'\n', h) heappop(h)
>>> >>> >>> >>> >>> >>> >>> <class 'list'> [(1, 'write spec'), (3, 'create tests'), (5, 'write code'), (7, 'release product')] (1, 'write spec')
As you might recon a heap in this particular case is a specific list, which is sorted on the fly.
heappush(h, (6, 'test it up')) print('\n', h)
[(3, 'create tests'), (6, 'test it up'), (5, 'write code'), (7, 'release product')]
Obviously that order is corrupted, but it is strictly following by the
heap
definition.
heappop(h) print('\n', h) heappop(h)
(3, 'create tests') [(5, 'write code'), (6, 'test it up'), (7, 'release product')] (5, 'write code')
From StackOverflow
If you use binary heap to pop all elements in order, the thing you do is basically heapsort. It is slower than sort algorightm in sorted function apart from it's implementation is pure python.
The heapq is faster than sorted in case if you need to add elements on the fly i.e. additions and insertions could come in unspecified order. Adding new element preserving inner order in any heap is faster than resorting array after each insertion.
The sorted is faster if you will need to retrieve all elements in order later.
The only problem where they can compete - if you need some portion of smallest (or largest) elements from collection. Although there are special algorigthms for that case, whether heapq or sorted will be faster here depends on the size of the initial array and portion you'll need to extract.
Lets compare how fast they are work
Comparison Task: We have a large list of integers which is appended 1000 times with a single value during each iteration. Try to extract 10 smallest values out of it after every modification. Compare the execution time
Lets create a random sequence of integers
from random import randint numbers = [randint(0,10000) for i in range(100)]
Comparison between heapq
and sort
Lets create a function to detect minimum values in the data-set:
def min_10_values_by_native_sort(l): l.sort() return l[:10]
And using heapq
module
from heapq import nsmallest, heapify def min_10_values_in_the_heap(h): heapify(h) return nsmallest(10, h)
Now it's time to evaluate with this data-set:
def time_complexity_analysis(n, l, f): result = [] for i in range(n): l.append(randint(0,100)) result.append(f(l)) return result[-1]
i = time(); time_complexity_analysis(10, numbers, min_10_values_by_native_sort); print(time()-i) i = time(); time_complexity_analysis(10, numbers, min_10_values_in_the_heap); print(time()-i)
[24, 29, 30, 34, 52, 54, 64, 65, 72, 93] 0.00017976760864257812 [1, 5, 24, 25, 27, 29, 30, 34, 41, 50] 0.0005156993865966797
Obviously that heapq
module works 4 time slowly than a native sort.
But try to elaborate our algorithm:
heapify
initial data-set onceheappush
new values into it many timesnsmallest
after each modification
Lets restrict our algorithm to heapify
the data array only once.
def custom_heap_algorithm(n, h): """h is a preliminarily prepared heap""" result = [] for i in range(n): heappush(h, randint(0, 100)) result.append(nsmallest(10, h)) return result[-1]
i = time(); time_complexity_analysis(10, numbers, min_10_values_by_native_sort); print(time()-i) i = time(); heapify(numbers); custom_heap_algorithm(10, numbers); print(time()-i)
[1, 1, 5, 19, 23, 24, 25, 27, 29, 30] 0.0001804828643798828 [1, 1, 2, 5, 8, 14, 18, 19, 23, 24] 0.00045680999755859375
i = time(); time_complexity_analysis(10**3, numbers, min_10_values_by_native_sort); print(time()-i) i = time(); heapify(numbers); custom_heap_algorithm(10**3, numbers); print(time()-i)
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0] 0.02643871307373047 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] 0.2994558811187744


Mungebits2 defines a way of thinking about data preparation that couples the definition of what happens in batch processing versus online prediction so that both can be described by the same codebase.
For example, consider the simple example of imputation. While the general concept of imputing a variable works on arbitrary codebases, a separate data transformation will have to be defined for each model that uses imputation in a production setting. This is because the imputed value depends inherently on the dataset. We must remember the mean of the data set encountered during training, and recall this value when performing replacement in a production setting.
Mungebits provide a sort of "train track switch" that allows one to write data preparation offline, but ensure it works online (on a stream of new data, such as one-row data.frames).
By reframing data preparation as the process of constructing a "munge procedure", a list of trained mungebits that can reproduce the same mathematical operation on a dataset in a production environment without additional code, the process of productionizing a machine learning model should become significantly simplified.


{% extends "base.html" %} {% block title %} University Timetable {% endblock title %} {% block body %}
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[dscrdeql] <Cryptoon> AndronicusBass-Founder - vandaag om 12:41
@Cryptoon are you thinking that the outside area may be inefficient or some interior space that may be un useable?
[dscrdeql] <Cryptoon> Thinking mostly interior/exterior, as in the height the space can't be used optimally given the arches?
[dscrdeql] <Cryptoon> But don't get me wrong, domes are great for nature resistant homes
[dscrdeql] <MySoulisNotForSale> come on rains
[dscrdeql] <MySoulisNotForSale>
[dscrdeql] <DaylightHours> Good morning
[dscrdeql] <jellysmash> you just got to work huh
[dscrdeql] <DaylightHours> My eql friends
[dscrdeql] <jellysmash> hope it goes alright for you
[dscrdeql] <jellysmash> I'm home now...just over indulged in dinner
[dscrdeql] <jellysmash> feeling very full
[dscrdeql] <jellysmash> it's a good feeling
[dscrdeql] <jellysmash> brown rice, slow cooked chicken with spices and potato...not to bad
[dscrdeql] <jellysmash> hey @donaldmathers
[dscrdeql] <jellysmash> I feel a sense of joy and possiblity when i walk out the door of work to go home
[dscrdeql] <jellysmash> when i walk out of the building and it's cold and dark...it's hard to feel that
[dscrdeql] <jellysmash> when I walk out in sprint summer and it's warm and still day light...arrrrhhhhhhh....life is good
[dscrdeql] <jellysmash> I'm a morning and summer person at heart
[dscrdeql] <x2maano> GOOD
[dscrdeql] <x2maano>
[dscrdeql] <donaldmathers>
[dscrdeql] <edsky> Anyone watched black mirror I regret watching 1st episode..... i seen things I can’t unsee
[dscrdeql] <AndronicusBass-Founder> Blackmirror = todays Goosebumps hahaha
[dscrdeql] <x2maano> HOW IS IT?
[dscrdeql] <CombatWombat> never heard of black mirror
[dscrdeql] <CombatWombat> worth a watch?
[dscrdeql] <edsky> Hahaha I’ve told it really good so I’ll keep watching
[dscrdeql] <edsky> @CombatWombat based on 1st ep can’t recommend but have been told it’s very good
[dscrdeql] <SwimedDragon> What's it about?
[dscrdeql] <CombatWombat> haha well watch some more and let us know the verdict
[dscrdeql] <edsky> I believe no really story line just random stories each ep
[dscrdeql] <jellysmash> I liked goosbumps ...the movie
[dscrdeql] <edsky> First ep involved a prime minister and a pig I’ll let you imagination do the rest
[dscrdeql] <jellysmash> so is black mirror like watching that?
[dscrdeql] <jellysmash> of stories like teh goosebumps books?
[dscrdeql] <edsky> It’s different thats for sure
[dscrdeql] <CombatWombat> congrats on level up
[dscrdeql] <jellysmash> looks like you leveled up @edsky
[dscrdeql] <jellysmash> nice
[dscrdeql] <edsky> Thx mate
[dscrdeql] <jellysmash> you're a novice in the making
[dscrdeql] <jellysmash> that's after level 15 i believe
[dscrdeql] <edsky> Man it’s good chatting in here
[dscrdeql] <jellysmash> cool...so many nice people hanging out here
[dscrdeql] <edsky> Yeah and many diverse conversations
[dscrdeql] <CombatWombat> :EQLI:
[dscrdeql] <AndronicusBass-Founder> Keeping it real, that's for sure
[dscrdeql] <x2maano>
[dscrdeql] <x2maano> tea time
[dscrdeql] <AndronicusBass-Founder> That emoticon always reminds me of matcha green tea
[dscrdeql] <AndronicusBass-Founder> acquired taste, not bad after a few sips


Orochi Framework
Detecting Orochi Native...
Accelerometer
Accelerometer Readings:
Compass
Compass Readings:
Media
Network
Notification
by Ronald Tsang
<EMAIL_ADDRESS>ronaldtsang@orochis-den.com


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java.lang.Object org.apache.xalan.transformer.TransformSnapshotImpl
class TransformSnapshotImpl
This class holds a "snapshot" of it's current transformer state, which can later be restored. This only saves state which can change over the course of the side-effect-free (i.e. no extensions that call setURIResolver, etc.).
| Field Summary | |
|---|---|
private java.util.Stack |
m_attrSetStack
Deprecated. Stack for the purposes of flagging infinite recursion with attribute sets. |
private java.util.Stack |
m_axesIteratorStack
Deprecated. Stack of AxesIterators. |
private DTMIterator |
m_contextNodeList
Deprecated. The current context node list. |
private java.util.Stack |
m_contextNodeLists
Deprecated. The current context node lists stack. |
private CountersTable |
m_countersTable
Deprecated. The table of counters for xsl:number support. |
private IntStack |
m_currentExpressionNodes
Deprecated. A stack of the current sub-expression nodes. |
private NodeVector |
m_currentMatchNodes
Deprecated. A node vector used as a stack to track the current ElemTemplate that was matched, as well as the node that was matched. |
private java.util.Stack |
m_currentMatchTemplates
Deprecated. A node vector used as a stack to track the current ElemTemplate that was matched, as well as the node that was matched. |
private IntStack |
m_currentNodes
Deprecated. The stack of current node objects. |
private ObjectStack |
m_currentTemplateElements
Deprecated. A node vector used as a stack to track the current ElemTemplateElement. |
private BoolStack |
m_currentTemplateRuleIsNull
Deprecated. Is > 0 when we're processing a for-each. |
(package private) boolean |
m_nsContextPushed
Deprecated. Indicate whether a namespace context was pushed |
private NamespaceMappings |
m_nsSupport
Deprecated. Use the SAX2 helper class to track result namespaces. |
private VariableStack |
m_variableStacks
Deprecated. The stack of Variable stack frames. |
| Constructor Summary | |
|---|---|
TransformSnapshotImpl(TransformerImpl transformer)
Deprecated. It doesn't look like this code, which is for tooling, has functioned propery for a while, so it doesn't look like it is being used. |
| Method Summary | |
|---|---|
(package private) void |
apply(TransformerImpl transformer)
Deprecated. It doesn't look like this code, which is for tooling, has functioned propery for a while, so it doesn't look like it is being used. |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
private VariableStack m_variableStacks
private IntStack m_currentNodes
private IntStack m_currentExpressionNodes
private java.util.Stack m_contextNodeLists
private DTMIterator m_contextNodeList
private java.util.Stack m_axesIteratorStack
private BoolStack m_currentTemplateRuleIsNull
private ObjectStack m_currentTemplateElements
private java.util.Stack m_currentMatchTemplates
private NodeVector m_currentMatchNodes
private CountersTable m_countersTable
ElemNumber
private java.util.Stack m_attrSetStack
boolean m_nsContextPushed
private NamespaceMappings m_nsSupport
| Constructor Detail |
|---|
TransformSnapshotImpl(TransformerImpl transformer)
transformer
- Non null transformer instance| Method Detail |
|---|
void apply(TransformerImpl transformer)
transformer
- Non null transformer instance
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Photo: Joe Burrow Had A Special Guest At LSU’s Game Last Night
by Andrew HolleranJoe Burrow and the LSU Tigers continued their perfect season on Saturday night, dominating Arkansas at Tiger Stadium, 56-20, to move to 11-0 on the season. Burrow was his usual great self, throwing for 327 yards and three touchdowns on 23 of 28 passing.
The former Ohio State quarterback, who transferred to LSU two years ago, had a special guest in attendance on Saturday night.
J.T. Barrett, who played with Burrow at Ohio State, was at Tiger Stadium supporting his former teammate. He was at the game with another former Buckeyes quarterback, Stephen Collier.
The former Ohio State star QB was wearing a Burrow No. 9 LSU jersey.
Burrow remains close with several of his former Ohio State teammates. The Buckeyes have definitely been rooting for Burrow and the Tigers this season.
The rooting could stop soon, though.
Ohio State and LSU are both favorites to make the College Football Playoff right now. The Buckeyes and the Tigers could meet in the national title game in New Orleans at the end of the season.
Barrett will have to change his jersey for that one.


Ingredients
- 250g Plain Flour
- 135g Butter
- 400g Golden Syrup
- 150g Breadcrumbs
- Zest of 2 Lemons
- 1 beaten Eggs
Recipe
First make the short crust pastry: measure the flour into a large bowl and rub in the butter with your fingertips until the mixture resembles fine breadcrumbs (alternatively, this can be done in a food processor). Add about three tablespoons of cold water and mix to a firm dough, wrap in cling film and chill in the fridge for about 20 minutes. Preheat the oven to 200C/400F/Gas 6 and put a heavy baking tray in the oven to heat up. Grease a deep 18cm/7in loose-bottomed fluted flan tin with butter. Remove about 150g/5½oz of pastry from the main ball and set aside for the lattice top. Roll the rest of the pastry out thinly on a lightly floured work surface and line the prepared flan tin with the pastry. Prick the base with a fork, to stop the base rising up during baking. Place the reserved pastry for the lattice top on cling film and roll out thinly. Egg wash the pastry and set aside to chill in the fridge (the cling film makes it easier to move about). Do not cut into strips at this stage. Do not egg wash the strips once they are on the tart as it will drip into the treacle mixture. To make the filling, heat the syrup gently in a large pan but do not boil. Once melted, add the breadcrumbs, lemon juice and zest to the syrup. (You can add less lemon if you would prefer less citrus taste.) If the mixture looks runny, add a few more breadcrumbs. Pour the syrup mixture into the lined tin and level the surface. Remove the reserved pastry from the fridge and cut into long strips, 1cm/½in wide. Make sure they are all longer than the edges of the tart tin. Egg wash the edge of the pastry in the tin, and start to make the woven laying lattice pattern over the mixture, leave the strips hanging over the edge of the tin. Once the lattice is in place, use the tin edge to cut off the strips by pressing down with your hands, creating a neat finish. Bake on the pre-heated baking tray in the hot oven for about 10 minutes until the pastry has started to colour, and then reduce the oven temperature to 180C/350F/Gas 4. If at this stage the lattice seems to be getting too dark brown, cover the tart with tin foil. Bake for a further 25-30 minutes until the pastry is golden-brown and the filling set. Remove the tart from the oven and leave to firm up in the tin. Serve warm or cold.


grafana-cli
A small executable that is bundled with Grafana serve.
More information: home page
- Install, update, or remove specific plugins:
grafana-cli plugins install|update|remove plugin_id1 plugin_id2 ...
- List all installed plugins:
grafana-cli plugins ls