Cinema Uprising by Steve Evans
Dogma Written and directed by: Kevin Smith. Starring Linda Fiorentino, Matt Damon, Ben Affleck, Chris Rock, Alan Rickman, George Carlin, Salma Hayek, Jason Mewes, Alanis Morisette, Smith and assorted surprise cameos.
The pitch: a woman suffering a crisis of faith must stop two fallen angels from sneaking back into Heaven and thereby negating existence in this ribald, raunchy and occasionally provocative satire of Roman Catholicism by the director of Clerks.
By turns gleefully offensive, juvenile and, yes, even brilliant, this edgy comic parable doesn't deserve the hail of criticism raining from some (non-official) segments of the Catholic Church. A contingent of bishops, meanwhile, is calling for a boycott. Verily, film fans, here is the gospel: those who lose or even doubt their faith after seeing this film didn't have a strong grasp on it to begin with. The director is clearly a religious man, if not a devout Catholic in the traditional sense. And he knows the Bible better than some of his critics. His intent here is to question the machinations and politics of the church, not the underlying principles of faith that members embrace for meaning in their lives. And Smith doesn't push as far as he could have gone: his camera never even enters a sanctuary. No blasphemy has been committed here, although the picture is assuredly not for all tastes. Perhaps the greatest offense, though, comes from people who would condemn Dogma without seeing it. We can't do anything about that, since willful ignorance and hypocrisy are not crimes in this country. Then again, neither is blasphemy. Smith's great success is he removes religion from the holier-than-thou hands of official church spokesmen and turns possession over to the clumsy and imperfect people who must live in this world.
Fiorentino stars as Bethany, a world-weary worker at an abortion clinic. One of the movie's quiet ironies is Bethany's infertility. Alone in bed, she receives a message from God in the form of a fireball that turns into Alan Rickman (recall the terrorist leader in Die Hard). The sensible Bethany blasts a fire extinguisher at the intruder, then threatens to crown him with a baseball bat. She cools off when Rickman unfurls his wings and tells her to settle down. Affecting a fey English accent, he explains that Bethany must stop a pair of fallen angels (Damon and Affleck) from passing beneath the archway of a renovated church in New Jersey. These wicked angels once were God's messengers of doom – the fiery Old Testament stuff - but they fell from Her favor and She banished them to…Wisconsin. Eager to regain entrance to the Kingdom of Heaven after spending millennia in the land of cheese, they discover a loophole in Catholic dogma. If Damon and Affleck walk through the church in Jersey, they may have a plenary indulgence – what Catholics call instant forgiveness for all sins – which entitles direct admission into Heaven. Problem is, that would show God is fallible. And that would trigger an outcome worse than the apocalypse - all would cease to exist.
The cardinal of the church (George Carlin, having a blast) plans to rededicate his sanctuary to God with a new marketing campaign endorsed by the Vatican – Catholicism Wow! At a press conference, Carlin unveils a statue of the Buddy Christ, a grinning, winking figure with a prominent thumbs up. Buddy is a new totem for a new generation bored with the traditional symbols and rituals of the church (The posture of Buddy Christ also bears passing resemblance to Mr. Natural, the brain-addled philosopher in Robert Crumb's underground comics. That, if anything, might rankle the devout, assuming they are hip to the subreference).
Back in Wisconsin, Damon enjoys toying with the fragile faithful.  Soon the poor sister heads off in search of a one-night stand and fashionable clothing. Damon and Affleck snicker at their mischief.
Bethany seems a strange choice to stop a pair of rotten angels. She is a reluctant hero, preferring to tithe her salary from Planned Parenthood to the church. Only when her life is saved by two unlikely prophets, Jay and Silent Bob (Mewes and director Smith), does she believe in the urgency of her mission. Jay and Silent Bob are recurring characters in all of the director's films. Jay is coarse and chatty, a stoner with a sharp, foul tongue who cannot conceal his basic cluelessness. And he damn-near steals the film. As Silent Bob, Smith has three words of dialogue in the entire picture, but his range of facial expressions can bring down the house. They hook up with Bethany after she is attacked outside the abortion clinic by three teenage demons wielding hockey sticks. After Jay and Silent Bob dispatch the thugs, Bethany wants to know why they're hanging around an abortion clinic.
`We thought it would be a good place to meet loose women,' Jay declares.
Together, this triumvirate is joined by Rufus, the 13th apostle (Chris Rock) who literally falls from the sky to help them.
Rufus says his role was left out of the Bible because he's black. He also claims Jesus once told him the meaning of life during a wedding reception in Cana, `but I got drunk and forgot it.'
They meet a stripper-muse (the delectable Hayek). She claims to be the inspiration for 19 of the 20 top-grossing movies of all time. But she won't take credit for Home Alone.
`Someone sold their soul to Satan to get the grosses up on that piece of crap,' she declares.
Extending the metaphor, the heroes are soon attacked by an excrement demon that rises from a toilet and, well…what's a Kevin Smith movie without a little potty humor?
While Bethany and her holy helpers ponder how to fight the demon, Damon and Affleck make their way across the country, spreading murder and mayhem. The fallen angels crash a board meeting of The Mooby Corporation, a company clearly modeled after Disney (which passed on distributing this film, fearing the ensuing controversy). Damon berates the board members.
Well, we get the idea.
Smith's screenplay is crammed with pop-cultural references, both sly and obvious, from Star Wars characters to ancient commercials for floor wax. At times, we wonder if he might be trying too hard, especially during the longish second hour when each character gets to deliver a speech (sermon?) that earnestly explains the importance of faith – regardless of religious denominations.
The director also wobbles at the climax, when Affleck and Damon lay waste to a city block surrounding the church. These and other scenes of jarring violence seem out of place in a comedy. The bloodshed throws off the tone of the film – illustrating once again that, as with most art forms, less is more. When the point is made, move on.
Perhaps Smith is struggling to maintain his momentum. Maybe he'll sustain that high note in his next film. But in Dogma, after soaring completely over the top with two hours of anarchic excess, he literally ends with a squeak when Alanis Morisette arrives for her cameo as God. Morisette may be an impassioned vocalist, but she's no actor. And a movie that wants to push the satirical limit needs a climax that packs an ungodly wallop and an almighty bang, not the thespian exertions of a rank amateur.
Rated R for constant foul language, scatological humor, brief (but potent) violence.
Cinema Uprising copyright C 1999 by Stephen B. Evans. All rights reserved. This work may not be reproduced or transmitted in any form, by any means, without the prior, written permission of the author. The author may be contacted at<EMAIL_ADDRESS>The review above was posted to the
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Welcome to our beauty blog!
We post new beauty, fashion, and inspirational blog posts every week! Be sure to visit our page every monday.
The mission of our website is to inform and inspire young women to express their inner fashion and beauty. This website will be designed to help encourage young women to express their beauty through showing new clothing trends, different make-up looks, and hairstyles. We will try to satisfy all of our users by having various styles to fit everyone’s needs. The ultimate goal we would like to achieve is to ensure that our target audience feels beautiful from the inside and out.


Naming Conventions¶
File and Directory Names¶
Our directory tree stripped down looks something like:
statsmodels/
__init__.py
api.py
discrete/
__init__.py
discrete_model.py
tests/
results/
tsa/
__init__.py
api.py
tsatools.py
stattools.py
arima_model.py
arima_process.py
vector_ar/
__init__.py
var_model.py
tests/
results/
tests/
results/
stats/
__init__.py
api.py
stattools.py
tests/
tools/
__init__.py
tools.py
decorators.py
tests/
The submodules are arranged by topic, discrete for discrete choice models, or tsa for time series analysis. The submodules that can be import heavy contain an empty __init__.py, except for some testing code for running tests for the submodules. The namespace to be imported is in api.py. That way, we can import selectively and do not have to import a lot of code that we do not need. Helper functions are usually put in files named tools.py and statistical functions, such as statistical tests are placed in stattools.py. Everything has directories for tests.
endog & exog¶
Our working definition of a statistical model is an object that has both endogenous and exogenous data defined as well as a statistical relationship. In place of endogenous and exogenous one can often substitute the terms left hand side (LHS) and right hand side (RHS), dependent and independent variables, regressand and regressors, outcome and design, response variable and explanatory variable, respectively. The usage is quite often domain specific; however, we have chosen to use endog and exog almost exclusively, since the principal developers of statsmodels have a background in econometrics, and this feels most natural. This means that all of the models are objects with endog and exog defined, though in some cases exog is None for convenience (for instance, with an autoregressive process). Each object also defines a fit (or similar) method that returns a model-specific results object. In addition there are some functions, e.g. for statistical tests or convenience functions.
See also the related explanation in endog, exog, what’s that?.
Variable Names¶
All of our models assume that data is arranged with variables in columns. Thus, internally the data is all 2d arrays. By convention, we will prepend a k_ to variable names that indicate moving over axis 1 (columns), and n_ to variables that indicate moving over axis 0 (rows). The main exception to the underscore is that nobs should indicate the number of observations. For example, in the time-series ARMA model we have:
`k_ar` - The number of AR lags included in the RHS variables
`k_ma` - The number of MA lags included in the RHS variables
`k_trend` - The number of trend variables included in the RHS variables
`k_exog` - The number of exogenous variables included in the RHS variables excluding the trend terms
`n_totobs` - The total number of observations for the LHS variables including the pre-sample values
Options¶
We are using similar options in many classes, methods and functions. They should follow a standardized pattern if they recur frequently.
`missing` ['none', 'drop', 'raise'] define whether inputs are checked for
nans, and how they are treated
`alpha` (float in (0, 1)) significance level for hypothesis tests and
confidence intervals, e.g. `alpha=0.05`
patterns
`return_xxx` : boolean to indicate optional or different returns
(not `ret_xxx`)


| GIO Reference Manual |
|---|
gio-querymodulesgio-querymodules — GIO module cache creation |
gio-querymodules
{DIRECTORY...}
gio-querymodules creates a
giomodule.cache
file in the listed directories.
This file lists the implemented extension points for each module
that has been found. It is used by GIO at runtime to avoid opening
all modules just to find out which extension points they are implementing.
GIO modules are usually installed in the gio/modules
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- Blog Posts
JavaScript and Ruby are pretty similar in more ways than one. But I think it's worth discussing how JavaScript Objects and Ruby Hashes are similar.
At their core they're very simpple. JavaScript Objects store information and so do Ruby hashes. The only difference is the way they store info is a little bit different (really not much different at all). If you have been following my blog posts you've seen me discuss Ruby hashes already. Hashes allow information to be stored and called upon much faster than it would be if stored in an array. This is achieved by using a unique "Key" to call a value associated with said key. Ex: Hash = {key: value}
Conversely, if we look at JavaScript Objects we can the similarities rather quickly. They may look a little bit different but they perform the same job of storing information. The only difference is that JavaScript Objects store their info in properties which end up taking a similar form. Ex: var Object_Name = { property: info }
On a quick glance you can see that the core information is stored inside of curly brackets just like the Ruby Object. The only difference is the names for some of the moving parts. A key would be a property in a JavaScript object and a value would be the info.
Also, the way that we access the info from Javascript Objects / Ruby Hashes is a litle different. In JavaScript we use a dot notation that is fairly straight forward: "Name.property". This notation will allow us to retrieve the information we want. In ruby they use the key name to retrieve the value also housed within the hash: "Hash[:key]". As I said before, they do what are essentially the same jobs the only difference is that they are contained in two separate programming languages.


µVision Build Log
Tool Versions:
IDE-Version: µVision V<IP_ADDRESS> Copyright (C) 2020 ARM Ltd and ARM Germany GmbH. All rights reserved. License Information: Andrin Kälin, OST, LIC=---- Tool Versions: Toolchain: MDK-Lite Version: <IP_ADDRESS> Toolchain Path: D:\Keil\ARM\ARMCC\Bin C Compiler: Armcc.exe V5.06 update 7 (build 960) Assembler: Armasm.exe V5.06 update 7 (build 960) Linker/Locator: ArmLink.exe V5.06 update 7 (build 960) Library Manager: ArmAr.exe V5.06 update 7 (build 960) Hex Converter: FromElf.exe V5.06 update 7 (build 960) CPU DLL: SARMCM3.DLL V<IP_ADDRESS> Dialog DLL: DCM.DLL V<IP_ADDRESS> Target DLL: STLink\ST-LINKIII-KEIL_SWO.dll V<IP_ADDRESS> Dialog DLL: TCM.DLL V<IP_ADDRESS>Project:
C:\Users\seakf\Documents\CODES\Hypnos\Hypnos_Code\Hypnos_Code.uvprojx Project File Date: 01/17/2021Output:
*** Using Compiler 'V5.06 update 7 (build 960)', folder: 'D:\Keil\ARM\ARMCC\Bin' Build target 'Target 1' compiling Hypnos_Code.c... Hypnos_Code.c(21): warning: #177-D: variable "Data" was declared but never referenced unsigned int Data = 0; Hypnos_Code.c(22): warning: #177-D: variable "i" was declared but never referenced unsigned int i = 0; Hypnos_Code.c(23): warning: #177-D: variable "wByte" was declared but never referenced unsigned char wByte[3] ; Hypnos_Code.c: 3 warnings, 0 errors linking... Program Size: Code=2176 RO-data=412 RW-data=0 ZI-data=1632 FromELF: creating hex file... ".\Objects\Hypnos_Code.axf" - 0 Error(s), 3 Warning(s).Software Packages used:
Package Vendor: ARM http://www.keil.com/pack/ARM.CMSIS.5.7.0.pack ARM.CMSIS.5.7.0 CMSIS (Cortex Microcontroller Software Interface Standard) * Component: CORE Version: 5.4.0 Package Vendor: Keil https://www.keil.com/pack/Keil.STM32L4xx_DFP.2.5.0.pack Keil.STM32L4xx_DFP.2.5.0 STMicroelectronics STM32L4 Series Device Support, Drivers and Examples * Component: Startup Version: 1.3.1Collection of Component include folders:
.\RTE\_Target_1 D:\Keil\ARM\CMSIS\5.7.0\CMSIS\Core\Include D:\Keil\Keil\STM32L4xx_DFP\2.5.0\Drivers\CMSIS\Device\ST\STM32L4xx\IncludeCollection of Component Files used:
* Component: ARM::CMSIS:CORE:5.4.0 * Component: Keil::Device:Startup:1.3.1 Include file: Drivers\CMSIS\Device\ST\STM32L4xx\Include\stm32l4xx.h Source file: MDK\Device\Source\ARM\STM32L4xx_SB_OPT.s Source file: Drivers\CMSIS\Device\ST\STM32L4xx\Source\Templates\arm\startup_stm32l431xx.s Source file: Drivers\CMSIS\Device\ST\STM32L4xx\Source\Templates\system_stm32l4xx.c Build Time Elapsed: 00:00:02


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(Note: For scientific articles by individual herbarium curators and researchers, visit their personal pages linked from the UC/JEPS Directory)
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California Bees and Blooms: A Guide for Gardeners and Naturalists
Co-authored by UC/JEPS Curator of Western North American Flora Barbara Ertter, California Bees and Blooms: A Guide for Gardeners and Naturalists by Gordon W. Frankie, Robbin W. Thorp, Rollin E. Coville, and Barbara Ertter will help readers discover and learn about California's bees. California Bees and Blooms holds a magnifying glass up to the twenty-two most common genera (and six species of cuckoo bees), describing each one's distinctive behaviors, social structures, flight season, preferred flowers, and enemies. Enhancing these descriptions are photographs of bees so finely detailed they capture pollen scattered across gauzy wings and iridescent exoskeletons. Available from Heyday Press.
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The Jepson Manual, Vascular Plants of California, Second edition (2012)
The second edition of The Jepson Manual thoroughly updates this acclaimed work, the single most comprehensive resource on California's amazingly diverse flora. The Jepson Manual, second edition, integrates the latest science with the results of intensive fieldwork, institutional collaboration, and efforts of hundreds of contributing authors into an essential reference on California's native and naturalized vascular plants. Available now from UC Press.
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Annotated Checklist of the East Bay Flora (2013)
UC/JEPS Curator of Western North American Flora Barbara Ertter and restoration ecologist, botanist, and photographer Lech Naumovich have published a new edition of the Annotated Checklist of the East Bay Flora, incorporating a wealth of new information. Available now from the California Native Plant Society.
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The Pteridophytes of Mexico (2004)
Co-authored by UC/JEPS Curator of Pteridophytes Alan R. Smith, this is the first modern, comprehensive fern flora for Mexico and one of the few fully illustrated fern floras for any tropical country. Available now from New York Botanical Garden Press.
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Tarweeds and Silverswords: Evolution of Madiinae (Asteraceae) (2003)
(From MBG Press): Tarweeds and silverswords of the Madiinae represent singular examples of adaptive radiation and speciation: they show us plants evolving first to meet the diverse environments of the California Floristic Province, and colonizing later the islands of Hawaii. This book introduces the student to the Madiinae. Included are the phylogeny and taxonomy of the Madiinae and modern analysis of their macro- and micro-evolution as well as molecular investigations. Also profiled are their anatomies of leaf and wood. Available now from Missouri Botanical Garden Press.
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Constancea: University of California Electronic Publications in Botany (2002-)
Constancea is a free online scientific journal sponsored by the University and Jepson Herbaria and UC Press. It is an online continuation of University of California Publications in Botany, which ran from 1902-2002). Available online.
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The Jepson Desert Manual (2002)
In the spirit of the avid desert botanist Willis Linn Jepson, The Jepson Desert Manual provides botanical enthusiasts of all backgrounds with the first comprehensive field guide focused exclusively on native and naturalized vascular plants of California's southeastern deserts. Based on The Jepson Manual: Higher Plants of California, the Desert Manual incorporates new illustrations for more than two hundred desert taxa, revised keys to identification, updated distributional information, and 128 color photographs. This guide will allow easier identification of California's fascinating desert plants than would be possible in a manual with broader geographic coverage. Available now from UC Press.
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The Flowering Plants and Ferns of Mount Diablo, California (2002)
"This magnificent revision of Mary Bowerman's masterpiece lives up to the unsurpassed standards of her now-classic original and brings a tremendous wealth of new information about Mt. Diablo and its spectacular flora into sharp focus. All of the outstanding qualities of the 1944 edition are preserved here and are richly embellished with a thorough, up-to-date, floristic and ecological reassessment based on extensive field and herbaria research. The results of these renewed efforts are impressive, with the addition of more than 200 native and naturalized plant species. Perspectives on the physical environment, vegetation, and flora of Mt. Diablo spanning over half a century of direct investigation provide a fascinating, invaluable account of environmental change on the mountain and of progress in scientific understanding of its rocks, soils, and plants. Anyone with an interest in the natural history of California will not want to be without this book."
-Bruce Baldwin, Curator of the Jepson Herbarium
Available now from the California Native Plant Society.
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Proceedings from the Jepson Herbarium 50th Anniversary Symposium (2000)
Proceedings from The Jepson Herbarium 50th anniversary celebration and scientific symposium: Discovery, communication, and conservation of plant biodiversity in California
June 16-18, 2000. A special issue of Madroño Volume 47, Number 4. Madroño is a quarterly scientific journal of West American botany, published by the California Botanical Society. Available for order from the California Botanical Society.
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The Jepson Globe (1987-present)
The Jepson Globe is a semiannual newsletter published for the Friends of the Jepson Herbarium. Hard copies are distributed to the Friends, then issues are posted online one year after publication. Visit the Jepson Globe index for issues from 2003 to last year, or Join the Friends of the Jepson Herbarium to receive current issues as they are published.
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Catalogue of the Benthic Marine Algae of the Indian Ocean (1996)
All published records of species and infraspecific taxa of benthic marine algae from the Indian Ocean excluding the Red Sea are assembled in a catalogue. A history of Indian Ocean phycology precedes the systematic part of the catalogue, and extensive nomenclatural notes by P.C. Silva on various taxa are included in an appendix. Online version now available.
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The Future of California Floristics and Systematics: Research Education, Conservation (1995)
Madroño, Volume 42, Number 2. A special issue with contributions from many UC/JEPS researchers and staff. Madroño is a quarterly scientific journal of West American botany, published by the California Botanical Society. Available for order from the California Botanical Society.
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A Flora of California by Willis Linn Jepson (1909-1940)
The Flora was published by the Jepson Herbarium in a multi-volume series beginning in 1909 and continuing steadily through 1940. Work on the Flora slowed after Jepson's death in 1946, with Volume 4 Part 2 by Lauramay T. Dempster, appearing in 1979 after a long hiatus. The Flora contains exceptionally detailed taxonomic treatments and original line drawings; for many taxa in California, the Flora contains the most comprehensive description of morphological characteristics, habitats, and ecology available. Unfortunately, this great work was never completed and is now out-of-print, although there are a limited number of full sets still available through the Jepson Herbarium.
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Trees of California by Willis Linn Jepson (1909)
Jepson's account of the trees of California includes several papers on trees and forestry followed by a systematic treatment of the trees of the State, including thorough notes and features. This volume is out of print but limited copies are still available through the Jepson Herbarium.
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Tiger Woods first captain to pick himself as Presidents Cup wild card
Tiger Woods has become the first Presidents Cup captain to use a wild-card selection on himself.
He will also become only the second playing captain in the Presidents Cup, after Hale Irwin did so in the inaugural matches 25 years ago.
Since returning in early 2018 from a fourth surgery on his back, Woods has won three tournaments, including his 15th major when he won the Masters in April.
“It’s going to be a lot of work, but (it is) something I’ve been looking forward to for a long time,” Woods said.
In October, Woods equalled the PGA Tour record with his 82nd career victory at the Zozo Championship in Japan.
He said the trip to Japan – the travel as well as winning – convinced him he was fully healed from knee surgery he had in August and capable of playing in the Presidents Cup, which will be held from December 12-15 at Royal Melbourne in Australia.
As captain, I’m going to choose Tiger Woods as the last player on the team
Woods also selected Tony Finau, US Open champion Gary Woodland and Patrick Reed.
The rest of the US team is Dustin Johnson, Xander Schauffele, Bryson DeChambeau, Justin Thomas, Matt Kuchar, Patrick Cantlay and Webb Simpson.
That leaves room for one more player, which could be current world No 1 Brooks Koepka, who had stem cell treatment in his left knee after the Tour Championship.
In announcing himself as his fourth and final pick, Woods said: “As captain, I’m going to choose Tiger Woods as the last player on the team.
“He’s made … nine Cups and he’s played in Australia twice in the Presidents Cup, so this will be his third appearance as a player.
“And I find it interesting talking in the third person.”


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No matter if you are a student who wants to learn more or a senior developer wanting to share experiences, we welcome everyone along to the group to enjoy the event and network with like-minded technologists.
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Everyone should have the opportunity to learn, being free gives everyone a chance to learn no matter what background you come from.


Knowing you was already a blessing but having the opportunity to love you was a much bigger blessing.
You are the man I have always dreamed of.
I have always dreamed of having someone that would understand me for who I am, would love me for who I am as well. I envisioned my future husband to be someone who always sees the good in others, and someone who values trust. A man who never forgets to keep her woman happy, a man who handles rough situations maturely is also a man I desired. And, my love, you are all that. You have shown me that you are capable of loving me even if I am hard to love. You have seen me at my worst and yet you still found a reason to stay and love me even more. We have our share of downturns, but you handle everything perfectly. You keep me happy, even if I am the moodiest person in the whole world, you never fail to turn each frown into a smile. And most importantly, you trust me completely with your whole life.
I promise to be the woman that you deserve.
I may not be perfect, but I try to be, and I promise to never stop trying. You deserve the world, love, and I will give that to you. I promise to be always by your side no matter what, I will always listen and understand you and your feelings. I promise to love you every second of every minute of every hour of every day.
You are my favorite everything.
 I can be myself when I am around you and that is the best part. I am truly the happiest when I am with you. I truly believe that you are the man desired for me. I hope that you never get tired of loving me, because I will never get tired of loving you.


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Useful tips and tricks to deal with load shedding | IOL News
Cape Town - As South Africans brace for a dark festive season, experts have offered useful tips and tricks to help deal with ongoing load shedding.
On Monday morning, Eskom announced that the planned Stage 2 load shedding would move to stage 4 from 10am until 11pm due to additional loss of units at its power stations.
The entity also said the probability of load shedding remained high for the week as a result of a shortage of capacity.
To help deal with this, Budget Insurance has offered various ways consumers can cope with the ongoing power cuts, all while saving money and looking after the environment.
“Many South Africans are left scratching their heads on how to cope with high energy prices, as well as how to curb load shedding and its effects on their businesses and homes,” says Budget Insurance's Susan Steward.


Temperature:
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Outdoor Control
Sensor 1:
Sensor 2:
Sensor 3:
Watering:
Boost your Agriculture
[Farm Name]
As the graph shows, in the following few months we may have a highest temperature of {{highestTemp}} and lowest of {{lowestTemp}} Fahrenheit. Based on the machine learning algorithm, this is good/bad for your products in this farm. Also mind the high temperature on {{maxTempDate}}, we suggest that you, the manager of this farm, make sure that all plants are hydrated and may irrigate extra once per week during warm period.
This is an alternative temperature line chart in order to show you the temperature and weather in next 3 months from a different angle. We get the weather data from last 30 years and retrieve the average high and low temperatures for each day in the next 90 days. We suggest you also refer to this graph for a better understanding of the weather in the future, since it's representative proved by scientists.
Recently, we have average rainfall, and it seems that everything goes well. It will be raining heavily someday around {{maxRainDate}}. And it seems that {{percentageOfNoRain * 100 | number:2}}% of days in the next three months will have no rainfall.
The monthly gives you a more overall perception about precipitation. Everything goes right!
Lucky you! You get mild wind in the following ten days, with a average of {{avgWindSpd | number:2}}kts, so no worries about your products.
Based on our huge database and machine learning algorithms, we believe that the growing season for this farm will last for [INT] ~ [INT] more days, that is, your expected harvest period is from [DATE] to [DATE].
Also, the degree sweetness of your apples this year is expected to be [xxx], a little bit higher than previous ones. The quantity of apples and quality per apple are expected as [x] and [y] respectively. And the best selling period is considered from [date] to [date], [xxxx] days in total. And $xx/kg would be a reasonable price based on market trend in previous years.
Temperature:
Humidity:
Oxygen Concentration:
Illumination:
Sensor 1:
Sensor 2:
Sensor 3:
Watering:


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SIPB HWOPS
Welcome to the website of SIPB's Hardware Operations (HWOPS) project!
Overview:
- We are responsible for the operation and maintenance of the SIPB machine room in W20-575A, as well as for some aspects of SIPB's servers in W91.
- In addition, we are responsible for planning out the future of SIPB's physical server spaces.
- We provide physical server space, server hardware, and server support services to other SIPB projects.
- If your project is not an official SIPB project, we will be able to refer you to other resources, but we will not be able to provide you with server space unless your project becomes recognized as an official SIPB project.
- Some of our operational databases are publicly accessible on this website, for the sake of transparency.
- As with all SIPB services, HWOPS is a volunteer-run service, and although we strive for perfect uptime of the server room, we will not always be able to provide it.
Contact information:
- Primary contact point<EMAIL_ADDRESS>- Emergency phone contact: see bottom of page.
- Chat contact: see the Machine Rooms channel in SIPB Mattermost. Tag the primary support contact listed in the header.
- Phone contact: call<PHONE_NUMBER> to reach the SIPB office, which might or might not have anyone available who can help.
- Security/confidental contact<EMAIL_ADDRESS>- Team members mailing list<EMAIL_ADDRESS>- To obtain a replacement for a lost or stolen access card: email<EMAIL_ADDRESS>- To try to talk to someone in person: show up at the SIPB meeting on Monday at 7:30 PM.
As of 2019-02-18, the responsibility of managing the SIPB Machine Room has been transferred from the SIPB Vice Chair to the SIPB Hardware Operations project.
Server room emergency contact:
{% if user %}{% if on_office %}{{ emergency }}
You can only see this information because you are on<EMAIL_ADDRESS>else %}Although you are logged in, you cannot view this information, because you are not on the mailing list<EMAIL_ADDRESS>endif %}{% else %}[Information hidden; login with certificates to view.]{% endif %}
Do not share this contact information with anyone outside of SIPB.
Navigation: Server Inventory | Parts Inventory | Server Request Form | Documents and Manuals
The source code for this website is available on GitHub.


Restore from file or device
This option determines where the backup dump data is read from. It can either
be a local file or tape device, or a file or device on a remote host.
For restores from a remote host to work, it must support the
rmt protocol, which is not usually turned on by default for security
reasons.


The web service is accessed via a proxy (conventionally known in Java as a port). The proxy (here given a variable name of icat) may be obtained by the following:
URL hostUrl = new URL("https://<hostname>:8181")
URL
icatUrl = new URL(hostUrl, "ICATService/ICAT?wsdl");
QName
qName = new QName("http://icatproject.org", "ICATService");
ICATService service = new ICATService(icatUrl, qName);
ICAT
icat = service.getICATPort();
where <hostname> should be the full name of the ICAT server. For a secure installation, just specifying localhost will not work, the name must match what is on the host certificate.
The corresponding Python suds code is:
from suds.client import Client
client = Client(url)
icat = client.service
factory = client.factory
methods may then be invoked on the icat object and entities created using the factory.
When you login to ICAT you will be given back a string, the sessionId, which must be used as the first argument of almost all ICAT calls. The only exceptions being the login call itself, getEntityInfo and getApiVersion - none of which require authentication.
String login(String plugin, Credentials credentials)
where the plugin is the mnemonic defined in the ICAT installation for the authentication plugin you wish to use and credentials is essentially a map. The names of the keys and their meaning is defined by the plugin.
This sessionId returned will be valid for a period determined by the ICAT server.
The example below shows how it works for the authn_db plugin at the time of writing, where the plugin has been given the mnemonic "db".
Credentials credentials = new Credentials();
List<Entry>
entries = credentials.getEntry();
Entry e;
e =
new Entry();
e.setKey("username");
e.setValue("root");
entries.add(e);
e = new Entry();
e.setKey("password");
e.setValue("secret");
entries.add(e);
String sessionId = icat.login("db",
credentials);
The corresponding Python code, using the factory and icat service defined above is:
credentials = factory.create("login.credentials")
entry = factory.create("login.credentials.entry")
entry.key =
"username"
entry.value = "root"
credentials.entry.append(entry)
entry =
factory.create("login.credentials.entry")
entry.key =
"password"
entry.value = "secret"
credentials.entry.append(entry)
sessionId =
icat.login("db", credentials)
double getRemainingMinutes(String sessionId)
This returns the number of minutes left in the session. A user may have more than one session at once.
String getUserName(String sessionId)
This returns the string identifying the user of the session as provided by the authentication plugin.
void refresh(String sessionId)
This resets the time-to-live of the session as it was when the session was first obtained.
void logout(String sessionId)
This invalidates the sessionId.
There is only one exception thrown by ICAT. In the case of Java this is the IcatException_Exception which is a wrapper around the real exception which in turn includes an enumerated code to identify the kind of exception and the usual message. The codes and their meanings are:
For example to print what has happened you might use the following (in Java):
String sessionId;
try {
sessionId =
icat.login("db", credentials);
} catch
(IcatException_Exception e) {
IcatException ue =
e.getFaultInfo();
System.out.println("IcatException " + ue.getType() + " " +
ue.getMessage()
+ (ue.getOffset() >= 0 ? " at
offset " + ue.getOffset() : ""));
}
The corresponding Python code looks like:
try:
sessionId = icat.login("db", credentials)
except WebFault as e:
etype =
e.fault.detail.IcatException.type
message =
e.fault.detail.IcatException.message
offset =
e.fault.detail.IcatException.offset
print
"IcatException " + etype + " " + message + (" at offset " + offset) if
offset >= 0 else ""
Operations which work on a list of objects, such as createMany, may fail because of failure to process one of the objects. In this case the state of the database will be rolled back and the offset within the list of the entry causing the error will be stored in the IcatException. For other calls the offset will be negative, as it is with certain internal exceptions which are not associated with any specific object in a list.
long create(String sessionId, EntityBaseBean bean)
To create an object in ICAT, first instantiate the object of interest, for example a Dataset, and then call the setters to set its attributes and finally make a call to create the object in ICAT.
So typical code in Java might look like:
Dataset ds = new Dataset();
ds.setName("Name of dataset");
ds.set ...
Long dsid = icat.create(sessionId, ds);
You will see that no convenient constructors are generated, rather each field of the object must be set individually.
The corresponding code in Python is shownn below. Note that the factory.create takes the lower case name "dataset" rather than "Dataset"
ds = factory.create("dataset")
ds.name = "Name of dataset"
ds. ...
dsid = icat.create(sessionId, ds);
Most fields are optional and may be left with null values, however some are compulsory and the call to create will fail if they are not set. Each object has a primary key that identifies it in the database - this is a value of type "long" that is generated by ICAT and is used to represent relationships in a regular manner.
Some fields represent attributes of the object but others are used to represent relationships. The relationships are represented in the class definitions by a variable which either holds a reference to a single object or a list of objects. In the case of a list it may be "cascaded". Consider creating a dataset with a set of datafiles. Because the relationship from dataset to datafile is cascaded they may be created in one call as outlined by the Java code below:
Dataset ds = new Dataset();
ds.setName(dsName);
ds.setType(type);
Datafile datafile = new Datafile();
datafile.setDatafileFormat(format);
datafile.setName(dfName);
ds.getDatafiles().add(datafile); // Add the datafile to the
dataset
icat.create(sessionId, ds);
The call to create returns the key of the created object. If you choose to write the Java code
ds.setId(icat.create(sessionId, ds));
then the client copy of the Dataset will be updated to have the correct key value - however the keys in any other objects "within" the Dataset will still be null on the client side. In this case datafile.getId() will remain null.
It might help to understand what is happening when you call create. The client side object you pass in, and everything it refers to , is encoded as XML and sent to the server. There it is unpacked into the same set of objects and persisted in the database. The structure passed in must be a tree structure (or more correctly a DAG ) - if, for example, you modify the code above to create a dataset with one datafile and add datafile.setDataset(dataset) attempting to put in a reverse link which physically will appear in the ICAT database the call will be rejected by the client because you have a loop in the graph as you can then go backwards and forwards between datafile and dataset. If you passed in a proper DAG the database will create one row in the dataset table and one in the datafile table where the datafile entry includes the field datafile.dataset_id holding the dataset.id of the dataset entry just created. Relationships are represented in the database by holding the id value of the related object.
We now have a Java example of adding a datafile to an existing dataset, ds
Datafile datafile = new Datafile();
datafile.setDatafileFormat(format);
datafile.setName(name);
datafile.setDataset(ds); // Relate the datafile to an existing dataset
datafile.setId(icat.create(sessionId, datafile)); // Create
datafile and store id on client side
This is the only way to create a datafile and add it to a dataset - you cannot do it by any operation upon the dataset. A datafile cannot be created without a dataset. After the call is made a new entry will have been been added to the datafile table in the database where again the field datafile.dataset_id in the database will have been set to the dataset.id of the related dataset which in this case may be more intuitive as it corresponds to the line of user code datafile.setDataset(ds) .
It is worth noting that the dataset object you have in memory is not affected by the call to create a new datafile. More datafiles can be created referencing the same dataset without retrieving an updated copy of the dataset.
List <Long> createMany(String sessionId, List <EntityBaseBean> beans)
This call, as its name suggests, creates many objects. It takes the list of objects to create and returns a list of ids. If any of the individual operations fail the whole call fails and the database will be unchanged. The objects to be created need not be of the same type. For an example (where they are of the same type) consider adding many Datafiles to a existing Dataset, ds in Java:
List <Datafile> dfs = new ArrayList<Datafile>();
for (int i = 0; i < n; i++) {
Datafile
datafile = new Datafile();
datafile.setDatafileFormat(dfmt);
datafile.setName("bill" + i);
datafile.setDataset(ds);
dfs.add(datafile);
}
icat.createMany(sesionId, dfs); // many datafiles are stored
in one call
The equivalent Python code is:
dfs = []
for i in range(n):
datafile =
factory.create("datafile")
datafile.datafileFormat = dfmt)
datafile.name =
"bill" + str(i)
datafile.dataset = ds
dfs.append(datafile)
icat.createMany(sesionId,
dfs)
The only reason that this call exists is to minimize calls to ICAT as it is faster to call createMany than to make many calls to create .
EntityBaseBean get(String sessionId, String query, long id)
The first parameter is the sessionId, the second is a query string which in the simplest case is just the name of the type of object and the last parameter is the id of the object. You may know the id of an object because you have created it or it was returned from a search call. For example in Java:
get(sessionId, "Dataset", 75L)
will return the Dataset with an id of 75 or throw an exception if it is not found. The dataset is returned on its own with no related objects; the set of related datafiles will be empty and the type (which is a related object) will be null. Often however you will want to return related objects as well. To get a Dataset with all its Datafiles you can use the query:
Dataset ds INCLUDE ds.datafiles
This uses the variable "ds" to identify the selected dataset. The Dataset field "datafiles" will be followed to include all those "Datafiles" related to the selected dataset. Those datafiles which the user is not allowed to read are silently ignored.
To get a Dataset with all its Datafiles, DatasetParameters and DatafileParameters you can use the query:
Dataset ds INCLUDE ds.datafiles df, df.parameters,
ds.parameters
which has introduced another variable df to represent the set of (readable) datafiles and which are related to the initial dataset ds. The variable could be preceded by the keyword "AS" if you feel this makes it easier to read as in:
Dataset ds INCLUDE ds.datafiles AS df, df.parameters,
ds.parameters
To save typing you could write the equivalent:
Dataset ds INCLUDE ds.datafiles.parameters, ds.parameters
This slightly shortened form may make it less obvious that the datafiles are also included in the set of returned objects. In fact they must be present as the returned objects always form a DAG again and the DatafileParameters need the Datafiles to connect in to the structure.
It is permissible to visit an entity type more than once in an INCLUDE - for example following a provenance chain or including the datasets with the same type as a particular dataset which would be:
Dataset ds INCLUDE ds.type t, t.datasets
There is also a special notation "INCLUDE 1" which is described in the next section.
void update(String sessionId, EntityBaseBean bean)
To update an object simply retrieve it, update the fields you want to change and call update. For example to change the name of the dataset to "Fred":
Dataset ds = (Dataset) icat.get(sessionId, "Dataset INCLUDE 1", dsid);
ds.setName("Fred");
icat.update(sessionId, ds);
All "many to one" relationships, such as the relationship to the
Investigation, will be updated as will any simple field values.
Consequently it is essential to get the existing values for any "many
to one" relationships otherwise they will be set to null. This is most
reliably achieved by the notation
INCLUDE 1
as shown here. The effect of the "1" is to include all "many to one"
related types. "One to many" relationships, such as the set of
Datafiles are ignored by the update mechanism. If your attempted
change violates a uniqeness constraint an exception will be thrown.
In addition "many to one" relationships can be modified. For example to make the Dataset part of a different Investigation:
Dataset ds = (Dataset) icat.get(sessionId, "Dataset INCLUDE 1", dsid);
ds.setInvestigation(anotherInvestigation);
icat.update(sessionId, ds);
The equivalent Python code is:
ds = icat.get(sessionId, "Dataset INCLUDE 1", dsid)
ds.investigation = anotherInvestigation
icat.update(sessionId,
ds);
It is sufficient for the relation object to just have the id value correct as the rest of the fields are ignored. For example if you know the id of the Investigation then you could write in Python:
ds = icat.get(sessionId, "Dataset INCLUDE 1", dsid)
inv =
factory.create("investigation")
inv.id =
anotherInvestigationId
ds.investigation = inv
icat.update(sessionId, ds);
void delete(String sessionId, EntityBaseBean bean)
The following Java code will get a dataset and delete it.
Dataset ds = (Dataset) icat.get(sessionId, "Dataset", dsid);
icat.delete(sessionId, ds);
All "one to many" related objects will also be deleted. In the extreme
case, if you delete a facility, you lose everything associated with
that facility. This privilege should not be given to many - see the authorization section later. When you get a
local copy of the object to delete there is no need to use
INCLUDE 1
to populate the "one to many" related objects as all cascades will be
followed. In fact the only part of the object that is used by the
delete call is the id. So the following Java code will have the same
effect and avoids one ICAT call:
Dataset ds = new Dataset()
ds.setId(dsid);
icat.delete(sessionId, ds);
The syntax is a standard JPQL "SELECT" statement with with two extensions a LIMIT clause and an INCLUDE clause which may come in either order after the standard JPQL. The only restriction is that returned item must be a set of entities, the result of an aggregate function (such as COUNT or MAX) or a set of values of one field of an entity type. If you use nested selects please define new variable names for use within such a construct. Some keywords, such as FETCH, are not relevant and are ignored. The language, which borrows a lot from SQL is well explained in the Oracle JPQL documentation.
There are also two extensions to JPQL a LIMIT clause and an INCLUDE
clause which may come in either order after the standard JPQL. The
LIMIT clase follows MySQL syntax and takes the form:
LIMIT 10, 100
which will skip 10 results and return the next 100. A LIMIT clause
will normally be used with an ORDER BY clause. The INCLUDE clause is
just as as has been explained for the get call . A
few examples are shown below:
SELECT ds FROM Dataset ds INCLUDE
ds.datafiles.parameters, ds.parameters
This uses the variable "ds" defined in the FROM clause. It means that the "Dataset" field "datafiles" will be followed to include all those "Datafiles" and that for each "Datafile" the "parameters" field will be followed to get the "DatafileParameters". In addition the "DatasetParameters" will be included. A more interesting example is:
SELECT ds.name FROM Dataset ds WHERE ds.type.name = 'GS'
ORDER BY ds.name LIMIT 0, 10"
This will take the first 10 datasets (as ordered by name) which have a type with a name of 'GS'. The next example is looking for the ids of datasets which have both a parameter A1 > 50 and a parameter A2 > 20
SELECT ds.id FROM Dataset ds, ds.parameters dp1, ds.parameters dp2
WHERE
dp1.type.name = 'A1' AND dp1.numericValue > 50 AND
dp2.type.name = 'A2' AND dp2.numericValue > 20
Note in the example above how the parameters dp1 and dp2 were
introduced. The form
:user
may be used to denote the currently authenticated user (derived from
the sessionId). For example to see the investigations to which you are
associated:
SELECT i FROM Investigation i, i.investigationUsers ius
WHERE ius.user.name = :user
Time literals (which are implementation dependent in JPQL) should be expressed as shown in the next example:
SELECT i FROM Investigation i WHERE i.createTime > {ts
2011-01-15 00:00:00}
The timestamp format must be exactly as shown.  Note that the full class name
org.icatproject.ParameterValueType
must be specified.
Joins can be performed - for example
SELECT u FROM User u JOIN u.userGroups ug JOIN ug.grouping
g WHERE g.name='FacilityAdmins'
The mechanism is rule based. Rules allow groupings of users to do things. There are four things that can be done: Create, Read, Update and Delete. It makes use of five entity types: Rule, User, Grouping, UserGroup and PublicStep. The name "Grouping" has been introduced as, the more natural, "Group" is a reserved word in JPQL. The authentication mechanism authenticates a person with a certain name and this name identifies the User in the ICAT User table. Groupings have names and the UserGroup performs the function of a "many to many" relationship between Users and Groupings. Rules are applied to Groupings. There are special "root users" with full access to all entities. The set of "root users" is a configuration parameter of the ICAT installation. Only a root user can set up the initial set of authorization rules though these rules can then allow others to manipulate rules.
Though the authorization rules are handled as efficiently as possible to get the best performance define a rule to make those entity types world readable where this makes sense. Such rules have no conditions in the "what" field and the grouping field is left null. Such rules are recognised and are cached in memory. Typically those entities which are used to implement a many to many relationship can be world readable as can those which represent types. The PublicStep mechanism is also available to cover the case where access to one entity implies that another may be accessed. For example you might define a PublicStep from Datafile to its Dataset (via the dataset field) and from a Dataset to its Investigation (via the investigation field). For other cases you will need to write rules.
By default access is denied to all objects, rules allow access. It is
only necessary to be permitted by one rule where that rule is only
applied to the object referenced directly in the API call. The Rule
table has two exposed fields:
crudFlags
and
what
. The field
crudFlags
contains letters from the set "CRUD" to indicate which types of
operation are being allowed (Create, Read, Update and/or Delete). The
other field,
what
, is the rule itself. There is also a "many to one" relationship to
Grouping which may be absent.
Consider the Java code:
Rule rule = new Rule();
rule.setGrouping(userOffice);
rule.setCrudFlags("CRUD");
rule.setWhat("Investigation");
icat.create(sessionId, rule);
allows members of the userOffice Grouping full access to all Investigations.
Rule rule = new Rule();
rule.setGrouping(null); // Not
necessary as it will be null on a newly created rule
rule.setCrudFlags("R");
rule.setWhat("ParameterType");
icat.create(sessionId, rule);
allows any authenticated user (with a sessionId) to read Parameters. Consider a Grouping of users: fredReaders. To allow fredReaders to read a datafile with a name of "fred" we could have:
Rule rule = new Rule();
rule.setGrouping(fredReaders);
rule.setCrudFlags("R");
rule.setWhat("SELECT Datafile df WHERE
df.name='fred'");
icat.create(sessionId, rule);
The
what
field may contain almost anything which may appear as a search query.
The query, if evaluated, would return the set of objects which can be
read, updated or deleted in the case of R, U and D crudFlags. For the
C crudFlag which controls create operations, the call is allowed if
after creation of the object it would be in the set defined by the
what
field. Control of update operations is more complex if the update
includes modification of any field that identifies the object. In this
case the user must have delete access to the object before the change
and create access after the change.
To control access to the complete object the search query in the
what
field must return a set of objects rather than a set of fields or an
aggregate function. The query must not contain INCLUDE, LIMIT nor
ORDER BY clauses.
More complex restrictions can be added using other related objects. For example to allow read access to Datasets belonging to an Investigation which includes an InvestigationUser which has a user with a name matching the currently authenticated user (from the sessionId) we can have:
Rule rule = new Rule();
rule.setGrouping(null);
rule.setCrudFlags("R");
rule.setWhat("select Dataset ds,
ds.investigation i, i.investigationUser iu WHERE iu.name = :user");
icat.create(sessionId, rule);
The rules shown so far permit access to all the fields of the object. However for READ and UPDATE it makes sense to control access to an individual attribute. To express this a rule may reference a specific attribute. For example the following Python:
rule = factory.create("rule")
rule.crudFlags = "U"
rule.grouping = invHackers rule.what = "select Investigation inv.doi"
icat.create(sessionId, rule)
allows members of the invHackers grouping to modify the doi field of all Investigations. Currently only the UPDATE operation can be controlled this way. It would be possible to also support READ however as yet no compelling Use Case has been encountered.
Rules which allow everyone to read a table are cached in memory and are good for performance. For example to give universal read access to DatasetType the following Java code could be used:
Rule rule = new Rule();
rule.setGrouping(null);
rule.setCrudFlags("R");
rule.setWhat("DatasetType");
icat.create(sessionId, rule);
This table has two columns (origin and field). An entry in this table affects the way in which INCLUDE authorization is carried out. Each entry permits all users to make a step from the origin entity by the specified relationship field without any further checking. This information is held in memory for speed. For those INCLUDEs that are not mentioned in the PublicStep table a full read authorization check must be made before including an object to be returned - which can be expensive. The following Python code permits the jobs relationship to be followed from an Application.
ps = factory.create("publicStep)
ps.origin = "Application"
ps.field = "jobs"
session.create(ps)
This will mean that if you have a query "SELECT Application a INCLUDE a.jobs" then the system will only return applications your are authorized to read. It will also provide all the jobs which are related to those applications provided you are authorized to do so. In the absence of a PublicStep it will check each one individually which can be time consuming but with this PublicStep in place the system will simply following the relationship without further checks.
boolean isAccessAllowed(String sessionId, EntityBaseBean bean, AccessType accessType)
This call returns true if the access to the bean specified by the accessType is permitted. For example:
Dataset ds = new Dataset();
ds.setName("Name of dataset");
ds.set ...
System.out.println(isAccessAllowed(sessionId, ds,
AccessType.CREATE))
This code sets up a Dataset and then prints whether or not it would be allowed to create it.
This call is expected to be made from GUIs so that they can avoid offering operations that will fail. As such, though READ acess may be queried it is unlikely to be useful as the GUI user will not have found out about the object to be checked. If READ, DELETE or UPDATE access is queried for an object that does not exist it will return false.
In the case of CREATE, the entity is created within a database
transaction, the check is made and the transaction is rolled back.
Note that if a
create
operation would result in a duplicate this will cause an exception to
be thrown.
String getApiVersion()
returns the version of the server
List<String> getEntityNames()
Returns an alphabetic list of all the entity names known to ICAT. This is of most value for tools.
EntityInfo getEntityInfo(String beanName)
returns full information about a table given its name. For example:
EntityInfo ei = icat.getEntityInfo("Investigation");
System.out.println(ei.getClassComment());
for (Constraint c :
ei.getConstraints()) {
; ;
;System.out.println("Constraint columns: " + c.getFieldNames());
}
for (EntityField f : ei.getFields()) {
; ; ;System.out.println("Field names: " + f.getName());
}
Prints out some information about the Investigation table. For a list of all available fields in EntityInfo and the objects it references please consult the javadoc for EntityInfo .
To be authorized to use administration calls you must be authenticated with a name listed in the rootUserNames in the run.properties file.
List<String> getProperties(String sessionId)
lists the active contents of the run.properties file. It does this by examining the properties after they have been read in so any superfluous definitions in the original properties file will not be seen. The current physical file is not re-examined
Originally ICAT did not support JPQL but instead had its own concise query syntax. The concise syntax however is not as general as JPQL and so cannot express some queries. At some time in the future support for the concise syntax may be removed - you have been warned.
If the query is simply
Dataset
this will return all Datasets. If the query is
Dataset.name
this will return all Dataset names. To get related objects returned,
then use INCLUDE followed by a list of object types:
Dataset INCLUDE
Datafile,DatasetParameter,DatafileParameter
The related types must be all be related to the original type or to
some other type in the list. This means that you could not have
"Dataset INCLUDE DatafileParameter"
. In addition there must be only one route from the original type to
each of the included types - i.e. you can only construct one DAG from
the starting object.
You can specify an order (which may precede or follow an INCLUDE clause):
Dataset.id ORDER BY id
Restrictions can be placed on the data returned. For example:
Dataset.id [type.name IN ('GS', 'GQ')]
which could also be written:
Dataset.id [type.name = 'GS' OR type.name = 'GQ']
The restriction in the square brackets can be as complex as required - but must only refer to attributes of the object being restricted - in this case the Dataset. Expressions may use parentheses, AND, OR, <, <=, >, >=, =, <>, !=, NOT, IN, LIKE and BETWEEN. Currently the BETWEEN operator does not work on strings. This appears to be a JPA bug.
Functions: MAX, MIN, COUNT, AVG and SUM may also be used such as:
MAX (Dataset.id)
Selection may involve more than one related object. To show the relationship a "<->" token is used. For example:
Dataset.id <-> DatasetParameter[type.name =
'TIMESTAMP']
Note also here the use of the JPQL style path: type.name . This expressions means ids of Datasets which have a DatasetParameter which has a type with a name of TIMESTAMP. Multiple " <->" may appear but all the objects involved, including the first one, must be connectable in only one way . The next example show how restrictions may be applied to both the Dataset and the DatasetParameter:
Dataset.id [name like 'fred%'] <->
DatasetParameter[type.name = 'TIMESTAMP']
It is also possible to restrict the number of results returned by specifying a pair of numbers at the beginning of the query string. This construct would normally be used with an ORDER BY clause. The first number is the offset from within the full list of available results from which to start returning data and the second is the maximum number of results to return. These numbers if specified must be positive. If the offset is greater than or equal to the number of internal results then no data will be returned. The default values are 0 and "infinity". The numbers must be separated by a comma though either may be omitted. The following are all valid:
3,5 Dataset.id ORDER BY id
3, Dataset.id ORDER BY id
,5 Dataset.id ORDER BY id
To see the investigations to which you are associated you can make use of the special value :user as in:
Investigation <-> InvestigationUser [name = :user]
Time literals (which are implementation dependent in JPQL) should be expressed as shown in the next example:
Investigation [createTime > {ts 2011-01-15 00:00:00}]
The timestamp format must be exactly as shown. Literal boolean values are TRUE and FALSE as in:
Dataset [complete = TRUE]
and finally enums are expressed as shown below:
ParameterType [valueType = DATE_AND_TIME]
which is selecting those ParameterTypes which have a valueType of DATE_AND_TIME from ParameterTypeValue.


UCR International Agreements and MOUs
| Country | Number |
|---|---|
| Argentina | 2 |
| Australia | 1 |
| Belgium | 2 |
| Brazil | 2 |
| Brussels | 1 |
| Canada | 11 |
| Canada | 1 |
| CANADA | 1 |
| Chile | 1 |
| China | 76 |
| China | 1 |
| CHINA | 5 |
| Croatia | 1 |
| Denmark | 1 |
| England | 2 |
| England | 1 |
| France | 26 |
| Germany | 19 |
| Germany, Sweden | 1 |
| Honduras | 1 |
| Hungary | 1 |
| India | 14 |
| India | 1 |
| Ireland | 1 |
| Japan | 33 |
| JAPAN | 1 |
| Korea | 25 |
| Mexico | 2 |
| Netherlands | 1 |
| Norward | 1 |
| Norway | 1 |
| Scotland | 1 |
| Scotland | 1 |
| Singapore | 2 |
| Spain | 26 |
| SPAIN | 1 |
| Switzerland | 1 |
| Taiwan | 6 |
| Turkey | 2 |
| United Arab Emirates | 1 |
| United States of America | 1 |
| USA | 1 |
| Various | 1 |
| Vietnam | 3 |
UCR partners with universities throughout the world to maintain the highest standards of teaching and research, to keep up with academic trends, and to share innovations.
International agreements represent an outstanding opportunity for UCR faculty, staff, and students to grow and learn through contact with international colleagues. A partnership may be codified through an agreement known as a Memorandum of Understanding (MOU), or an International Exchange and Linkage Agreement (IE Agreement). The MOU is a broad agreement in which UCR and a partner express an intention to engage in cooperative academic or research activities. The IE agreement involves a commitment of UCR resources for specific cooperative international academic and research activities.
UCR Faculty
All international agreements must be routed for approval, archiving, and inclusion in a campus database. This website includes:
- on campus agreements
- Information about creating international agreements
- Archive of existing agreements
- Template with pre-approved text to propose new MOUs.
Logon with a UCR NetID is required to access some sections of this site. The University Extension Dean's Office assists the EVC/Provost with the approval and archiving of agreements. Please direct questions about agreements to:
Marie Martin, University Extension Dean's<EMAIL_ADDRESS>(951) 827-4102, campus extension 2-4102
International Universities
If you are interested in research collaborations with UC Riverside and are not already in contact
with an academic department or other unit, please contact:
| Public Policy | Anil Deolalikar U.S.<PHONE_NUMBER> |
<EMAIL_ADDRESS>International<PHONE_NUMBER>43 |
| Natural and Agricultural Sciences | ||
| Education | Jennifer Blain U.S.<PHONE_NUMBER> |
<EMAIL_ADDRESS>International<PHONE_NUMBER>02 |
For all other inquiries regarding research collaborations or visiting student programs, please contact:
Bronwyn Jenkins-Deas,
Associate Dean for International Education, University Extension
<EMAIL_ADDRESS>U.S.<PHONE_NUMBER>, International<PHONE_NUMBER>702


Your device is or looks brand-spankin’-new. Choose top-notch if all of the following apply:
Your phone or tablet has been used, but it’s in pretty brag-worthy condition (if you do say so yourself). Choose decent if all of the following apply:
You live your life, and it really shows in the state of your phone. Choose busted if ANY of the following apply:


Why ClojureScript?
Chris Oakman
March 2014
Chris Oakman
March 2014
ClojureScript is an excellent language choice for UI development.
Are we all talking about the same thing?
I say hello, you say hola.
A programming system has two parts. The programming environment is the part that's installed on the computer. The programming language is the part that's installed in the programmer's head.
____________ is a stateful, dynamically typed, imperative programming language often used for web development that supports an object-oriented programming style.
Most web development languages are more similar than they are different. People love to focus on the superficial differences between similar languages.
Change your language; change the way you think about your programs.
Best of breed.
// a, b, someFn, anotherFn are defined above this line
a = "foo";
b = { bar: "baz"};
a = someFn(a);
b = anotherFn(a, b);
// what is the value of a? b?
console.log(a);
console.log(b);
Mutability complects value over time.
Put another way, the value of something depends on what "time" it is in the program. Time becomes one more ball to juggle while you're programming.
;; foo is an atom; it can change state
(def foo (atom nil))
(defn on-change-foo [old-foo new-foo]
;; do something here
)
;; "watch" the atom for changes
;; run on-change-foo everytime foo changes value
(add-watch foo on-change-foo)
;; change the value of foo with swap!
;; foo becomes the result of executing the bar function
(swap! foo bar)
(defn add-events []
(-> ($ "#myContainer")
(on "mousedown" on-mousedown)
(on "click" "#btn1" on-click-btn1)
(on "click" "#btn2" on-click-btn2)
(on "hover" ".tab" on-hover-tab)
(on "change" "input.date" change-date-field)
(on "click" "#submitBtn" on-submit)))
var personA = {
age: 32,
name: { first: "John", last: "Doe" }
};
var personB = {
age: 22,
name: { first: "Jane", last: "Doe" }
};
if (personA === personB) {
// why can't I do this in JS?
};
(def person-a {
:age 32
:name { :first "John" :last "Doe" }})
(def person-b {
:age 22
:name { :first "Jane" :last "Doe" }})
(if (= person-a person-b)
;; do something
)
// no optimizations
function hello(name) {
alert('Hello, ' + name);
}
hello('New user');
// simple optimizations
function hello(a){alert("Hello, "+a)}hello("New user");
// advanced optimizations removes dead code
alert("Hello, New user");
There is no free lunch.
The positives outweigh the negatives.
Chris Oakman
<EMAIL_ADDRESS>http://oakmac.com/why-cljs/
https://github.com/oakmac/why-cljs


This project is still in development. Please stay tuned for more features and changes! If you have a feature request, please poke Snipa on irc.freenode.net in #monero-pools
PPS Fee
{{config.pps_fee}}%
PPLNS Fee
{{config.pplns_fee}}%
Solo Fee
{{config.solo_fee}}%
BTC Fee
{{config.btc_fee}}%
Minimum payout (Wallet)
{{config.min_wallet_payout | toXMR}} XMR
Minimum payout (BTC)
{{config.min_btc_payout | toXMR}} XMR
Minimum payout (Exchange)
{{config.min_exchange_payout | toXMR}} XMR
Core Devs Donation
{{config.dev_donation}}%
Pool Devs Donation
{{config.pool_dev_donation}}%
Block Maturity Depth
{{config.maturity_depth}}
Minimum Denomination
{{config.min_denom | toXMR}}


jQuery.post( url [, data ] [, success ] [, dataType ] )Returns: jqXHR
Description: Load data from the server using a HTTP POST request.
-
jQuery.post( url [, data ] [, success ] [, dataType ] )
-
urlType: StringA string containing the URL to which the request is sent.
-
dataType: PlainObject or StringA plain object or string that is sent to the server with the request.
-
successA callback function that is executed if the request succeeds. Required if
dataType
is provided, but can benull
in that case. -
dataTypeType: StringThe type of data expected from the server. Default: Intelligent Guess (xml, json, script, text, html).
-
This is a shorthand Ajax function, which is equivalent to:
|
1
2
3
4
5
6
7
|
|
The success
callback function is passed the returned data, which will be an XML root element or a text string depending on the MIME type of the response. It is also passed the text status of the response.
As of jQuery 1.5, the success
callback function is also passed a "jqXHR" object (in jQuery 1.4, it was passed the XMLHttpRequest
object).
Most implementations will specify a success handler:
|
1
2
3
|
|
This example fetches the requested HTML snippet and inserts it on the page.
Pages fetched with POST
are never cached, so the cache
and ifModified
options in jQuery.ajaxSetup()
have no effect on these requests.


|
|
| RK4Register () |
| | Constructor calls CosmoArray constructors; call RK4Register::init to initialize class.
|
| |
|
| RK4Register (IT nx_in, IT ny_in, IT nz_in, RT sim_dt_in) |
| |
| void | init (IT nx_in, IT ny_in, IT nz_in, RT sim_dt_in) |
| | Initialize class variables; call CosmoArray::init for array members. More...
|
| |
|
void | setDt (RT sim_dt_in) |
| | Set "dt" for RK4Register instance.
|
| |
| void | setName (std::string name_in) |
| | Set "name" property of instance, CosmoArray member instances. More...
|
| |
|
void | swap_a_c () |
| | Swap data in and names of _a and _c registers.
|
| |
|
void | swap_p_f () |
| | Swap data in and names of _p and _f registers.
|
| |
|
void | stepInit () |
| |
|
void | K1Finalize () |
| |
|
void | K2Finalize () |
| |
|
void | K3Finalize () |
| |
|
void | K4Finalize () |
| |
|
RT & | _p (const IT &i, const IT &j, const IT &k) |
| |
|
RT & | _a (const IT &i, const IT &j, const IT &k) |
| |
|
RT & | _c (const IT &i, const IT &j, const IT &k) |
| |
|
RT & | _f (const IT &i, const IT &j, const IT &k) |
| |
|
RT & | operator() (const IT &i, const IT &j, const IT &k) |
| |
|
RT & | operator[] (IT idx) |
| |
template<typename IT, typename RT>
class cosmo::RK4Register< IT, RT >
RK4 Class for integration.
See the docs/RK4_integration.pptx file.
- Template Parameters
-


{% extends 'layout.html' %} {% block body %}
This web app displays space planets in our solar system and outside of the solar system where each user can upload and search planets pictures and its attributes in the universe.


Int-rev Login2
Username
Username required!
Password
Password required!
Log in
403 Unauthorized
You are not authorized to enter the admin panel.
OK


Still shopping for those finnicky feminists? We’ve got you covered. *Order from the FMF Feminist Store by the end of the day to get an ethical gift delivered in time for the holidays! [ http://store.feminist.org ]*
You’ll find feminist apparel, children’s toys, office supplies, jewelery, and more in the FMF’s Feminist Store - all ethically made, with proceeds benefitting our work for women’s equality around the world.
[ http://store.feminist.org/ ]
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Website Background Generator
Software Design Final Project 2019
Katie Foster, Anne Jiang, Shirin Kuppusamy
Our Project
As college students, we are very busy with our studies and so rarely find the time to appreciate the outdoors as much we would like. Our product creates a background that mimics the natural light outside to create a visually pleasing color and then to create an environment that users enjoy looking at when opening a browser. We hope to enhance people’s computer experience and mental well being through our web app display.
Link to our website: http://gradient-background-generator.herokuapp.com/
Process
As we worked to develop this project, we came to several points at which we realized that we should change our approach.
For example, we started off thinking we would use a lot more Javascript than we actually ended up using. This page that you are currently on has no Python, and is just HTML, CSS, and Javascript. Originally, we were planning on generating an image from Python with a clear background, and then displaying it over this page. Unfortunately, when we attempted this approach, the image behaved as though it had an opaque white background instead of a clear one, so we were unable to see the gradient background through the image. So, we ended up taking screenshots of all the different gradient backgrounds created with Javascript and CSS, adding the foreground on top of these images in Python, and then displaying the final image as the background in the output page.
We also ended up using Flask, a web framework for Python, for things that we originally were planning to use Javascript for, such as passing the user’s selected scene into the part of the program that generates and image.
Implementation
This project relies on several different components working together.
We used Flask, a web framework for Python, to tie together the Python and web components of this project. The welcome screen you see here allows users to enter which scene they want. Once they click submit, the html form sends the user’s choice of scene, as well as their local time and the dimensions of their screen to Flask, which then calls upon the function to generate the image, and save it to a local directory. Then, the Flask passes the name of the image file to output page, which displays the image as a background.
The first layer to the program takes the date from the Flask form and opens a gradient image generated in CSS corresponding to that hour. It also reads scene choice from the Flask form and opens a middleground image corresponding to that scene and chooses a list of random objects corresponding to that scene. A random number generator is used to select a random subset of images from that list. Those images are then altered to remove whitespace and apply a color overlay to the image based on the time of day. The random images are then pasted onto the middleground at a randomly generated position within the range of the screen and then this compressed image is pasted onto the background.
Results
We made a video showing the functionality and use of our program, which can be found here.
Impacts and Privacy
Although this website does use the user’s time zone, and therefore some vague information about their location, the program does not store that data at all, so there is no need to worry about anyone stealing or using that data for malicious purposes. And although we intended our project to help people connect more with the outdoors and keep track of the time of day, our project might have the unintended consequence of replacing outdoor time, which would not be healthy. However, we believe that the benefits will outweigh the risks.
The Future of this Project
If we had more time to work on this, we would make some more different backgrounds, and perhaps include animation or some interactive element on the webpage. We would also want to improve our image placement, and get the random element of our program to work on Heroku.
About Us
Note: we are not actually fish.
Katie is a student in the class of 2022 at Olin College of Engineering studying Computing. On this project, she focused on making the website, integrating the website with Flask, and getting the whole project online using Heroku. In her free time, she can be found rock climbing and spinning fire as part of Olin’s Fire Arts Club.
Anne is an undergraduate studying Business IT Management and Electrical Engineering. In this project Anne worked on integrating and editing images on multiple layers to create final scenery through Python. Anne enjoys working on professional photography, working on ventures, and meditating during her free time.
Shirin, an Olin College class of 2022 student, is majoring in Biomedical Engineering with a focus in Computer Science. She enjoys exploring the intersection of software design with other areas of study, such as medicine, human sentiment, and aesthetic design. On this project, she focused on integrating the python backend elements and debugging integration errors with the web app frontend. Aside from engineering, she has a passion for dance - dancing both for the Babson College Dance Ensemble and for NNKB Dance Academy in Johns Creek, Georgia as an alumna.
User Instructions
If you want to see our website, just click here.
But if you want to fork our code and get it working on your own computer, you can fork or clone our repository here.
In order to get it running, you will need to install the PIL image library, Flask, and python-resize-image by typing the following commands into the Linux command line:
$ pip install Pillow
$ pip install Flask
$ pip install python-resize-image
Sources
Here are the links to where we got most of the images:
beachball
bag
sandandwater
Yew
fernplant
ferret
Flyingsquirrel
Fox1
hummingbird
jackrabbit
Fern
Driftwood3
FennecFox
Flowershrub
Yew
forest_sillhouette
Poppies
MountainGoat
Wildflowers2
Wildflowers3
Treee
tree2
trees
mountain1
mountain2
bunny
yew
Starfish2
Starfish
Shrubby
Sanddollar2
Plant
optimisticlizard
mushroom2
mushroom
grumpylizard
Lizard4
hermitcrab
hermitcrab2
Fred(merecat)
Georgey(merecat)
Plant2
Plant4
Forest1
Plant3
yucca
wildcat1
wildcat2
wallace
spikes
lizardlizarding
lizard2
cactflowery
We got the colors that were used in the gradient background by taking color samples off this time lapse video.
The stars were taken directly from Lunar Logic’s Auroral Animated Background Gradients. The moon is based off the code for the stars, but modified. Here is the link to Lunar Logic’s repository.


Cailean Cooney, Harlan Kellaway, Gioia Stevens, & Stephen Zweibel
Is it a field?
Definition?
New: 20 years
Humanities Computing -> Digital Humanities
Using computational methods for humanistic inquiry
Community
Professional apparatus
Methodology
Require specialized knowledge to install, configure, and use
Resources (including hardware, technical support, institutional backing) are often limited
Requesting server space from IT Dept.
Downloading software
Sifting through installation documentation
Dealing with firewalls and operating system configurations
A virtual linux computer with all the bells
and whistles of a traditional computer
Tap into this system via a wireless or network server
A Domain of One's Own at University of Mary Washington
umwdomains.com
"Reclaim the web"
"Take control of your digital identity"
Alpha/Beta phase...would you like to test?
Hosted service
A browser and an internet connection
Faculty who have experience with one or more
of the applications included in DH Box:
Stephen Zweibel @stevezweibel
Cailean Cooney @_csmcc
Harlan Kellaway @DigiHumanatee
Gioia Stevens @gioiastevens


Description
The dataset contains weekly dengue data for the San Juan-Carolina-Caguas Metropolitan Statistical Area. The dataset includes the following variables:
- season: the transmission season;
- season_week: week of the season (not the calendar year - the season starts following the week with historically lowest dengue cases over the years 1990-2009);
- week_start_date: date of the first day of the week;
- denv1_cases: number of laboratory confirmed cases with DENV1;
- denv2_cases: number of laboratory confirmed cases with DENV2;
- denv3_cases: number of laboratory confirmed cases with DENV3;
- denv4_cases: number of laboratory confirmed cases with DENV4;
- other_positive_cases: laboratory-positive cases without serotype identified (these include acute IgM positive and IgM conversions);
- additional_cases: at times not all specimens submitted were tested due to overload of the capacity for testing or incomplete case information. For those weeks, the number of additional laboratory-positive cases among those not tested was estimated by multiplying the number of untested cases by the rate of laboratory-positive cases amongst those that were tested;
- total_cases: the sum of all cases (denv1-4_cases + other_positive_cases + additional_cases), the target time series for forecasting.
Over time, the sensitivity of testing increased, particularly in 2005 when PCR was implemented for routine diagnostics, in 2007 when improved IgM testing was implemented, and in 2009 when a more sensitive PCR assay was adopted. Details are presented in Sharp et al. 2010.
Sharp TM, Hunsperger E, Santiago GA, Muñoz-Jordan JL, Santiago LM, Rivera A, et al. (2013)
Virus-Specific Differences in Rates of Disease during the 2010 Dengue Epidemic in Puerto Rico. PLoS Negl Trop Dis 7(4): e2159. doi:10.1371/journal.pntd.0002159
Spatial
San Juan-Carolina-Caguas Metropolitan Statistical Area including the municipalities of Aguas Buenas, Aibonito, Barceloneta, Barranquitas, Bayamón, Caguas, Canóvanas, Carolina, Cataño, Cayey, Ceiba, Ciales, Cidra, Comerío, Corozal, Dorado, Fajardo, Florida, Guaynabo, Gurabo, Humacao, Juncos, Las Piedras, Loíza, Luquillo, Manatí, Maunabo, Morovis, Naguabo, Naranjito, Orocovis, Río Grande, San Juan, San Lorenzo, Toa Alta, Toa Baja, Trujillo Alto, Vega Alta, Vega Baja, and Yabucoa.


Profiling Your Model¶
Profiling is used to determine how optimization will affect performance and loss.
A performance profile provides an indication of the effect of model optimizations on the inference performance of the model. In addition, it provides detailed performance information for the model without any optimizations. The profile looks at a detailed view of how fast each layer is running and how much time it is taking as well as how much time can be optimized.
A loss profile is an indication of the effect of optimization on the loss. It shows how each layer is likely to affect the loss when model optimizations such as pruning are applied to it. The loss profile also shows how many parameters there are in the model.
Note: If you change information on this dialog and then click BACK, the changes are retained when you return to this dialog.
You can select both Performance and Loss for profiling. In general, both should be run and, as such, both are selected by default.
You may opt to disable the Performance option if the model is large and will require numerous executions that will take considerable time. In this case, the performance profile will be approximated from the architecture as a FLOPS (floating point operations per second) profile. A FLOPS profile is a theoretical measure of performance.
If you are just benchmarking the model, you may disable both the Performance and Loss options. In this case, both profiles will be approximated from the architecture.
Enter names for the performance and loss profiles. These names will be referenced throughout Sparsify to quickly identify your profiles.
Further describe the Performance profile for the target deployment:
Batch size of the inputs to be used with the model. For example, you might enter 1 if you are running real-time object detection. If you are running a throughput use case, batch size depends on your domain and use case (64 is common for image classification).
Number of CPU cores on which to run the model.
You should enter the batch size and core count to which you will deploy. Sparsify will run with this batch size and core count and apply the optimizations to the model to see how the performance is being changed. Batch size and core count can affect how Sparsify runs the model and how fast it is run; therefore, they affect how Sparsify optimizes the model.
Note: Eventually, you might want to run multiple performance profiles by Adding a New Performance Profile. For example, if you are unsure of how you will deploy, you might want to consider various optimization schemes. Or, you may want multiple performance profiles because you deploy a model in multiple ways (such as a throughput offline and latency online).
Click RUN and a message will indicate that the system is profiling the performance and/or loss.
When all metrics are generated, the New Project Setup dialog is grayed out. For example:
Click COMPLETE. The performance profile will be displayed, as described in Reviewing Performance Profiles.
Next steps…
Continue by reviewing your Performance Profiles and Loss Profiles. Then, you will be ready to Optimize.


フロー furoBEC #
The furo build essentials container. #
This container contains all tools you need to work with a furo spec project.
Usage #
Bash mode #
docker run -it --rm -v `pwd`:/specs thenorstroem/furo-bec
# do your stuff
# type exit to quit
exit
Command mode #
This will run spectools with the configured flow build.
docker run -it --rm -v `pwd`:/specs thenorstroem/furo-bec build
TIPP: If your spectools commands have to access different directories, do not forget to mount them.
Installed Tools #
- golang
- git
- protoc
- protoc-gen-grpc-gateway (v2)
- protoc-gen-openapiv2
- protoc-gen-go
- protoc-gen-go-grpc
- simple-generator
- spectools
- furoc
No furoc generators are installed. Add the needed furoc-gen-XXX to the
.furobecrc
file. Or build a image based on this one.


Last updated December 29, 20201
Version 0.4.0
1. Bug Fixes and Calendar Performace Improvements
Version 0.3.0
1. All New IITDApp is here!!!