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MTV Stings
A series of three Stings designed for an auidence of car park attendants and to be aired on MTV. This project was designed in collaboration with Andrew Milligan and Hannah Guilfoyle.
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Drowning Mona * * (out of * * * * )
Directed by Nick Gomez. Cast: Danny DeVito, Neve Campbell, Casey Affleck, Jamie Lee Curtis, William Fichtner, Marcus Thomas, Bette Midler, Peter Dobson, Kathleen Wilhoite, Will Ferrell, Tracey Walter. 2000 - 91 minutes Rated PG-13 (for mild violence and profanity). Reviewed by Dustin Putman, March 4, 2000.
Nick Gomez's "Drowning Mona" displays an ensemble of interesting and inventive characters in search of a sharper, more focused screenplay than the one they have been given. Hand it to the bright, exciting cast for giving it their all (and they are all obviously having a blast with their roles), but the script, by Peter Steinfeld, aimlessly wanders around between them, not knowing where it is going, and resting its rooting interest on the tepid whodunit plotline.
Mona Dearly (Bette Midler) is the most despised wench living in the small white trash town of Verplanck, New York, which was the testing site years ago for the Yugo car company. When she is unable to put on her brakes and flies right over the cliff and into a watery grave in the opening scene, suspicions are aroused by Chief Wyatt Rash (Danny DeVito) when he learns the brake lines had been intentionally cut. Soon, everyone even remotely related to the maniacal Mona is a suspect, including her husband Phil (William Fichtner) and her son Jeff (Marcus Thomas), both of which hated her as much as everyone else. Jeff is landscaping partners with Bobby Calzone (Casey Affleck), who was consistently verbally and even physically battered by Mona, and he is about to marry the pretty, tough-spoken Ellen (Neve Campbell). Having an affair with both Phil and Jeff is Rona (Jamie Lee Curtis), the straightforward waitress at the local diner, who also may or may not have killed Mona because she wanted Mona's family to herself.
At just 91 minutes, "Drowning Mona" feels drug out, and one of the reasons for this is that the film always seems like it is finally going to take off with its story, and in the interactions of the Verplanck inhabitants, but it never truly does. Occasionally, there will be a spark of wit and originality, as when Rona and Phil, meeting at their usual hotel room for a tryst, use the "Wheel of Fortune" game as foreplay. But more often than not, the humor just isn't edgy enough to work the way it should, and at least one of the detractors of this is its bothersome PG-13 rating when it very well could have been R, and probably a whole lot funnier. That isn't to say the film has no laughs; one scene, in particular, drove me to tears, and I missed the whole next scene because I couldn't get over the previous one. Too bad the laughs are relatively few and far between.
Advertised as one of the major stars of the picture, Bette Midler actually only pops up sporadically, and even then it is only for a minute or two each time, via flashbacks that are supposed to present her as this evil woman, but fails. Sure, she has a hot temper, but she doesn't seem all that bad, and in the one good flashback sequence Midler is given, Mona loses at a knife-throwing contest and expresses her frustration for not ever being a winner at anything in her life. Otherwise, Midler is sorely underused, but at least better than she was in the recent stinker, "Isn't She Great."
Of the rest of the cast, only Danny DeVito is disappointing, not because of his performance, but because his character is the one that gets very few funny things to say. The high points are most certainly Neve Campbell, who is shaping up to be a promising major talent in Hollywood, if only she starts to choose her projects a little more wisely (her upcoming Sundance hit, "Panic," co-starring William H. Macy, is a good start), and especially Jamie Lee Curtis, who it is nice to see again after not appearing in a feature film in over a year. Curtis joyously gets right into her character, and the film always gains the most mileage out of her appearances. And Will Ferrell, as a balding mortician with a taste for taking kinky pictures of scantily clad women in his backroom, demonstrates his sheer comic timing to his few scenes.
Undoubtedly made on a limited budget, the cinematography, by Bruce Douglas Johnson, is particularly flat for a wide-release motion picture, and after seeing his 1997 misfire, "Illtown," and now the superior, but still not very good "Drowning Mona," it is safe to say director Gomez is never going to be winning any Oscars. Relying on the performances alone, try as they might, they simply cannot withhold the weight of the film all by themselves. "Drowning Mona" has promise, and it has occasional flare, but for the most part, it is a string of missed opportunities.
- Copyright 2000 by Dustin Putman Http://www.young-hollywood.com Http://www.atnzone.com
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This part prescribes acquisition policies and procedures supporting the Government’s program for ensuring a drug-free workplace, for protecting and improving the quality of the environment, and to foster markets for sustainable technologies, materials, products, and services, and encouraging the safe operation of vehicles by—
(a) Reducing or preventing pollution;
(b) Managing efficiently and reducing energy and water use in Government facilities;
(c) Using renewable energy and renewable energy technologies;
(d) Acquiring energy-efficient and water-efficient products and services, environmentally preferable (including EPEAT®-registered, and non-toxic and less toxic) products, products containing recovered materials, biobased products, non-ozone-depleting products, and products and services that minimize or eliminate, when feasible, the use, release, or emission of high global warming potential hydrofluorocarbons, such as by using reclaimed instead of virgin hydrofluorocarbons;
(e) Requiring contractors to identify hazardous materials;
(f) Encouraging contractors to adopt and enforce policies that ban text messaging while driving; and
(g) Requiring contractors to comply with agency environmental management systems.
As used in this part—
“Environmental” means environmental aspects of internal agency operations and activities, including those aspects related to energy and transportation functions.
“Greenhouse gases” means carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride.
“Toxic chemical” means a chemical or chemical category listed in 40 CFR 372.65.
“United States”, except as used in subpart 23.10, means—
(1) The fifty States;
(2) The District of Columbia;
(3) The commonwealths of Puerto Rico and the Northern Mariana Islands;
(4) The territories of Guam, American Samoa, and the United States Virgin Islands; and
(5) Associated territorial waters and airspace.
Executive Order 13423 sections 3(e) and (f) require that contracts for contractor operation of a Government-owned or -leased facility and contracts for support services at a Government-owned or -operated facility include provisions that obligate the contractor to comply with the requirements of the order to the same extent as the agency would be required to comply if the agency operated or supported the facility. Compliance includes developing programs to promote and implement cost-effective waste reduction.
As used in this subpart—
“Contract action” means any oral or written action that results in the purchase, rent, or lease of supplies or equipment, services, or construction using appropriated dollars, including purchases below the micro-purchase threshold. Contract action does not include grants, cooperative agreements, other transactions, real property leases, requisitions from Federal stock, training authorizations, or other non-FAR based transactions.
(a) Executive Order 13423 of January 24, 2007, Strengthening Federal Environmental, Energy, and Transportation Management.
(b) Executive Order 13514 of October 5, 2009, Federal Leadership in Environmental, Energy, and Economic Performance.
(c) All of the authorities specified in subparts 23.2, 23.4, 23.7, 23.8, 23.9, and 23.10.
(a) Federal agencies shall advance sustainable acquisition by ensuring that 95 percent of new contract actions for the supply of products and for the acquisition of services (including construction) require that the products are—
(1) Energy-efficient (ENERGY STAR® or Federal Energy Management Program (FEMP)-designated);
(2) Water-efficient;
(3) Biobased;
(4) Environmentally preferable (e.g., EPEAT®-registered, or non-toxic or less toxic alternatives);
(5) Non-ozone depleting; or
(6) Made with recovered materials.
(b) The required products in the contract actions for services include products that are—
(1) Delivered to the Government during performance;
(2) Acquired by the contractor for use in performing services at a Federally-controlled facility; or
(3) Furnished by the contractor for use by the Government.
(c) The required products in the contract actions must meet agency performance requirements.
(d) For purposes of meeting the 95 percent sustainable acquisition requirement, the term “contract actions” includes new contracts (and task and delivery orders placed against them) and new task and delivery orders on existing contracts.
This subpart does not apply to the following acquisitions:
(a) Contracts performed outside of the United States, unless the agency head determines that such application is in the interest of the United States.
(b) Weapon systems.
(a) The head of an agency may exempt—
(1) Intelligence activities of the United States, and related personnel, resources, and facilities, to the extent the Director of National Intelligence or agency head determines it necessary to protect intelligence sources and methods from unauthorized disclosure;
(2) Law enforcement activities of that agency and related personnel, resources, and facilities, to the extent the head of an agency determines it necessary to protect undercover operations from unauthorized disclosure;
(3) Law enforcement, protective, emergency response, or military tactical vehicle fleets of that agency; and
(4) Agency activities and facilities in the interest of national security.
(b) If the head of the agency issues an exemption under paragraph (a) of this section, the agency must notify the Chair of the Council on Environmental Quality in writing within 30 days of the issuance of the exemption.
(c) The agency head may submit through the Chair of the Council on Environmental Quality a request for exemption of an agency activity other than those activities listed in paragraph (a) of this section and related personnel, resources, and facilities.


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Morning Maple Muffins★
- 16 muffins
- 30 mins.
- Taste of Home
- Sweet
2 cups
all-purpose flour1/2 cup
packed brown sugar2 tsp.
baking powder1/2 tsp.
salt3/4 cup
2% milk1/2 cup
butter, melted1/2 cup
maple syrup1/4 cup
sour cream1
large egg, room temperature1/2 tsp.
vanilla extract- Toppings:
3 tbsp.
all-purpose flour3 tbsp.
sugar2 tbsp.
chopped nuts1/2 tsp.
ground cinnamon2 tbsp.
cold butter
2 cups
all-purpose flour1/2 cup
packed brown sugar2 tsp.
baking powder1/2 tsp.
salt
Preheat oven to 400°. In a large bowl, combine flour, brown sugar, baking powder and salt.
3/4 cup
2% milk1/2 cup
butter, melted1/2 cup
maple syrup1/4 cup
sour cream1
large egg, room temperature1/2 tsp.
vanilla extract
In another bowl, combine milk, butter, syrup, sour cream, egg and vanilla. Stir into dry ingredients just until moistened.
Fill greased or paper-lined muffin cups two-thirds full.
3 tbsp.
all-purpose flour3 tbsp.
sugar2 tbsp.
chopped nuts1/2 tsp.
ground cinnamon2 tbsp.
cold butter
For topping, combine flour, sugar, nuts and cinnamon; cut in butter until crumbly. Sprinkle over batter.
Bake 16-20 minutes or until a toothpick inserted in center comes out clean. Cool 5 minutes before removing from pans to wire racks. Serve warm.


SP consoles family members of road accident victims
Two minutes’ silence observed in honour of the deceased
by Staff ReporterSuperintendent of Police R.N. Ammi Reddy consoled the families that had lost their dear ones in various accidents on World Remembrance Day on Sunday. Along with other police officials, he observed two minutes’ silence as a mark of respect to the deceased.
Recently, an elderly woman Kamalamma lost her life in an accident while crossing the road near Palakonda.
A teenaged boy Santosh died on the spot near Krishnapuram of Ponduru mandal while going to wish her sister on Rakhi.
One Krishna Rao had fallen down from an autorickshaw due to alleged negligence of the driver.
Their family members explained their ordeals and financial distress after the untimely death of their dear ones.
Mr. Ammi Reddy promised to extend maximum help and payment of insurance amount through Lok Adalat as early as possible. He urged people to have awareness on road safety to prevent accidents.


NightWalker is a clothing line dedicated to technology, fashion and the Retro-Future. As you probably can tell, we love color and the style of the 1980s.
We also love hearing from our customers.
If you have any questions or comments, please reach out and contact us
This web app was designed and developed by the same people that designed the First Flavors Collection itself. It was created using open source software. After every purchase, a donation is made to one of the following organizations behind that software:


{% extends "base.html" %} {% block title %}Administration - {% endblock %} {% block content %}
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They say bacon is good with everything, and it shows here!
4 Chicken fingers with your choice of BBQ, ranch, honey mustard, or blue cheese dipping sauce
4 Chicken fingers drenched in buffalo hot sauce with your choice of ranch or blue cheese dipping sauce
3 Chicken fingers with a heaping pile of fries or onion rings. Also includes your choice of dipping sauce


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(., HEV vaccination transmission data vaccine hepatitis .). infectious model Model infection []. mortality pregnant prior water cases environmental mean period virus assumed number estimated different {border-style models population reported Hepatitis outbreak px;} #ffffff;} given potential reductions baseline latent reactive women camps days epidemic reservoir used doses immunity impact camp infected pre-emptive rate sanitation study Health Medicine assumptions dose effectiveness important parameters saturating shedding (Model associated posterior proportion using weeks Gamma Sciences acute additional based distribution distributions estimates evidence outbreaks persistence reproduction risk Infect Madi Table analysis consistent corresponds derived effect environment high intervention large people single sources symptomatic viral Beta(., Dis. Prior age aged case contamination data. deaths displaced effective infections parameter periods px; rates results second sensitivity shape shown strategies viable years {font-family Click Fig LINK Proportion evaluate faecal file. font-size genotype groups individuals patients person priors relative settings studies threshold values (.,.) (Fig Biology Clin Mean Paloga Uganda United Viral WATSAN account assuming basic clinical disease double; drinking effects efficacy emergency epidemiological fitting genotypes herd interventions observed obtained patient performed person-to-person possible previous reduced route scale similar start time use work (.%, (Table (days) .%) :SEIRW Lancet. Models Rate Rein Research Time Vaccine ZhangJ, Zhu [,]. []; allow available border-color border-width camps. cause days) did duration fact fecal higher immune importance indicate information informative likely loss mode p(mean pathogens phase quantify reduce represented role solid; value vary week withshape {font-style {font-weight (Models (PDF) (i.e. .); .)p: ./S-()- ./journal.pntd..tTable .w: Asia CrI Data However, HuangSJ, IDP Immunology: Population Sudan, Tropical Uganda. Vaccination WangZZ, ZhangXF, [], accounting analysis. bold camp-specific cases, complex considered correspond courier; direct em; estimate excluding expected explicitly extended findings gave household increase infection, infection. initially known little lower modelling negative new occurring percentage period, persons pt;} range recent recorded respectively. review shows simulations sporadic suggest transmission. vaccination, vaccination.


2 Samuel 15:31
And one told David, saying, Ahithophel is among the conspirators with Absalom. And David said, O LORD, I pray thee, turn the counsel of Ahithophel into foolishness.


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rwlman − RWP*Load Simulator overview of rwl man pages
rwlman
rwlman page
The rwlman command without any options shows this overview of the man pages for the RWP*Load Simulator, rwloadsim. As a whole, these man pages constitute the reference manual for rwloadsim. This reference manual is split into four major parts with the following top pages:
rwloadsim
The reference manual for the actual rwloadsim executable.
rwlprogram
The reference manual for the rwl programming language.
directive
The reference manual for the directives used to modify the behavior of rwloadsim.
statistics
This page describes how rwloadsim saves execution statistics.
The rwlman script simply calls the normal man(3) utility with a proper MANPATH setting. Although possible, you are recommended not copying the man pages to your normal man page location such as /usr/share/man
The primary developer and maintainer of the RWP*Load Simulator and its man pages is Bjørn Kisbye Engsig. The preferred way to contact him about rwloadsim is via the issues page on github.
Copyright © 2021 Oracle Corporation
Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl
rwl(1rwl), rwloadsim(1rwl), directive(1rwl), statistics(1rwl), bengsig(1rwl)


hcash
2.0.0
hcash
libraries
blockchain
Namespaces
PropertyEntry.cpp File Reference
#include <
blockchain/ChainInterface.hpp
>
#include <
blockchain/PropertyEntry.hpp
>
Include dependency graph for PropertyEntry.cpp:
Namespaces
hsrcore
hsrcore::blockchain
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GDC 2020 debuts new Summit to help devs find funding and forge deals!
by StaffToday GDC organizers are excited to announce that a new Summit focused on the art and business of funding game development will be making its debut at GDC 2020 in San Francisco!
This new Game Funding & Investment Summit is aimed at making GDC attendees’ professional lives easier by providing a focal point for discussions of game, project, and company funding.
Featuring speakers and panelists from the venture capital, angel/seed, and project funding areas, this Summit will leave attendees with the knowledge to raise funding and forge partnerships to build your company or game, as well as tips and takeaways for active investors in the space.
The game industry is dynamic, driven by new business models and opportunities, and at the new GDC 2020 Game Funding & Investment Summit you can expect advice on how to capitalize on that to achieve your goals!
Next year GDC 2020 runs from Monday, March 16th through Friday, March 20th. This will be the 34th edition of GDC, and now that registration is officially open, you'll want to take a look at the (ever-growing) session schedule and your GDC pass options. This new Game Funding & Investment Summit will take place alongside the other 20+ Summits held Monday and Tuesday of GDC 2020, with speakers and sessions to be announced!
For more details on GDC 2020 visit the show's official website, or subscribe to regular updates via Facebook, Twitter, or RSS.
Gamasutra and GDC are sibling organizations under parent company Informa Tech


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problems package¶
Submodules¶
problems.cntnv_max_profit module¶
Summary¶
Maximize the expected profit for the continuous newsvendor problem.
-
class
problems.cntnv_max_profit.
CntNVMaxProfit
(fixed_factors={}, oracle_fixed_factors={})¶ Bases:
base.Problem
Base class to implement simulation-optimization problems.
-
name
¶ name of problem
- Type
string
-
minmax
¶ indicator of maximization (+1) or minimization (-1) for each objective
- Type
tuple of int (+/- 1)
-
constraint_type
¶ - description of constraints types:
“unconstrained”, “box”, “deterministic”, “stochastic”
- Type
string
-
variable_type
¶ - description of variable types:
“discrete”, “continuous”, “mixed”
- Type
string
-
oracle
¶ associated simulation oracle that generates replications
- Type
Oracle object
-
rng_list
¶ list of RNGs used to generate a random initial solution or a random problem instance
- Type
list of rng.MRG32k3a objects
- Parameters
fixed_factors (dict) – dictionary of user-specified problem factors
factors (oracle_fixed) – subset of user-specified non-decision factors to pass through to the oracle
See also
-
check_deterministic_constraints
(x)¶ Check if a solution x satisfies the problem’s deterministic constraints.
-
deterministic_objectives_and_gradients
(x)¶ Compute deterministic components of objectives for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_objectives (tuple) – vector of deterministic components of objectives
det_objectives_gradients (tuple) – vector of gradients of deterministic components of objectives
-
deterministic_stochastic_constraints_and_gradients
(x)¶ Compute deterministic components of stochastic constraints for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_stoch_constraints (tuple) – vector of deterministic components of stochastic constraints
det_stoch_constraints_gradients (tuple) – vector of gradients of deterministic components of stochastic constraints
-
factor_dict_to_vector
(factor_dict)¶ Convert a dictionary with factor keys to a vector of variables.
- Parameters
factor_dict (dictionary) – dictionary with factor keys and associated values
- Returns
vector – vector of values associated with decision variables
- Return type
-
get_random_solution
(rand_sol_rng)¶ Generate a random solution for starting or restarting solvers.
- Parameters
rand_sol_rng (rng.MRG32k3a object) – random-number generator used to sample a new random solution
- Returns
x – vector of decision variables
- Return type
-
response_dict_to_objectives
(response_dict)¶ Convert a dictionary with response keys to a vector of objectives.
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
objectives – vector of objectives
- Return type
-
response_dict_to_stoch_constraints
(response_dict)¶ Convert a dictionary with response keys to a vector of left-hand sides of stochastic constraints: E[Y] >= 0
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
stoch_constraints – vector of LHSs of stochastic constraint
- Return type
-
problems.facilitysizing_max_service module¶
Summary¶
Maximize the probability of not stocking out subject to a budget constraint on the total cost of installing capacity.
-
class
problems.facilitysizing_max_service.
FacilitySizingMaxService
(fixed_factors={}, oracle_fixed_factors={})¶ Bases:
base.Problem
Base class to implement simulation-optimization problems.
-
name
¶ name of problem
- Type
string
-
minmax
¶ indicator of maximization (+1) or minimization (-1) for each objective
- Type
tuple of int (+/- 1)
-
constraint_type
¶ - description of constraints types:
“unconstrained”, “box”, “deterministic”, “stochastic”
- Type
string
-
variable_type
¶ - description of variable types:
“discrete”, “continuous”, “mixed”
- Type
string
-
oracle
¶ associated simulation oracle that generates replications
- Type
Oracle object
-
rng_list
¶ list of RNGs used to generate a random initial solution or a random problem instance
- Type
list of rng.MRG32k3a objects
- Parameters
fixed_factors (dict) – dictionary of user-specified problem factors
factors (oracle_fixed) – subset of user-specified non-decision factors to pass through to the oracle
See also
-
check_deterministic_constraints
(x)¶ Check if a solution x satisfies the problem’s deterministic constraints.
-
deterministic_objectives_and_gradients
(x)¶ Compute deterministic components of objectives for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_objectives (tuple) – vector of deterministic components of objectives
det_objectives_gradients (tuple) – vector of gradients of deterministic components of objectives
-
deterministic_stochastic_constraints_and_gradients
(x)¶ Compute deterministic components of stochastic constraints for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_stoch_constraints (tuple) – vector of deterministic components of stochastic constraints
det_stoch_constraints_gradients (tuple) – vector of gradients of deterministic components of stochastic constraints
-
factor_dict_to_vector
(factor_dict)¶ Convert a dictionary with factor keys to a vector of variables.
- Parameters
factor_dict (dictionary) – dictionary with factor keys and associated values
- Returns
vector – vector of values associated with decision variables
- Return type
-
get_random_solution
(rand_sol_rng)¶ Generate a random solution for starting or restarting solvers.
- Parameters
rand_sol_rng (rng.MRG32k3a object) – random-number generator used to sample a new random solution
- Returns
x – vector of decision variables
- Return type
-
response_dict_to_objectives
(response_dict)¶ Convert a dictionary with response keys to a vector of objectives.
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
objectives – vector of objectives
- Return type
-
response_dict_to_stoch_constraints
(response_dict)¶ Convert a dictionary with response keys to a vector of left-hand sides of stochastic constraints: E[Y] >= 0
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
stoch_constraints – vector of LHSs of stochastic constraint
- Return type
-
problems.facilitysizing_totalcost module¶
Summary¶
Minimize the (deterministic) total cost of installing capacity at facilities subject to a chance constraint on stockout probability.
-
class
problems.facilitysizing_totalcost.
FacilitySizingTotalCost
(fixed_factors={}, oracle_fixed_factors={})¶ Bases:
base.Problem
Base class to implement simulation-optimization problems.
-
name
¶ name of problem
- Type
string
-
minmax
¶ indicator of maximization (+1) or minimization (-1) for each objective
- Type
tuple of int (+/- 1)
-
constraint_type
¶ - description of constraints types:
“unconstrained”, “box”, “deterministic”, “stochastic”
- Type
string
-
variable_type
¶ - description of variable types:
“discrete”, “continuous”, “mixed”
- Type
string
-
oracle
¶ associated simulation oracle that generates replications
- Type
Oracle object
-
rng_list
¶ list of RNGs used to generate a random initial solution or a random problem instance
- Type
list of rng.MRG32k3a objects
- Parameters
fixed_factors (dict) – dictionary of user-specified problem factors
factors (oracle_fixed) – subset of user-specified non-decision factors to pass through to the oracle
See also
-
check_deterministic_constraints
(x)¶ Check if a solution x satisfies the problem’s deterministic constraints.
-
deterministic_objectives_and_gradients
(x)¶ Compute deterministic components of objectives for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_objectives (tuple) – vector of deterministic components of objectives
det_objectives_gradients (tuple) – vector of gradients of deterministic components of objectives
-
deterministic_stochastic_constraints_and_gradients
(x)¶ Compute deterministic components of stochastic constraints for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_stoch_constraints (tuple) – vector of deterministic components of stochastic constraints
det_stoch_constraints_gradients (tuple) – vector of gradients of deterministic components of stochastic constraints
-
factor_dict_to_vector
(factor_dict)¶ Convert a dictionary with factor keys to a vector of variables.
- Parameters
factor_dict (dictionary) – dictionary with factor keys and associated values
- Returns
vector – vector of values associated with decision variables
- Return type
-
get_random_solution
(rand_sol_rng)¶ Generate a random solution for starting or restarting solvers.
- Parameters
rand_sol_rng (rng.MRG32k3a object) – random-number generator used to sample a new random solution
- Returns
x – vector of decision variables
- Return type
-
response_dict_to_objectives
(response_dict)¶ Convert a dictionary with response keys to a vector of objectives.
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
objectives – vector of objectives
- Return type
-
response_dict_to_stoch_constraints
(response_dict)¶ Convert a dictionary with response keys to a vector of left-hand sides of stochastic constraints: E[Y] >= 0
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
stoch_constraints – vector of LHSs of stochastic constraint
- Return type
-
problems.mm1_min_mean_sojourn_time module¶
Summary¶
Minimize the mean sojourn time of an M/M/1 queue.
-
class
problems.mm1_min_mean_sojourn_time.
MM1MinMeanSojournTime
(fixed_factors={}, oracle_fixed_factors={})¶ Bases:
base.Problem
Base class to implement simulation-optimization problems.
-
name
¶ name of problem
- Type
string
-
minmax
¶ indicator of maximization (+1) or minimization (-1) for each objective
- Type
tuple of int (+/- 1)
-
constraint_type
¶ - description of constraints types:
“unconstrained”, “box”, “deterministic”, “stochastic”
- Type
string
-
variable_type
¶ - description of variable types:
“discrete”, “continuous”, “mixed”
- Type
string
-
oracle
¶ associated simulation oracle that generates replications
- Type
Oracle object
-
rng_list
¶ list of RNGs used to generate a random initial solution or a random problem instance
- Type
list of rng.MRG32k3a objects
- Parameters
See also
-
check_deterministic_constraints
(x)¶ Check if a solution x satisfies the problem’s deterministic constraints.
-
deterministic_objectives_and_gradients
(x)¶ Compute deterministic components of objectives for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_objectives (tuple) – vector of deterministic components of objectives
det_objectives_gradients (tuple) – vector of gradients of deterministic components of objectives
-
deterministic_stochastic_constraints_and_gradients
(x)¶ Compute deterministic components of stochastic constraints for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_stoch_constraints (tuple) – vector of deterministic components of stochastic constraints
det_stoch_constraints_gradients (tuple) – vector of gradients of deterministic components of stochastic constraints
-
factor_dict_to_vector
(factor_dict)¶ Convert a dictionary with factor keys to a vector of variables.
- Parameters
factor_dict (dictionary) – dictionary with factor keys and associated values
- Returns
vector – vector of values associated with decision variables
- Return type
-
get_random_solution
(rand_sol_rng)¶ Generate a random solution for starting or restarting solvers.
- Parameters
rand_sol_rng (rng.MRG32k3a object) – random-number generator used to sample a new random solution
- Returns
x – vector of decision variables
- Return type
-
response_dict_to_objectives
(response_dict)¶ Convert a dictionary with response keys to a vector of objectives.
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
objectives – vector of objectives
- Return type
-
response_dict_to_stoch_constraints
(response_dict)¶ Convert a dictionary with response keys to a vector of left-hand sides of stochastic constraints: E[Y] >= 0
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
stoch_constraints – vector of LHSs of stochastic constraint
- Return type
-
problems.rmitd_maxrevenue module¶
Summary¶
Maximize the total revenue of a multi-stage revenue management with inter-temporal dependence problem.
-
class
problems.rmitd_maxrevenue.
RMITDMaxRevenue
(fixed_factors={}, oracle_fixed_factors={})¶ Bases:
base.Problem
Base class to implement simulation-optimization problems.
-
name
¶ name of problem
- Type
string
-
minmax
¶ indicator of maximization (+1) or minimization (-1) for each objective
- Type
tuple of int (+/- 1)
-
constraint_type
¶ - description of constraints types:
“unconstrained”, “box”, “deterministic”, “stochastic”
- Type
string
-
variable_type
¶ - description of variable types:
“discrete”, “continuous”, “mixed”
- Type
string
-
oracle
¶ associated simulation oracle that generates replications
- Type
Oracle object
-
rng_list
¶ list of RNGs used to generate a random initial solution or a random problem instance
- Type
list of rng.MRG32k3a objects
- Parameters
See also
-
check_deterministic_constraints
(x)¶ Check if a solution x satisfies the problem’s deterministic constraints.
-
factor_dict_to_vector
(factor_dict)¶ Convert a dictionary with factor keys to a vector of variables.
- Parameters
factor_dict (dictionary) – dictionary with factor keys and associated values
- Returns
vector – vector of values associated with decision variables
- Return type
-
get_random_solution
(rand_sol_rng)¶ Generate a random solution for starting or restarting solvers.
- Parameters
rand_sol_rng (rng.MRG32k3a object) – random-number generator used to sample a new random solution
- Returns
x – vector of decision variables
- Return type
-
response_dict_to_objectives
(response_dict)¶ Convert a dictionary with response keys to a vector of objectives.
- Parameters
response_dict (dictionary) – dictionary with response keys and associated values
- Returns
objectives – vector of objectives
- Return type
-
problems.sscont_min_cost module¶
Summary¶
Minimize the expected total cost for (s, S) inventory system.
-
class
problems.sscont_min_cost.
SSContMinCost
(fixed_factors={}, oracle_fixed_factors={})¶ Bases:
base.Problem
Class to make (s,S) inventory simulation-optimization problems.
-
minmax
¶ indicator of maximization (+1) or minimization (-1) for each objective
- Type
tuple of int (+/- 1)
-
constraint_type
¶ - description of constraints types:
“unconstrained”, “box”, “deterministic”, “stochastic”
- Type
-
oracle
¶ associated simulation oracle that generates replications
- Type
-
rng_list
¶ list of RNGs used to generate a random initial solution or a random problem instance
- Type
- Parameters
fixed_factors (dict) – dictionary of user-specified problem factors
factors (oracle_fixed) – subset of user-specified non-decision factors to pass through to the oracle
See also
-
check_deterministic_constraints
(x)¶ Check if a solution x satisfies the problem’s deterministic constraints.
-
deterministic_objectives_and_gradients
(x)¶ Compute deterministic components of objectives for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_objectives (tuple) – vector of deterministic components of objectives
det_objectives_gradients (tuple) – vector of gradients of deterministic components of objectives
-
deterministic_stochastic_constraints_and_gradients
(x)¶ Compute deterministic components of stochastic constraints for a solution x.
- Parameters
x (tuple) – vector of decision variables
- Returns
det_stoch_constraints (tuple) – vector of deterministic components of stochastic constraints
det_stoch_constraints_gradients (tuple) – vector of gradients of deterministic components of stochastic constraints
-
factor_dict_to_vector
(factor_dict)¶ Convert a dictionary with factor keys to a vector of variables.
-
get_random_solution
(rand_sol_rng)¶ Generate a random solution for starting or restarting solvers.
- Parameters
rand_sol_rng (rng.mrg32k3a.MRG32k3a) – random-number generator used to sample a new random solution
- Returns
x – vector of decision variables
- Return type
-
response_dict_to_objectives
(response_dict)¶ Convert a dictionary with response keys to a vector of objectives.
-
response_dict_to_stoch_constraints
(response_dict)¶ Convert a dictionary with response keys to a vector of left-hand sides of stochastic constraints: E[Y] >= 0
-


---
subject: Xavier is Elite Again!
description: Xavier Men's Basketball earned its spot in the Elite 8 with a win over Arizona.
---
{{> header }}
{{> spacer size=32 }}
{{> spacer }}
Here are Eight Elite things to do to support your Musketeers:
- Tune in on Saturday, March 25, at 6:09 p.m. (EST) to TBS as the Musketeers face Gonzaga.
{{> spacer }}
- Watch the highlights from the Musketeer's win over Arizona.
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- Know that Xavier continues to push academic excellence with a string of 100 consecutive men's basketball seniors graduating from Xavier.
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- Update your Facebook or Twitter profile picture.
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- See what your fellow high school friends and Xavier fans are saying online about the Musketeers.
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- Continue to find out more about Xavier.
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- Continue the conversation online by sharing your thoughts and photos including everything that makes the Xavier community elite, indeed.
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- Schedule your next visit to campus. There is nothing like seeing our campus in person.
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50 Cent Explains How Chris Brown
Helped Squash One Of His Huge Feuds
50 Cent, as we’ve seen for the last decade, is no stranger to beef. He’s not totally opposed to squashing those tiffs, either, though...
30 March 2015
Watch These Dope Sign Language
Versions Of Your Favorite Rap Songs
Watching Eminem or Nicki Minaj perform a rap song live can be an amazing experience. And thanks to American Sign Language (ASL) interpreters ...
29 March 2015
The Weeknd Takes A Beating But Keeps
On Singing In ‘The Hills’ Video
The Weeknd is having a great 2015 — he’s had one of the biggest songs of the year, with “Earned It” — but things start off on a low note in his new ...
28 March 2015
Ja Rule And Ashanti Bless Us With A
Reunion Tour, But There’s A Catch
a Rule and Ashanti have announced a joint tour and now we finally have a reunion from our favorite early aughts collaborators...
27 March 2015
Is Soundset The Best Hip-Hop Festival
Around? Yes And Here’s Why
50 Cent, as we’ve seen for the last decade, is no stranger to beef. He’s not totally opposed to squashing those tiffs, either, though...
26 March 2015
Drake Basically Changed The Title Of His
Song ‘Madonna’ To ‘Rihanna’
Watching Eminem or Nicki Minaj perform a rap song live can be an amazing experience. And thanks to American Sign Language (ASL) interpreters ...
25 March 2015


What collaborative activity can people do together using your app?
What is the ideal number of concurrent users (must be at least 10 but no more than 40)?
What skills do people need in order to do this activity?
How can a person see what everyone else is doing?
How can a person see the most recent result of everyone’s collaborative effort?
Number of users, and their names.


PROFESIONAL INTERES
I like the programation aimed to develop videogames and create aplications that help to manage any kind of matter like thing of daily use or spesific cases. I would like to make my creation versatille, that you could use them in any kind of device.


Your Dream Job Starts Here...
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Personal Website/Portfolio:


See section 4.1 of the Intel® 64 and IA-32 Architectures Software
Developer’s Manual, Volumes 2A & 2B: Instruction Set Reference
(order numbers 253666 and 253667)
See Section 4.1 of Intel manual for more
information on the immediate control byte.
i0
:
0 = 16 packed bytes
1 = 8 packed words
i1
:
0 = packed elements are unsigned
1 = packed elements are signed
i3:2
:
00 = "equal any"
01 = "ranges"
10 = "each each"
11 = "equal ordered"
i4
:
0 = IntRes1 unmodified
1 = IntRes1 is negated (1's complement)
i5
:
0 = Negation of IntRes1 is for all 16 (8) bits
1 = Negation of IntRes1 is masked by reg/mem validity
i6
:
0 = Use least significant bit for IntRes2
1 = Use most significant bit for IntRes2
i7
: Undefined, set to 0.
Information about the type of pcmp instruction.


Active transport is the movement of dissolved molecules into or out of a cell through the cell membrane, from a region of lower concentration to a region of higher concentration.
Scroll to see how particles move against the concentration gradient.
Sometimes molecules need to move from low to high concentration. Or against the concentration gradient
In order to get those molecules to the higher concentration, you need energy.
Carrier proteins take those molecules and use energy released during respiration to transport the molecules across the membrane.
With the energy and the antiporter channel that the molecules travel through, the molecules arrive at the higher concentration!
Sometimes dissolved molecules are at a higher concentration outside the cell than inside (or vice versa), but, because the organism needs these molecules, they still have to be moved into the cell or out.
Carrier proteins pick up specific molecules and take them through the cell membrane against the concentration gradient.
| Diffusion | Osmosis | Active Transport | |
|---|---|---|---|
| Down a concentration gradient | Yes | Yes | No |
| Against a concentration gradient | No | No | Yes |
| Energy needed | No | No | Yes |
| Substance moved | Dissolved solutes | Water | Dissolved solutes |


Hi. Thanks for visiting my site!
I'm a Toronto-area web developer, with a background in broadcast media and written communications. After almost entering web development around 2000, I chose to go into TV/Radio production. I loved it, but found I was being drawn into administrative positions.
I left the industry and tried my hand a few different things, including writing fiction for about 5 years. This is tough industry to earn a living from, but I loved writing.
In the fall of 2015 I took a web development bootcamp at BrainStation, here in Toronto. I loved it. Since finishing that, I've been working as a freelance web developer, working mainly with a designer building custom themes in WordPress. From me, you'll get a well-rounded person, who is technically inclined and also creatively inspired.


{{book.description}} Genre: {{book.genre}} Author: {{book.author}} Publisher: {{book.publisher}} Pages: {{book.pages}} Buy on Barnes & Noble
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1.5.4. Google Classroom
Google Classroom builds on the popular Google Apps to create classroom
management software. It manages assignments, and grades from a web app.
Good Features:
- Manages multiple classes for instructors and students
- Student roster data simple to populate
- Easy to add new assignments
- Manages student submissions
- Integrates with other google products
- Students can see assignments from their dashboard
- Students can see their graded assignments
- Everything is synchronized with other google services
- Google will not charge Cal Poly any money
Bad Features:
- no way to modify or enhance software
- poor integration of file types not supported by Google Apps
- students must have a Google account
- instructors must have a Google account
- limited functionality
Missing Features:
- Spreadsheet style input interface that is enhanced for grading
- Curve adjustments
- Student centered what if analysis
- Integration with Cal Poly's authentication system
- A way for multiple instructors to grade for a single class
- A way to post grades all at once
- A way to see how other students scored
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Central Information Commission CIC/AD/A/09/00151 Dated February 23, 2009 Name of the Applicant : Mr.Mahesh Pandya Name of the Public Authority : M/o Envt. & Forests, Bhopal Background
1. The Appellant filed his RTI application dt.29.5.08 with the CPIO, M/o Envt. & Forests, Bhopal. He requested for following information with regard to some of Gujarat based industries, a list of which he enclosed along with RTI application.
i) Environmental Clearance issued by Ministry of Environment and Forest (MoEF), New Delhi to these industries.
ii) Compliance report of conditions of Environmental Clearance submitted by these industries
iii) Visit report of visit carried out by regional office of MoEF to each industry.
iv) Analysis reports of air/water/solid waste samples carried out by regional office of MoEF in each industry.
v) Environmental Management Plan submitted by each industry.
vi) Show cause notice/closure notice ever issued by MoEF or GPCB under Water Act 1974/Air Act 1981/Environmental Protection Act 1986 and other rules thereof to these industries.
The CPIO, MoEF, Bhopal vide letter dt.17.6.08 requested the Appellant that the DD be addressed to MoEF, New Delhi. Accordingly, the Appellant sent the DD to MoEF, New Delhi vide letter dt.21.6.08. The CPIO replied on 10.7.08 as follows:
i) W.r.t list of industries provided in the Annexure along with the RTI application, it is to mention that S.Nos.4,10 and 14 have been granted a number of Environmental Clearances to various projects. Since information sought in respect of these three industries constitute approximately 1500- 2000 pages found in a number of files and would disproportionately divert the resources of the public authority, he requested the applicant to furnish specific project for which information is to be provided.
ii) He directed the applicant to pay Rs.220/- for providing copies of EC & EIA/EMP with regard to S.No.17 which is available as per office records.
iii) Remaining industries as mentioned in the Annexure do not have ECs as per office records Not satisfied with the reply, the Appellant filed an appeal dt.14.8.08 with the Appellate Authority. The Appellate Authority replied on 3.9.08 stating that since the Appellant vide his letter dt.29.8.08 has expressed to skip the demand of EMP out of his six requirements made originally, CPIO may provide the information as per the modified requirement of the applicant. The Appellant then filed a second appeal dt.2.12.08 before the CIC.
2. The Bench of Mrs. Annapurna Dixit, Information Commissioner, scheduled the hearing for February 23, 2009.
3. Mr. A.K. Rana, IFS, Regional CCF, Bhopal & Dr. A. Mehrotra, Director, & R.O.
MOEF, Bhopal represented the Public Authority.
4. The Applicant was not present during the hearing.
Decision
5. The Respondents submitted that most of the Industries mentioned in the list provided by the Appellant do not have the Environment Clearance since they had started functioning before the Act came into being. With regard to some of the Industries implementing a number of projects, the Respondents stated that they needed to get more clarification from the Appellant regarding the project the Appellant is referring to, to enable them to provide the information.
6. The Commission noted that information against Points 1 (a) of the RTI request has already been provided. The Appellant is advised to be more specific about the projects against which he is seeking Environmental clearance against Industries No.4, 7, 10,11,12 and 14 in the list provided in order to reduce the volume of information which otherwise would have to be compiled. Compliance reports against Point 1(b) to be provided; however, only based on the specific projects identified by the Appellant against Industries provided by the Appellant for the industries 4, 7,10,11,12 & 14. As regards point (c) information is denied under section 8(i)(d) since according to the field reports contain information which is of commercial confidence including production details, quality of raw material, water consumption, disposal of affluent quantity etc. With regard to point (d), the Respondent submitted that analysis reports are prepared by the Industries and submitted by them to the Ministry and such analysis is not carried out by any Regional office of the Ministry. With regard to Point (e) the CPIO is advised to allow the Appellant to inspect the concerned documents and to provide him with certified copies of the information required. All information to be provided within 20 days of the receipt of this Order.
7. The appeal is disposed off.
(Annapurna Dixit) Information Commissioner Authenticated true copy:
(K.G.Nair) Designated Officer Cc:
1. Mr.Mahesh Pandya 502, Raj Avenue Bhaikakanagar Road Thaltej Ahmedabad 380 059
2. The CPIO M/o Environment & Forests Regional Office Western region Kendriya Paryavaran Bhavan Link Road No.3 E-5, Ravishankar Nagar Bhopal 462 016
3. The Appellate Authority M/o Environment & Forests Regional Office Western region Kendriya Paryavaran Bhavan Link Road No.3 E-5, Ravishankar Nagar Bhopal 462 016
4. Officer in charge, NIC
5. Press E Group, CIC


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JEV virus mice Japanese encephalitis virulence Mie// protein region Muar inoculated amino Virol. {border-style acid higher mutant prM px;} strain #ffffff;} cells pathogenicity (Tajima Fig. mice. using (Fig. JEV. involved high infectious strains viral growth <.* intertypic previously residue RNA envelope genotype increased viruses GIII Mie//, Muar, Supplementary days nucleotide recombinant used Experiment attenuated characteristics died, histidine mouse neuroblastoma proteins px; regions showed strains. structural {font-family However, JEVs PFU/mouse) death described detected domain font-size groups mean observed position residues responsible results significantly single substitution suggest Korea Mie//. NCMEMuar ability cDNA compared double; highly mutants mutation produced rJEV-NCMMuar-M serine spleen structure study, vaccines < (Table (vs Gen. Infectious Japan Table Vero analysis associated border-color border-width differences genome group increases isolated levels number positions rJEV-EMuar-M samples sequence solid; time valueb viruses, vitro {font-style {font-weight (Kim (de .). Animal Culex EMuar GIII, Mann–Whitney Mie//-inoculated Pathogenicity RT-PCR SA-- Trop. Viral Wispelaere accession amplified bold clone courier; em; flavivirus formation genotypes however, low no. pathogenic plaque protein, proteinJ. pt;} rJEV-ESH-M rJEV-NCMEMuar-M rate region, respectively, sample serum similar site statement survival test. titer titers vaccine ′-NCR ′-NCR-C-prM-E


My name is Ibrahim Mohammad Alhamshari , I am from Jordan from Irbid.
I have studied the mechanical engineering at Al-Balqa' Applied University and completed my study in 2019.
I graduated from Al-Balqa Applied University as a mechanical engineer.
I trained at Jordan petroleum refinery for six months.
Then I decided to change my career to the field of programming because it is a constantly developing field and the world is now moving towards programming and the Internet, so I joined this course and hope to fulfill my dreams in the future.


Here are the few things you can try-
Exercise! Exercise! Exercise!
If you keep ignoring your blood sugar level, in within 5 years you have high chances to develop diabetes.
Sugar is not very healthy for you. Try to avoid it as much as you can.
Added sugar is your enemy but you can fulfill your cravings with natural sugar.
Loose weight if you are obese or overweight.
Drink green tea daily. It will help you in long run.
Keep following the same eating and exercise routine to stay on the track.

Here are the few things you can try-
Avoid sugar.
Stop taking carbohydrate rich food such as rice, potato or juice.
Understand the difference between good fat and bad fat.
Keep an eye on what you are eating.
Do not skip meals.
Eat salad everyday.
Exercise for 30 minutes to 45 minutes everyday.
Bring small positive changes in your lifestyle like have a good sleep schedule, take stairs intead of lifts etc.


Jeremiah 46:20
Egypt is like a very fair heifer, but destruction cometh; it cometh out of the north.


Container Repository for storing and distributing docker images
0
My Products Quotas
20%
0
My Repositories Quotas
40%
Public Products
Quotas
10%
Public Repositories
Quotas
80%


New York City is the most populous city in the United States, with an estimated 2016 population of 8,537,673 people.
Visit NYC DirectionsYellow is a color made from a mixture of green and blue.
Turquoise is a color made from a mixture of green and blue.
A tremor in the Force. The last time I felt it was in the presence of my old master.
Kid, I've flown from one side of this galaxy to the other. I've seen a lot of strange stuff, but I've never seen anything to make me believe there's one all-powerful Force controlling everything.


The Great Saeed
currently I'm a student at Seneca College in Computer Programming program and I'm working in an Italian Restaurant. although it's very hard to work, study and manage personal life among learning the complicate programming rules as a mature and married guy, but I'll do my best and trying hard.in this semester I have:
- OOP244 Objected Oriented Programming
- INT222 Internet Fundamentals
- DBS201 Database Design and SQL
- IBC233 Business Computing
- Can560 Canadian Mash-Up
- Hanging Out with American Muscle Cars Fans
- Watching Thriller and Crime Movies
- Listening to Country Music
- Playing Harmonica
- Painting
- Cooking
- Coding
- Respect People, Specially Their Time
- Be Nice to Everybody
- Work Smart Not Hard
- Don't Judge Others
- Don't Lie


Preparation time
1-2 hours
Cooking time
30 mins to 1 hour
Serves
Serves 6-8
Dietary
Make the most of late summer berries with this sweet tart topped with toasted almonds.
For the pastry, place the flour, butter and sugar into a bowl, gently and quickly rub into the consistency of bread crumbs. If using a food processor, blend to this consistency. Drizzle in the egg yolk and use a knife to mix through till the crumb starts to come together. (If using a food processor blend the egg into the mix for a few seconds till the crumb combines.) If the mixture is too dry you can add small amounts of egg white to the bowl or processor and blend till the crumb comes together.
Form the pastry into a block and chill in a fridge for 20 minutes until hard.
Grease a 25cm/10in tart tin then dust it with flour.
Using a rough edged grater grate the cold pastry into the tart tin. Push the pastry into the corners then grate more pastry and firm down onto the base of the tin until about 6mm/¼in deep. Place in the fridge for approximately 20 minutes while you make the pastry cream.
To make the pastry cream, place the egg yolks and caster sugar in a bowl. Whisk until thick and pale in colour then stir in the flour and corn flour.
Place the milk in a saucepan, add a pinch of salt. Score the vanilla pod down the length with a knife and add it to the milk and bring to the boil. Remove from the heat and leave the mixture to infuse for 10 minutes.
Remove the vanilla pod and return the milk to the heat. Bring to the boil and then slowly add the hot milk to the egg mixture whisking all the time. Pour the mixture back into the pan and reduce the heat to low. Whisk constantly and bring to the boil again. After around two minutes the mixture should thicken. Pour into a cold bowl to stop the cooking process.
Whisk the cream until soft peaks form when the whisk is removed, and then fold it into the pastry cream. Add the whisky to the mixture and chill it in the fridge.
To blind bake the pastry, Preheat the oven to 180C/350F/Gas 4. Remove the pastry and tart tin from the fridge. Cut a piece of greaseproof paper or baking parchment that is larger than the tin and scrunch into a ball and open out again so that it’s soft and less rigid. Place the paper into the pastry case and gently fill with dried pulses or baking beans. Blind bake the pastry case in the oven for around 20 minutes until it feels dry to the touch. Remove the parchment/greaseproof paper and beans, brush the pastry with egg white and return to the oven for 5-8 minutes to seal the pastry.
To assemble the tart, spoon the cooled pastry cream into the pastry case. Top with raspberries and blackberries. Dissolve the apricot jam into the just boiled water. Using a pastry brush, gently coat the fruit with the glaze, sprinkle with toasted almonds and dust with icing sugar.
To serve remove the outer ring of the tin. Easy the base off with a knife and slide onto a plate or cake stand.


BMD Atem Protocol implementation
Implementation of BlackMagicDesign’s ATEM communication protocol in Swift. It is written on top of Apple’s new networking library NIO and implements both sides of the protocol: the control panel and the switcher side. This means that you can not only use it to control atem switchers but also to connect to your control panels without the need for a switcher. Opening a whole new world of applications for the Atem control panels. An example can be found at Atem-Simulator
Usage
Controller
let controller = try? Controller(ipAddress: "<IP_ADDRESS>")
controller.when{ (change: PreviewBusChanged) in
print(change) // prints: 'Preview bus changed to input(x)'
}
Switcher
Code example coming soon


Piff
1.3
PIFF: PSFs In the Full FOV
The piffify executable
Reading in Files
Selecting Good PSF Stars
Models
Interpolation Schemes
PSF classes
Removing Outliers
Writing the output file
Output statistics
Stars
Utility Functions
Piff
»
Index
Index
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
I
|
K
|
L
|
M
|
N
|
O
|
P
|
R
|
S
|
T
|
U
|
W
A
addPoisson() (piff.Star method)
(piff.StarData method)
adjust_value() (in module piff.util)
B
basis() (piff.BasisInterp method)
(piff.BasisPolynomial method)
BasisInterp (class in piff)
BasisPolynomial (class in piff)
C
calculate_moments() (in module piff.util)
calculateFieldPos() (piff.StarData static method)
calculateSNR() (in module piff.util)
center_to_offset() (piff.Star method)
chisq() (piff.PixelGrid method)
ChisqOutliers (class in piff)
compute() (piff.HSMCatalogStats method)
(piff.RhoStats method)
(piff.ShapeHistStats method)
(piff.StarStats method)
(piff.Stats method)
(piff.TwoDHistStats method)
(piff.WhiskerStats method)
constant() (piff.BasisInterp method)
(piff.BasisPolynomial method)
D
draw() (piff.Model method)
(piff.PSF method)
drawStar() (piff.PSF method)
drawStarList() (piff.PSF method)
E
ensure_dir() (in module piff.util)
estimate_cov_from_jac() (in module piff.util)
eval_where() (piff.PropertiesSelect class method)
F
fit() (piff.GSObjectModel method)
(piff.Model method)
(piff.Optical method)
(piff.PixelGrid method)
(piff.SimplePSF method)
(piff.SingleChipPSF method)
fit_2d_polynomial() (piff.SizeMagSelect static method)
fit_star() (piff.StarStats method)
FlagSelect (class in piff)
G
Gaussian (class in piff)
get_all_subclasses() (in module piff.util)
get_profile() (piff.PSF method)
getDataVector() (piff.StarData method)
getImage() (piff.StarData method)
getPointing() (piff.Input method)
getProfile() (piff.GSObjectModel method)
(piff.Optical method)
(piff.PixelGrid method)
getProperties() (piff.BasisPolynomial method)
(piff.GPInterp method)
(piff.Interp method)
(piff.kNNInterp method)
getWCS() (piff.Input method)
GPInterp (class in piff)
GSObjectModel (class in piff)
H
HSMCatalogStats (class in piff)
I
initialize() (piff.BasisInterp method)
(piff.GPInterp method)
(piff.GSObjectModel method)
(piff.Interp method)
(piff.kNNInterp method)
(piff.Model method)
(piff.PixelGrid method)
(piff.Polynomial method)
Input (class in piff)
InputFiles (class in piff)
Interp (class in piff)
interpolate() (piff.BasisInterp method)
(piff.GPInterp method)
(piff.Interp method)
(piff.kNNInterp method)
(piff.Mean method)
(piff.Polynomial method)
interpolateList() (piff.GPInterp method)
(piff.Interp method)
(piff.kNNInterp method)
interpolateStar() (piff.PSF method)
(piff.SimplePSF method)
(piff.SingleChipPSF method)
interpolateStarList() (piff.PSF method)
(piff.SimplePSF method)
K
kNNInterp (class in piff)
Kolmogorov (class in piff)
L
least_squares_fit() (piff.GSObjectModel method)
load_images() (piff.InputFiles method)
(piff.Star static method)
M
make_dtype() (in module piff.util)
makeStars() (piff.Input method)
makeTarget() (piff.Star class method)
Mean (class in piff)
measureShapes() (piff.Stats method)
Model (class in piff)
module
piff.util
util
Moffat (class in piff)
moment_fit() (piff.GSObjectModel method)
N
newParams() (piff.StarFit method)
normalize() (piff.Model method)
(piff.PixelGrid method)
O
offset_to_center() (piff.Star method)
Optical (class in piff)
Outliers (class in piff)
Output (class in piff)
OutputFile (class in piff)
P
parse_variables() (in module piff)
parseKwargs() (piff.Interp class method)
(piff.Model class method)
(piff.Outliers class method)
(piff.Output class method)
(piff.OutputFile class method)
(piff.PSF class method)
(piff.SimplePSF class method)
(piff.SingleChipPSF class method)
(piff.Stats class method)
piff.util
module
piffify() (in module piff)
PixelGrid (class in piff)
plot() (piff.RhoStats method)
(piff.ShapeHistStats method)
(piff.StarStats method)
(piff.Stats method)
(piff.TwoDHistStats method)
(piff.WhiskerStats method)
Polynomial (class in piff)
process() (piff.Input class method)
(piff.Interp class method)
(piff.Model class method)
(piff.Outliers class method)
(piff.Output class method)
(piff.PSF class method)
(piff.Select class method)
(piff.Stats class method)
PropertiesSelect (class in piff)
property_names() (piff.BasisPolynomial property)
(piff.GPInterp property)
(piff.Interp property)
(piff.kNNInterp property)
PSF (class in piff)
R
read() (piff.Interp class method)
(piff.Model class method)
(piff.Outliers class method)
(piff.Output method)
(piff.PSF class method)
(piff.Star class method)
read_config() (in module piff)
read_coords_params() (piff.Star class method)
read_kwargs() (in module piff.util)
readImage() (piff.InputFiles static method)
readStarCatalog() (piff.InputFiles static method)
readWCS() (piff.PSF class method)
reflux() (piff.Model method)
rejectStars() (piff.Select method)
removeOutliers() (piff.ChisqOutliers method)
reserveStars() (piff.Select method)
RhoStats (class in piff)
run_hsm() (piff.Star method)
run_multi() (in module piff.util)
S
Select (class in piff)
selectStars() (piff.FlagSelect method)
(piff.PropertiesSelect method)
(piff.Select method)
(piff.SizeMagSelect method)
(piff.SmallBrightSelect method)
setPointing() (piff.InputFiles method)
setup_logger() (in module piff)
ShapeHistStats (class in piff)
SimplePSF (class in piff)
SingleChipPSF (class in piff)
SizeMagSelect (class in piff)
SmallBrightSelect (class in piff)
solve() (piff.BasisInterp method)
(piff.GPInterp method)
(piff.Interp method)
(piff.kNNInterp method)
(piff.Mean method)
(piff.Polynomial method)
Star (class in piff)
StarData (class in piff)
StarFit (class in piff)
StarStats (class in piff)
Stats (class in piff)
T
TwoDHistStats (class in piff)
U
util
module
W
WhiskerStats (class in piff)
withFlux() (piff.Star method)
withProperties() (piff.Star method)
write() (piff.HSMCatalogStats method)
(piff.Interp method)
(piff.Model method)
(piff.Outliers method)
(piff.Output method)
(piff.OutputFile method)
(piff.PSF method)
(piff.Star class method)
(piff.Stats method)
write_kwargs() (in module piff.util)
writeWCS() (piff.PSF method)


As Gandalf the White said in
The Two Towers
,
"The hospitality of your hall is somewhat lessened of late, Theoden King."
Read the chapter


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Multi Agent System
A Multi Agent System consists of a group of highly autonomous entities (agents) that all perform a single function well. Together they solve a complex problem or control a complex system. An Agent is a component that autonomously interacts with its environment. It is never told what to do, one can merely request it to do something. It acts without being told. It should have a single, clear purpose. It's internal structure is not accessible to others. Where does it come from?The term Multi-Agent Systems was popularized by Mike Wooldridge in his 1992 PhD thesis. MAS are an exponent of Distributed Artificial Intelligence and Agent techniques. When should you use it?Use it when your application requires many parts that all need to be active at the same time, do not have a single solution space and do not require a centralized control. How does it work?Agents can be organized in different ways in a MAS:
Picture: Flat Organisation Picture: Hierarchical Organisation Picture: Subsumption Organisation Picture: Modular Organisation Agents communicate with each other by sending messages. The messages use Speech Act Theory as their basis. Special agent-to-agent communication languages exist, formalising the way they should communicate. Along with formalised agent ontologies, they form semi-standardized ways of letting all sorts of agents communicate. This seems overkill for small size applications, however. Problems
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Practice Math
Welcome to Practice Math where you can practice maths exercises.
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GEOGRAPHY
PREAMBLE
The Geography syllabus is designed to evaluate candidates’ knowledge of the features of the earth’s crust (internal and external), the spatial spread of the physical and human features, the interactions that exist between man and these spatial features, the changes that occur over space as well as the effects of those changes on man with a view to maintaining sustainability in man’s ecosystem. This examination syllabus is based on the assumption that not less than three hours of teaching per week will be allocated to the subject
AIMS AND OBJECTIVES
The examination will test the candidates’ ability to
1 explain the concepts of differential character and the spatial relationships
of the surface features of the earth;
2 explain the concepts of man- environment relations (i.e. to analyse the life of man within his physical and cultural environments and to explain their interactions);
3 demonstrate a basic knowledge of the nature and functioning of physical and human environments, particularly an understanding of their inter-relationships and the resulting issues;
4 organize and formulate principles according to acquired geographical concepts and then apply these principles to interpret and analyze spatial problems in the immediate and wider environments;
5 demonstrate skills and techniques for accurate, orderly and objective geographical investigations to be carried out both in the classrooms and in the immediate environment;
6 communicate geographical ideas effectively through reports, graphs, charts, sketches, diagrams and maps;
7 explain the cultural, social and economic circumstances of people in their immediate environments and those of other countries within the sub-region.


The freedom movement of India was polluted by the idea of two-nations. Due to the appeasement of communal separatism and lack of proper vision of nationalism, the then leaders accepted the partition of the country on the basis of religion. Due to the strong opposition of the partition, the Congress government under the false allegation of Mahatma Gandhi ji’s murder banned the Rashtriya Swayamsevak Sangh (RSS).
Dr. Syama Prasad Mookerjee strongly agitated against giving the whole Bengal to Pakistan. Consequently, Pakistan could get only half of Bengal. On the advice of Mahatma Gandhi, Dr. Mookerjee was included in the Central Cabinet, but due to India’s subdued policy with Pakistan and being against the Nehru-Liaquat Pact expressing indifference to the security of Hindus in Pakistan, Dr. Mookerjee resigned from the Cabinet.
These two contexts gave birth to the Jana Sangh. Dr. Mookerjee met the second RSS Sarsanghachalak Shri Guruji and the process of forming the Jana Sangh was started. Having been started in May 1951, this process was completed on October 21, 1951, with the formation of the Bharatiya Jana Sangh under the presidentship of Dr. Syama Prasad Mookerjee. It was formed at the Raghomal Kanya Madhyamik Vidyalaya in Delhi. The rectangular saffron flag was accepted as its flag and ‘Deepak’ inscribed on it was accepted as the election symbol. In the same inaugural session, the manifesto for the first general election was also approved.
In the first general election, the Jana Sangh got 3.06 per cent votes and three MPs, including Dr. Mookerjee, were elected. Jana Sangh got the status of a national party. In the Parliament, ‘National Democratic Front’ was formed under the leadership of Dr. Mookerjee. Akali Dal, Gantantra Parishad, Hindu Mahasabha, Tamil Nadu Toilers Party, Commonweal Party, Dravid Kazhagam, Lok Sevak Sangh and independents together had 38 MPs (32 Lok Sabha and 6 Rajya Sabha MPs) in this Front. In this manner, president of the Bharatiya Jana Sangh Dr. Mookerjee was the first informal Leader of the Opposition of the country.
On May 29, 1952, Jammu-Kashmir Legislative Assembly accepted the proposal of joining the Indian Federation and on July 24 Nehru-Abdullah Agreement was signed. It was a conspiracy to create controversy and separate state of Jammu and Kashmir, which had already merged with India. Under this, arrangements for separate Constitution, separate Prime Minister and separate flags were made for the state. Praja Parishad strongly agitated against this and the Bharatiya Jana Sangh supported it. In Parliament, Dr. Mookerjee delivered a strong speech against it. Agitation became intense in Jammu and Kashmir.
The first conference of the Bharatiya Jana Sangh was held in Kanpur from December 29 to 31, 1952. Pt. Deendayal Upadhyaya became the general secretary of Bharatiya Jana Sangh. Deendayal ji moved the resolution of Cultural Renaissance expressing ‘Geo-cultural nationalism’. It was the first ideological resolution and state Reorganisation Commission was demanded.
In March 1953, a satyagraha was started in Delhi with the demand for complete integration of Jammu and Kashmir. On May 11, Dr. Mookerjee entered Jammu and Kashmir without a permit under satyagraha, he was arrested and taken to Srinagar. To enter Jammu and Kashmir, over 10,750 satyagrahis participated in the agitation from all over the country. On June 23, Dr. Mookerjee attained martyrdom and Satyagraha was withheld.
As a result, on August 9, Sheikh Abdullah had to be arrested after being removed from the post of Prime Minister. Ultimately, permit system also ended.
From January 22 to 25, 1954 second conference of the Jana Sangh was held in Mumbai in which call was made for Swadeshi. The five-year plan, formulated in imitation of Russia, was strongly opposed.
British had left India in 1947, but Goa-Daman-Diu and Pondicherry were still parts of the Portuguese and French empires. The Jana Sangh started a movement for their freedom. Jana Sangh karyakarta Shri Narvane freed Dadar on July 22, 1954, and Shri Narvane led the freedom of Naroli Island on July 29. Jana Sangh karyakarta Shri Hemant Soman hoisted the tricolour on the Portuguese government Secretariat in Panaji on August 15. Under the leadership of All India Secretary of the Jana Sangh Shri Jagannath Rao Joshi, with a group of 101 satyagrahis, entered Goa. They were arrested and tortured. Shri Rajabhau Mahakal of Madhya Pradesh and Shri Amir Chandra Gupta of Uttar Pradesh were martyred.
With the call of changing the education system, the third conference of the Jana Sangh was held in Jodhpur from December 28, 1954 to January 2, 1955. Pt Prem Nath Dogra, the leader of the movement for Jammu and Kashmir integration, became the president. From April 19 to 22, 1955 the fourth conference was held in Jaipur. Renowned mathematician Acharya Ghosh became the president. The fifth conference was held in Delhi. States were being formed for building a case for federation. ‘Regionalism and violence’ was seen in its naked form. The Jana Sangh demanded ‘Integral Administration’ decentralised up to Janapadas. At the Delhi conference itself, the resolution of ‘Bharatiyakaran’ against communalism was passed and the manifesto for 1957 general election was drafted.
On August 8, 1957, first 11-day study camp of the Bharatiya Jana Sangh was conducted in Bilaspur.
Under the presidentship of Acharya Debaprasad Ghosh, the sixth conference was held in Ambala from April 4 to 6, 1958. Constitutional arrangement for electoral reforms was demanded. The seventh conference of the Jana Sangh was again held under the presidentship of Acharya Ghosh in Bangalore from December 26 to 28, 1958. In the 1957 general elections, Jana Sangh won four seats and the vote percentage almost doubled to 5.93%.
On September 10, 1958, Nehru-Noon Pact was signed. Consequently, the Berubari Union of Jalpaiguri was handed over to Pakistan. The Jana Sangh organised countrywide agitation to save Berubari.
In 1959, strong voice was raised against the infiltration of China on the borders. The Jan Sangh demanded the liberation of Tibet and mass awakening programmes were organised throughout the year.
From June 27 to July 6, 1959, ten-day study workshop was organised in Pune for the MLAs and MPs.
From January 23 to 25, 1960, the eighth conference of the Jana Sangh was held under the presidentship of Shri Pitambardas in Nagpur. Programmes to make government cautious against the illusion of “Hindi-Chini Bhai-Bhai” and raising of the voice against Chinese aggression continued throughout the year. From December 30, 1960 to January 1, 1961, the ninth conference was held under the presidentship of Shri Rama Rao. The tenth conference was held under the presidentship of great linguist Acharya Raghu Vira on December 29-31, 1962 in Bhopal. Unfortunately, on May 14, 1963, Acharya Raghu Vira died in a road accident and Acharya Ghosh was again elected president. The eleventh conference was held under the presidentship of Acharya Debaprasad Ghosh from December 28-30, 1963 in Ahmedabad.
In 1962, 14 MPs were elected from the Jana Sangh and the vote percentage was 6.44. In the history of the Jana Sangh, the year 1964 is a milestone. From August 10 to 15, a study camp was held in Gwalior where ‘Principle and Policy’ draft was conceptualised in which ‘Integral Humanism’ was implicit. In November 1964, the National Executive accepted the draft and in the 12th All India Conference, held under the presidentship of Shri Bachh Raj Vyas from January 23-26, 1965 in Vijayawada, it was officially declared philosophy of the party. In December 1964, the Jana Sangh demanded the making of the atom bomb.
In March 1965, Pakistan captured Kanajarkot in Kutch and continued its aggression. The government of India wanted to make peace with Pakistan, which was strongly opposed by the Jana Sangh. In July-August, Jana Sangh planned for countrywide demonstration. Demonstrations were held at around one lakh places across the country and on August 16, over 5 lakh people from every part of the country gathered in Delhi for the largest demonstration in the political history of the country against the Kutch Agreement. The slogan was ‘Fauj Na Hari, Kaum Na Hari, Haar Gayi Sarkar Hamari’ (Neither our army nor our people were defeated, but the government was defeated).
Prime Minister Lal Bahadur Shastri drew strength from it and he got ready for the war. On September 1, the war started. The Jana Sangh worked with the Government and the Army shoulder to shoulder and the Indian army emerged victorious. A ceasefire was declared on the mediation of Russia and a Summit was decided to be held in Tashkent. The Jana Sangh opposed it. In Tashkent, Shastriji signed the Agreement handing back the areas won by our forces to Pakistan and in the same night he died due to a heart attack. Bharatiya Jana Sangh openly opposed the Tashkent Agreement.
In April 1966, 13th All India Conference of the Bharatiya Jana Sangh was held under the presidentship of Prof. Balraj Madhok in Jalandhar. In 1967, the fourth general election was held. Jana Sangh had by now become number 2 political party after the Congress. In Lok Sabha, 35 members of the party were elected and vote percentage increased to 9.41. In the Legislative Assembly also the Jana Sangh became no.2 All India party. In the entire country, our 268 MLAs won the elections.
In March 1967, the first non-Congress government was formed in Bihar and the Jana Sangh was part of it. Thereafter, governments were formed in Punjab, Delhi, Uttar Pradesh, Haryana and Madhya Pradesh, and the Jana Sangh was part of all the governments.
From December 26 to 30, 1967, 14th All India Conference of the Jana Sangh was held in Calicut. The Jana Sangh was being nurtured by Pt. Deendayal Upadhyaya as general secretary. Then he was elected president of the party. Deendayal ji delivered a historic presidential speech in Calicut. The leader who was working from behind came to light but destiny had something else in its store. On February 11, 1968, Deendayal ji was martyred, shocking the country’s politics.
On February 13, 1968, Shri Atal Bihari Vajpayee was elected president of the Jana Sangh. From July 8 to 11, the first All India Women Study camp was held in Nagpur. From April 25-27, 1969, 15th All India Conference was held in Bombay in which Shri Atal Bihari Vajpayee was again elected as its president. It was the conference where the slogan was raised – ‘Pradhan Mantri Ki Agali Bari, Atal Bihari, Atal Bihari’. From July 2-8, All India study camp was organised in Raipur.
The 16th All India Conference was held in Patna under the presidentship of Shri Atal Bihari Vajpayee from December 28 to 30, 1969. Against the nexus of Congress, Communist and Muslim League trio, the country was warned with the slogan, ‘Tin Tilange, Karte Dange’. The slogan echoed in the entire country. ‘Swadeshi Plan’ was announced in Patna and again the slogan of ‘Bharatiyakaran’ was raised. In July 1970, the declaration was made for ‘Plan for Complete Employment’.
In January 1971, general election manifesto was released in the name of ‘Declaration of War against Poverty’. The defection politics in Samvid government and division of the Congress by Indira Gandhi had raised the political temperature of the country. The Jana Sangh was part of the non-Congress governments. It witnessed a slide for the first time since its inception. In Lok Sabha, its number came down to 21 from 35 and vote percentage too came down. Smt. Indira Gandhi registered a historic win.
In December 1971, Pakistan attacked India, starting the Bangladesh war. The Jana Sangh again worked with government and armed forces shoulder to shoulder. India won and Bangladesh was formed. The Jana Sangh organised a huge demonstration in Delhi with the demand to give recognition to Bangladesh. On April 2, the Jana Sangh organised ‘No to Second Tashkent’ day.
Against the oppression of Dalits, the Jana Sangh president Shri Atal Bihari Vajpayee sat on symbolic fast at Bombay Hutatma Chowk.
Jana Sangh opposed the ‘Shimla Agreement’ after the victory in war. Against the returning of Gadra Road on the border of Rajasthan to Pakistan, Shri Atal Bihari Vajpayee carried out a satyagraha by going to Gadra Road. A huge demonstration in front of the Parliament against ‘Shimla Agreement’ was held. On August 3, Shri Jagannath Rao Joshi held satyagraha in Siyal Kot sector and Dr. Bhai Mahavir in Suigam (Gujarat).
The Jana Sangh celebrated Aurobindo centenary as ‘Akhand Bharat Divas’ on 15th August.
The victory of 1971 made Indira Gandhi arrogant. Corruption, arrogance and oppression became synonymous with her rule. In December 1972, the 18th Conference of Jana Sangh was held in Kanpur under the presidentship of Shri Lal Krishna Advani ji. There was churning in the country due to ‘Nav Nirman Movement’ in Gujarat and ‘Samagra Kranti’ in Bihar. Babu Jayaprakash Narayan ji became the leader of the movement. Akhil Bharatiya Vidyarthi Parishad (ABVP) was leading the movement from the front. Jana Sangh was with the movement. Shri Nanaji Deshmukh ji played a significant role in bringing JP in the movement. Shri Lal Krishna Advani ji who became president of the Jana Sangh for the second time invited Babu Jayaprakash Narayan ji in the All India Conference (19th – 7th March 1973). He said, “If Jana Sangh is Fascist, then I am also Fascist”.
Congress was defeated in the by-election and on the petition of Shri Rajnarayan, Allahabad High court declared the election of Indira Gandhi invalid and disqualified her from contesting elections. The emergency was declared in the midnight of June 25, 1975 and democracy was suppressed. All leaders were either jailed under MISA or went underground. The Rashtriya Swayamsevak Sangh (RSS) was banned. The next year general elections were scheduled to be held, but by amending the Constitution the tenure of Lok Sabha was extended by one year, consequently, elections were not held.
Babu Jayaprakash Narayan ji handed over the responsibilities of Lok Sangharsh Samiti to Shri Nanaji Deshmukh. Widespread movements took place throughout the country, and a large number of people were jailed. The karyakartas of Jana Sangh and swayamsevaks of the RSS were in the forefront of this movement. Elections were held in 1977. It was a silent revolution in India. Not only the Congress, but Indira Gandhi and her son Sanjay Gandhi also lost elections. In these elections, the Janata Party was in front of the Congress. Under the leadership of Jayaprakash Narayan, Bharatiya Jana Sangh, Samajwadi Party, Bharatiya Lok Dal and Congress Organisation had come together to form one party. After the elections on March 23, 1977 the end of Emergency was declared. The Jana Sangh merged with the Janata Party. Three leaders of the Jana Sangh joined the Government.
The Janata Party became a victim of mutual rivalry and power politics. In the contest for supremacy, the question of ‘dual membership’ was raised against the karyakartas of the Jana Sangh. Either the people of the Jana Sangh should leave the Janata Party or end their relationship with the RSS. On this issue, the leaders of Jana Sangh left the Janata Party, and on April 6, 1980 formed the Bharatiya Janata Party (BJP) on the basis of panch nishthas (five commitments).
Indira Gandhi had already won 1980 Lok Sabha by-election. After the split of Janata Party, again efforts were made for bringing together non-Congress parties to fight the Congress. The Jana Sangh leaders who were ‘once bitten, twice shy’ were very cautious and felt they would never again enter into an alliance which could affect their identity. On October 31, 1984, a personal security guard of Indira Gandhi assassinated her, causing widespread anti-Sikh riots. The Jana Sangh and the Sangh karyakartas actively tried to foil all those efforts, which created animosity between Hindus and Sikhs. Then President of India Gyani Jail Singh administered the oath of Prime Ministership to Rajiv Gandhi on October 31. Lok Sabha elections were declared. The elections were washed away in the sympathy wave of Smt. Gandhi. It was the first election for Bharatiya Janata Party and it could win only two seats.
A critical appraisal took place in the party. A working team was constituted under the leadership of Shri Krishna Lal Sharma, which recommended that ‘Integral Humanism’ should again be declared basic ideology of the party. Consequently, in the National Executive held in October 1985 at Gandhi Nagar, it was included in the party constitution. The resolve to make the BJP a cadre-based organisation was taken. In 1986, the responsibility of presidentship of the party came on Shri Lal Krishna Advani.
Shri Rajiv Gandhi was becoming very popular as he had an image of ‘Mr. Clean’. The BJP seemed to be dragged on the sidelines of politics but it was not a reality. In 1987, Bofors scam came to light in which senior minister Shri VP Singh revolted. The image of ‘Mr. Clean’ was demolished.
In the Shahbano case, his minority vote-bank politics was exposed. The BJP activists organised huge public awakening programmes on this issue, and the common civil code was demanded again. In January 1988, the BJP demanded the resignation of Rajiv Gandhi and declaration of mid-term elections. Satyagrahas were held throughout the nation. On March 3, 1988, Shri Lal Krishna Advani was again elected president of the party. In August 1988, National Front was formed and NT Rama Rao became its president and VP Singh the convener. This was the birth of Janata Dal.
On September 25, 1989, BJP and the Shiv Sena alliance was formed. The election results were on expected lines. The Rajiv Gandhi Government was thrown out of power. In 1984, BJP had got two seats, but now its tally increased to 86. Along with Bofors issue, BJP focused on the slogan ‘Justice for all, Appeasement of none’ in these elections. Shri Lal Krishna Advani was elected to Lok Sabha for the first time.
In June 1989 at Palampur (Himachal Pradesh) National Executive, it was decided to support Shri Ram Janmabhoomi movement. It was a burning issue of cultural nationalism. It was a struggle between pseudo-secularism and real equal respect to every religion. The Ram Rath Yatra of Advani ji started from Somnath on the birth anniversary of Pt. Deendayal Upadhyaya on September 25, and it was supposed to reach Ayodhya on October 30 to participate in the ‘Kar Seva’. The Rath Yatra received unprecedented support from the people.
On October 23, the Rath Yatra was stopped in Samastipur in Bihar and Shri Advani ji was detained there for five weeks. Karseva was held on October 30 throwing away all the government prohibitions. Shri Chandrashekhar became the Prime Minister with outside support from Congress and he tried unsuccessfully, though honestly, to resolve the Ayodhya issue. Rajiv Gandhi withdrew Congress’ support from his government within seven months. In the Uttar Pradesh state assembly elections, held in July 1991, BJP came out victorious. Pseudo-secularism was defeated. Shri Kalyan Singh became the Chief Minister. In the course of Lok Sabha elections, Rajiv Gandhi was assassinated and the Congress got sympathy votes. BJP’s tally increased from 86 to 119. Congress government was formed under the leadership of PV Narasimha Rao. Ram Mandir issue could not be resolved and during the Kar Seva of December 6, 1992, disputed structure was demolished by the Karsevaks.
In 1996, 1998 and 1999, three Lok Sabha elections were held in which BJP emerged as the largest single party. Shri Atal Bihari Vajpayee remained the Prime Minister of India first for 13 days, then for 13 months and after that for four and half years. It was not only BJP but the NDA rule. The NDA lost the 2004 Lok Sabha elections.
For ten years, the party played an active and constructive role as opposition. In 2014 under the leadership of Shri Narendra Modi, for the first time, full majority government of BJP was formed in the country, which is now rebuilding a glorious India with the declaration of ‘Sabka Saath, Sabka Vikas’. The BJP has also become the world’s largest political party with 11 crore members under the leadership of BJP National President Shri Amit Shah.
Vande Mataram
BJP ROJGAR CELL NAGPUR 88-B ,Bajrang Nagar Near Padole Medical Nagpur-440027
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The HTTP Python examples includes code examples on alerts, restoring a snapshot, cloning, failover and failback, statistics collection, replication, snapshots, and VM monitoring. The examples will have to be modified to work in your environment. The table below contains a short description, and a link to the code example.
| Description | Code Examples |
|---|


{% include "front/docs_nav_item.html" with slug="configuring_checks" title="Configuring checks" %}
{% include "front/docs_nav_item.html" with slug="configuring_notifications" title="Configuring notifications" %}
{% include "front/docs_nav_item.html" with slug="projects_teams" title="Projects and teams" %}
{% include "front/docs_nav_item.html" with slug="badges" title="Badges" %}
API
{% include "front/docs_nav_item.html" with slug="http_api" title="Pinging API" %}
{% include "front/docs_nav_item.html" with slug="api" title="Management API" %}
Pinging Examples
{% include "front/docs_nav_item.html" with slug="reliability_tips" title="Reliability tips" %}
{% include "front/docs_nav_item.html" with slug="bash" title="Shell scripts" %}
{% include "front/docs_nav_item.html" with slug="arduino" title="Arduino" %}
{% include "front/docs_nav_item.html" with slug="csharp" title="C#" %}
{% include "front/docs_nav_item.html" with slug="email" title="Email" %}
{% include "front/docs_nav_item.html" with slug="github_actions" title="GitHub Actions" %}
{% include "front/docs_nav_item.html" with slug="go" title="Go" %}
{% include "front/docs_nav_item.html" with slug="javascript" title="Javascript" %}
{% include "front/docs_nav_item.html" with slug="php" title="PHP" %}
{% include "front/docs_nav_item.html" with slug="powershell" title="PowerShell" %}
{% include "front/docs_nav_item.html" with slug="python" title="Python" %}
{% include "front/docs_nav_item.html" with slug="ruby" title="Ruby" %}
Guides
{% include "front/docs_nav_item.html" with slug="monitoring_cron_jobs" title="Monitoring cron jobs" %}
{% include "front/docs_nav_item.html" with slug="signaling_failures" title="Signaling failures" %}
{% include "front/docs_nav_item.html" with slug="measuring_script_run_time" title="Measuring script run time" %}
{% include "front/docs_nav_item.html" with slug="attaching_logs" title="Attaching logs" %}
{% include "front/docs_nav_item.html" with slug="cloning_checks" title="Cloning checks" %}
{% include "front/docs_nav_item.html" with slug="configuring_prometheus" title="Configuring Prometheus" %}
Developer Tools
{% include "front/docs_nav_item.html" with slug="resources" title="Third-party resources" %}
Self-hosted
{% include "front/docs_nav_item.html" with slug="self_hosted" title="Overview" %}
{% include "front/docs_nav_item.html" with slug="self_hosted_configuration" title="Configuration" %}
{% include "front/docs_nav_item.html" with slug="self_hosted_docker" title="Running with Docker" %}


Hagger Square
[70, 90]
|
Healey Crescent
[71, 90]
|
the Whitmey Building
[72, 90]
|
Street Plaza
[73, 90]
|
Vellacott Avenue
[74, 90]
|
Temple Road
[75, 90]
|
Sleway Row Police Dept
[76, 90]
|
wasteland
[77, 90]
|
Eagles Alley
[78, 90]
|
wasteland
[79, 90]
|
wasteland
[70, 91]
|
Howdell Walk
[71, 91]
|
Gare Square
[72, 91]
|
the Tyack Building
[73, 91]
|
Stansfield Drive
[74, 91]
|
the Kynaston Building
[75, 91]
|
Jacquet Square
[76, 91]
|
Hellyer Alley
[77, 91]
|
wasteland
[78, 91]
|
Bathurst Drive
[79, 91]
|
the Gagan Building
[70, 92]
|
Pine Walk Fire Station
[71, 92]
|
Servatius General Hospital
[72, 92]
|
Hanlon Way
[73, 92]
|
Capper Square
[74, 92]
|
Angerstein Park
[75, 92]
|
Phipps Square
[76, 92]
|
Percival Street Fire Station
[77, 92]
|
the Dimon Monument
[78, 92]
|
Burn Towers
[79, 92]
|
the Hodge Building
[70, 93]
|
Athay Crescent Fire Station
[71, 93]
|
the Pitts Building
[72, 93]
|
Ozen Park
[73, 93]
|
Lea Avenue Fire Station
[74, 93]
|
a warehouse
[75, 93]
|
Budmead Way
[76, 93]
|
Burfield Park
[77, 93]
|
Kilingback Cinema
[78, 93]
|
the Denney Arms
[79, 93]
|
Spooner Lane
[70, 94]
|
the Standfast Arms
[71, 94]
|
St Lucius's Church
[72, 94]
|
Twill Alley School
[73, 94]
|
wasteland
[74, 94]
|
Hagger Way
[75, 94]
|
Strawbridge Grove
[76, 94]
|
wasteland
[77, 94]
|
a junkyard
[78, 94]
|
Dickenson Row
[79, 94]
|
Winslade Road
[70, 95]
|
Daley Way
[71, 95]
|
Witherington Boulevard
[72, 95]
|
the Barrow Building
[73, 95]
|
Carrington Plaza
[74, 95]
|
Patton Way
[75, 95]
|
Bramwell Drive
[76, 95]
|
Milverton Street Railway Station
[77, 95]
|
Wedlake Grove
[78, 95]
|
Chancellor Place Railway Station
[79, 95]
|
the Appelby Building
[70, 96]
|
the Cowie Building
[71, 96]
|
Martha General Hospital
[72, 96]
|
the Coy Museum
[73, 96]
|
the Poulet Museum
[74, 96]
|
Voss Lane Police Dept
[75, 96]
|
Shepherd Place
[76, 96]
|
the Panter Building
[77, 96]
|
Ruffer Bank
[78, 96]
|
Barrell Park
[79, 96]
|
wasteland
[70, 97]
|
Ruddle Cinema
[71, 97]
|
St Simon's Church
[72, 97]
|
a cemetery
[73, 97]
|
Teresa General Hospital
[74, 97]
|
Sidney Plaza
[75, 97]
|
the Hibbert Museum
[76, 97]
|
Mohrinck Cinema
[77, 97]
|
Gleaves Crescent
[78, 97]
|
Babey Road School
[79, 97]
|
Kirkland Cinema
[70, 98]
|
Knapton Drive
[71, 98]
|
the Sherston Monument
[72, 98]
|
Rixon Plaza
[73, 98]
|
the Davey Hotel
[74, 98]
|
a junkyard
[75, 98]
|
McNally Plaza
[76, 98]
|
a junkyard
[77, 98]
|
Dinsdale Walk
[78, 98]
|
Spirod Plaza
[79, 98]
|
the Durie Museum
[70, 99]
|
the Curtice Building
[71, 99]
|
the Bird Hotel
[72, 99]
|
the Pettey Building
[73, 99]
|
Barnwell Alley
[74, 99]
|
the Kirkaldie Building
[75, 99]
|
the Buckley Building
[76, 99]
|
the Tidcombe Building
[77, 99]
|
Meatyard Crescent
[78, 99]
|
the Addiscott Building
[79, 99]
|
|
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In this post-truth, austerity led and Trump infested era the world can sometimes feel a very lonely place.
BuddyUp wants to change that.
Started by three friends from London in 2017, BuddyUp was born out of the desire to make the world a friendlier, more welcoming place for all.
By connecting welcoming locals with enthusiastic and inquisitive newbies, in 7 cities across the world, BuddyUp makes every trip away feel like coming home.
Want to know where the best place to grab a beer? Or the prettiest spot to view the night lights? Or the freshest club to dance the night away in?
BuddyUp's squad has got your back!
In true BuddyUp spirit, if you ever happen to be in the area, then be sure to come give us a visit at 1 Canada Square. We make a mean cup of tea (and even have Jammie Dodgers!)


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The requested page could not be found. I have recently moved a whole bunch of stuff around....
Head to my new Blog
Where to find my old Blog