text:
Hurricane Norbert produced a 1-in-1,000 year rainfall event in Arizona in early September 2014. The fifteenth named storm, tenth hurricane, and seventh major hurricane of the 2014 Pacific hurricane season, Norbert originated from an area of disturbed weather in association with an area of low pressure on September 2. Tracking generally northwestward, the newly designated tropical storm steadily organized in a moderate shear environment. Norbert attained hurricane intensity early on September 4 and Category 2 hurricane strength the next afternoon. Thereafter, the cyclone began a period of rapid deepening, and it subsequently attained its peak intensity with winds of  and a minimum pressure of  early on September 6. A track over progressively cooler waters and into a more stable environment prompted a weakening trend after peak intensity, and by early on September 8, the system no longer maintained enough convection to be considered a tropical cyclone.

Meteorological history

On August 30, the National Hurricane Center (NHC) indicated the potential for an area of low pressure to form offshore the coastline of Mexico and slowly develop over subsequent days. This projection came to fruition the next afternoon, when a large area of showers and thunderstorms in association with a trough of low pressure was noted. Amid a generally favorable environment with moderate wind shear and warm sea surface temperatures, convection steadily coalesced atop a distinct low-level circulation, and the disturbance acquired enough organization to be deemed a tropical cyclone at 15:00 UTC on September 2; it was designated Tropical Storm Norbert in accordance with an Advanced Scatterometer (ASCAT) pass. Due to moderate northeasterly wind shear, only modest intensification was predicted. Norbert moved generally northwestward succeeding formation, steered around the southwestern periphery of a subtropical ridge across Baja California and northern Mexico. All the while, the cloud pattern of the cyclone progressively improved, with a symmetric central dense overcast and distinct rainbands on convectional satellite, and a formative inner core with hints of a small mid-level eye on hurricane imagery. In conjunction with satellite intensity estimates, Norbert was upgraded to a Category 1 hurricane on September 4.

Continuing on a general northwestward trajectory, increased easterly wind shear caused the system to temporarily lose organization during the pre-dawn hours of September 4 as the low- and mid-level circulations became dislocated. An Air Force Reserve Hurricane Hunter aircraft investigated Norbert that afternoon, recording peak flight-level winds of , maximum surface winds of , and a minimum barometric pressure of . Early on September 6, the cyclone began a period of unexpected rapid deepening; at 00:00 UTC, it was upgraded to a Category 2 hurricane, and at 06:00 UTC, it intensified a major hurricane, a Category 3 hurricane on the Saffir-Simpson Hurricane Wind Scale. After attaining its peak intensity with maximum winds of  and a minimum pressure of , Norbert began to track over cooler sea surface temperatures, and a weakening trend ensued. It was downgraded to a Category 2 hurricane at 21:00 UTC on September 6, and further to a Category 1 hurricane at 03:00 UTC the next day. Deep convection associated with Norbert began to wane significantly as the storm entered a stable environment, and a blend of satellite intensity estimates prompted the NHC to downgrade it to a tropical storm at 15:00 UTC. At 09:00 UTC on September 8, after having been devoid of deep, organized convection for over 12 hours, the system was declared a post-tropical cyclone. During the next few days, Nobert's remnants made a northward loop, before dissipating on September 11.

Preparations
Despite remaining well offshore the Mexican coast, classes in Manzanillo were suspended for a day. A "yellow" (moderate) alert was activated for Sinaloa, Nayarit, and Jalisco. Elsewhere, an "orange" (high) alert was issued for Soccoro Island, San Benedicto Island, and Baja California Sur. The southern portions of the state of Sonora was placed under a "yellow" alert, while a green alert was declared for the northern portions. The port of Guaymas was closed for small craft. Along the Baja California Peninsula officials activated 900 emergency workers to assist in the supply of food and fuel. Additionally, 164 shelters were opened. On September 5, the "orange" alert was upped to a "red" (maximum) alert.

When the remnants of Norbert spread into the United States, local National Weather Service offices issued flash flood watches and warnings, with watches posted across portions of California, Arizona, Nevada, Utah, and Colorado. Several schools in Arizona were closed or delayed due to flooding.

Mexican impact
Roads surrounding Manzanillo were closed for three hours due to landslides. Further north, several homes in Jalisco were flooded. In Nayarit, three people were evacuated to shelters. A man died in Mazatlán, Sinaloa after being swept away by a swollen stream, and two women in Chihuahua drowned while driving across a flooded creek. In Puerto San Carlos, a mudslide forced 425 people from two hotels to seek shelter. A dam collapsed northwest of the city due to the rains, causing flooding  deep in the town. The resultant floods damaged 2,500 homes and left about 2,500 people homeless, about one-third of its population. Throughout the municipalities of La Paz, Los Cabos, and Comondu, 2,000 people were evacuated to shelters, including 785 people in La Paz alone. Throughout the peninsula, 500 were rendered as homeless.

Southwestern United States flood event

The circulation of Norbert, in conjunction with the remnants of Atlantic Tropical Storm Dolly, spread moisture across northwest Mexico and into the southwestern United States. Rainfall in southern California peaked at around  in Hemet. The rains caused flooding along several freeways and other roads, stranding 70 cars along Route 74 near Mountain Center. Near Palm Springs, over 40 travelers required rescue after their cars were flooded. One nearby school was evacuated. Around 70 motorists got stuck on California State Route 74 due to flooding. Along the northern section of Riverside, many trees were toppled and power lines were knocked down. Almost all freeways across the Inland Empire were flooded. Damage in the state amounted to $706,000 (USD).

In Arizona, rainfall peaked at  near Chandler. During a seven-hour period, Phoenix Sky Harbor Airport recorded  of rainfall, breaking the 75‑year‑old daily rainfall record. It was also the highest precipitation in a single calendar day, but fell short of the station's 24‑hour rainfall total. The rainfall was more than the city's average summer rainfall. About one of every three Maricopa County rain gauges set all-time records. Accumulations in Chandler and Mesa were deemed to be a 1-in-1,000 year event while Phoenix was calculated to be a 1-in-200 year event. The floods covered several roads and highways, which closed portions of Interstates 17 and 10. County-wide, 10,000 customers lost power. In Mesa, residents from 100 homes were evacuated. Two women died, one in Pinal County and one in Tucson; both were swept away by floodwaters in their vehicles. Waters in Tucson reached as deep as . In several locations, pumping stations were unable to handle the deluge. About 10,000 people lost power in the state. In response to the flooding, Governor Jan Brewer issued a state of emergency and ordered nonessential workers to remain at home. Overall, the flooding was the worst to affect that state since 1970. Total damage statewide amounted to $18 million.

New Mexico Highway 152 suffered significant damage, with portions of the road washed away and debris covering large stretches of road. Due to the severity of damage, the New Mexico Department of Transportation closed the road indefinitely and stated it could be more than a month until it was re-opened.

In Nevada, rainfall totaled over  in a short period of time, causing the worst flooding in the Moapa Valley since 1981. The flooding prompted The National Weather Service to issue a strongly worded flash flood emergency for the Moapa Valley, advising people to avoid travel and keep local roads open for emergency operations. The waters closed a  section of Interstate 15 in both directions. Several vehicles were washed away along the interstate and damaged the road forcing the closure for several days. The cost of the repairs to the road are expected to be in excess of $5 million. Indian Reservation in Moapa was evacuated due to the floods. Up to 200 children were trapped in an elementary school due to waters  deep. Damage in the state amounted to $9.64 million.

See also

Other storms of the same name
Hurricane Doreen (1977)
Hurricane Nora (1997)
Hurricane Jimena (2009)
Hurricane Paul (2012)
Hurricane Linda (2015)
List of Baja California Peninsula hurricanes
List of California hurricanes
List of Arizona hurricanes

References

External links

 National Hurricane Center's advisory archive on Norbert
 National Hurricane Center's graphics archive on Norbert

2014 Pacific hurricane season
Pacific hurricanes in Mexico
Hurricanes in Arizona
Category 3 Pacific hurricanes
Norbert


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text:
Гаревая — река в России, протекает в Ильинском районе Пермского края. Река впадает в Камское водохранилище, устье реки находится в 776 км по правому берегу Камы. Длина реки составляет 29 км.

Исток реки на Верхнекамской возвышенности в 23 км к югу от посёлка Ильинский. Исток лежит на водоразделе с бассейном Ласьвы. От истока течёт на север, затем поворачивает на северо-восток. Протекает село Васильевское и несколько мелких деревень. Притоки — Майка-Шор, Михалиха, Долгая (левые); Чикман (правый). Впадает в вытянутый залив Камского водохранилища у села Филатово. В месте выхода залива в основную часть водохранилища стоит село Усть-Гаревая.

Данные водного реестра
По данным государственного водного реестра России относится к Камскому бассейновому округу, водохозяйственный участок реки — Кама от города Березники до Камского гидроузла, без реки Косьва (от истока до Широковского гидроузла), Чусовая и Сылва, речной подбассейн реки — бассейны притоков Камы до впадения Белой. Речной бассейн реки — Кама.

Код объекта в государственном водном реестре — 10010100912111100009882.

Примечания

Притоки Камы
Реки Ильинского района Пермского края

redpajama_set_name: RedPajamaWikipedia


text:
COMMONWEALTH OF KY MEDIA RELEASE: LEGISLATIVE LEADERS INVEST $10 MILLION IN LOUISVILLE ZOO KENTUCKY TRAILS SAFARI (Media Release)
Senate Majority Caucus
Release # 09-018
Contact: Angela Billings
angela.billings@lrc.ky.gov
Contact: Kyle Shepherd
(O) 502-238-5331 (C) 502-744-5639
LEGISLATIVE LEADERS INVEST $10 MILLION IN LOUISVILLE ZOO KENTUCKY TRAILS SAFARI
FRANKFORT, KY (September 22, 2022) — Senate Majority Caucus Chair Julie Raque Adams, R-Louisville, and Senate President Robert Stivers, R-Manchester, celebrated the $10 million in one-time funds the General Assembly invested to construct the Kentucky Trails Habitat at the Louisville Zoo today. Both were joined by Louisville Zoo Executive Director Dan Maloney and Louisville Zoo Foundation Chair Sheryl Snyder. City representatives on hand to express their appreciation to the General Assembly included Mayor Greg Fisher and Louisville Metro Councilman Anthony Piagentini.
"We are especially appreciative of President Stivers' and Senator Raque Adams' championship of this landmark appropriation. We are extremely grateful to all of our friends in the General Assembly for this incredible first step to making Kentucky Trails a reality!" Maloney said. "We look forward to working with all our supporters to see this project to completion for the sake of our wildlife and wild places. All species are interesting, and all creatures have their unique stories. We are so excited to showcase our region's wildlife and to inspire our guests to cherish and protect America's amazing animals."
This line item is a first for the Louisville Zoo. The habitat it will help fund will celebrate the wild and cultural heritages of Kentucky and for the first time will feature, large herds of bison and elk, flocks of turkeys and cranes, an "Upland South Safari" experience, a Rickhouse Hall restaurant for guests and catered evening events, paddle boats on the lake, local bourbonism and a bison encounter.
"Our exposure to the outdoors enriches our lives and this safari experience will bring our state's natural history and these amazing animals to families and children from all over the state and around the world right here in Louisville," said Adams. "Animals bring laughter and joy to our lives and I'm excited for the education and learning that will take place in such a fun and informative way."
"This is an unprecedented state appropriation for habitat design and development for the Louisville Zoo, and we are extremely thankful to the General Assembly for their support," said Snyder. "Families from all 120 Kentucky counties and tourists from across the United States visit the Zoo each year. With Kentucky Trails, these same families will be able to learn more about our native wildlife and natural heritage while visiting the #1 non-profit, paid-admission attraction in the state."
"This is a fine example of how a non-profit organization fuels the economy and the whole state benefits from it," said Stivers. "This one-time allocation demonstrates the General Assembly's commitment to investing in programs that reflect the natural treasure that will educate thousands of Kentucky residents and draw tourists to the commonwealth, fueling our economy and lifting our state up even more."
Piagentini, representing District 19 on the Louisville Metro Council, echoed Stivers' sentiments.
"The Louisville Zoo is a catalyst for learning, tourism and recreation. Every year, tens of thousands of students visit our state's zoo to learn about the importance of protecting animals and their habitats," Piagentini said. "The future Kentucky Wildlife exhibit will help further the connection of our zoo to the people of Kentucky and will draw even more visitors when it is opened in the coming years."
The Louisville Zoo, a non-profit organization and state zoo of Kentucky, is dedicated to bettering the bond between people and our planet by providing excellent care for animals, a great experience for visitors, and leadership in scientific research and conservation education. The Zoo is accredited by the Association of Zoos and Aquariums (AZA).
Visit legislature.ky.gov for more information on the 2022 state budget. Access archived footage from the 2022 Legislative Session at ket.org/legislature/archives. Live legislative coverage of ongoing 2022 Interim meetings is available at ket.org/legislature and via the Legislative Research Commission YouTube channel. Follow the Kentucky Senate Majority Caucus on Twitter, Facebook and Instagram.
Senator Julie Raque Adams, R-Louisville, represents Kentucky's 36th Senate District in eastern Jefferson County. She is the Senate Majority Caucus Chair. Adams serves as the co-chair of the Child Welfare Oversight and Advisory Committee. She also serves as a member of the Senate Standing Committees on Health and Welfare, Banking and Insurance, Licensing and Occupations, the Rules Committee, and the Committee on Committees. She was recently appointed to the Cabinet for Health and Family Services Organizational Structure, Operations and Administration Task Force for the 2022 Interim. Additionally, Adams is a member of the Legislative Research Commission; the Tobacco Settlement Agreement Fund Oversight Committee, and the Administrative Regulation Review Subcommittee.
For a high-resolution .jpeg of Raque Adams, please visit: https://legislature.ky.gov/Legislators%20Full%20Res%20Images/senate136.jpg.
Senate President Robert Stivers, R-Manchester, represents the 25th District, including Clay, Jackson, Knox, McCreary, Owsley, and Whitley Counties. He serves as chair of the Senate Committee on Committees and the Rules Committee. President Stivers is also co-chair of the Legislative Research Commission Committee. Additionally, he serves as a member of the Senate Standing Committees on Education and Judiciary, and was most recently appointed as co-chair to the Bourbon Barrel Taxation Task Force during the 2022 Interim.
For a high-resolution .jpeg of President Stivers, please visit: https://legislature.ky.gov/Legislators%20Full%20Res%20Images/senate125.jpg/.
Categories: Media Releases, Zoo News

redpajama_set_name: RedPajamaCommonCrawl


text:
Guest Post – Why oh why Waiuku?
By Enzo Giordani on August 23, 2018 • ( 3 Comments )
Mark O'Donnell
By Mark O'Donnell
Every footballer at every level longs to win a championship title. Indeed, some of the best footballers in the world never achieve that honour. For the 11 players on the pitch, 4 substitutes on the bench and all the management at Waiuku AFC they are 90 minutes away from achieving that prize. It has been a long time between titles for this small South Auckland club, about 20 years in fact.
The squad have trained lightly this week, looking to rest knocks and be fully fit for today's challenge. The weather has played its part and we are greeted with a semi sunny day and a pitch that is heavy and will test every players fitness level.
What a backdrop then to be playing our penultimate season's game against Pukekohe, a true derby match and our fiercest rivals. There will be no love lost today by either side and that's exactly how it should be. Pukekohe have had a disappointing season without a single win. They will want to spoil our party, stop us winning today and this is their cup final. Waiuku need to win today and clinch the title. The scene is set then for 2018's best Championship match.
The game is an arm wrestle from the beginning with Pukekohe matching Waiuku for endeavour and team spirit. Indeed half way through the first half the locals are cheering as a defensive mix up allows the Pukekohe striker to waltz through a flimsy defense and calmly slot the opening goal. Cue mass celebrations on and off the pitch as Pukekohe take an unlikely but really well appreciated (by their supporters), lead.
The game see saws for the next 20 minutes until a neat diagonal pass from Brad Holmes splits the square back line and finds Derek Sinclair in a one on one with the keeper. The striker keeps his nerve and drills a low hard shot across the keeper which swishes the vacant net. Just for a moment everything stops but then Sinclair is enveloped by relieved team mates. Not before he gives his Pukekohe marker a gob full though. The cheers are both filled with relief and celebration and the canny scot struts back to the halfway line chest out. The half ends soon after and both teams stride to their respective changing rooms.
The second half begins with Waiuku hot on attack. From a neat 4 pass movement Sam van Pomeran (the flying dutchman) beats the desperate lunge of a Pukekohe wide back and sends a sizzling low cross behind the defender and in front of the keeper into the "corridor of uncertainty". Legs flail from both sides but the crucial touch is supplied by Caine Robble and his face is etched with joy as the ball thunders past the keeper into THE BACK OF THE NET.
The Waiuku stalwart of 8 seasons has supplied the coup de gras and both the Waiuku bench and every player rushes to congratulate the tough uncompromising defender.
The rest of the half is played out with both sides looking to score. Pukekohe manage to do so but they are correctly ruled offside. Such are the fine margins in football between success and failure. Both sides manage numerous chances but neither can add to the scoreline.
So at 4.47 pm on the 18th day of August 2018 the blast of the referees acme thunderer signals wild celebrations for all associated with Waiuku AFC. Pukekohe provided great opposition and a stern challenge. They sportingly cheer and clap the Waiuku team after this bruising and enthralling encounter. The Waiuku team gather in the centre circle and celebrate their success fittingly. The local Waiuku Post paper is there to record the moment and players, management and supporters alike hug in response to the achievement.
We have a small squad of between 14-16 players and have only used 21 players all season. They are mostly local lads and have not received a cent for their toils but I have never witnessed a team this dedicated or loyal to a town nor football club. Waiuku AFC should indeed be proud of these lads.
I've personally had the privilege to coach higher ranked Northern League sides in University, Ellerslie and Onehunga Mangere over 10 years. I've been fortunate enough to win promotion and coach in all three NRFL divisions, Premier, First and Second. However, I have never enjoyed myself as much as I have this season.
People asked me at the beginning of the season, why oh why Waiuku? The answer is simple……. why not? They are a club with real spirit and passion and show that NZ football is alive and well for all the right reasons.
Categories: Other NZ Federation Leagues
Tagged as: Bledisloe Park guest posts Mark O'Donnell Pukekohe soccer Waiuku
Guest Post – Craigo
Red, white and Gray
Nice one marcus aurelius!
There may be bigger teams who win Championships , but the feelings of Elation, Pride, Elevated above the earth for a while, with the stars put the Waiuku Boys on a level with all the greatest Winners on a Football Field.
And… " corridor of uncertainty " … brilliant


text:
A Boy and His Blob är ett TV-spel till NES och Game Boy utvecklat 1989 av David Crane, skaparen av Pitfall!.

Spelet är ett sidoscrollande plattformsspel som handlar om en pojke och hans kompis Blobert som reser runt på jorden och Bloberts hemplanet för att besegra den onda kejsaren.

Spelsätt
Spelet gick ut på att den "blob", eller geleklump, som pojken har som vän kan transformera sig till olika saker baserat på vad den äter. På detta sätt kan man röra sig genom spelets banor på flera olika sätt.

Mottagande
A Boy and His Blob valdes till det bästa spelet under Consumer Electronics Show (CES) 1989 och fick även utmärkelsen Parents' Choice Award av Parents' Choice Foundation 1990.

Uppföljare
A Boy and His Blob har fått flera uppföljare, bland andra en till Nintendo DS och en till Nintendo Wii.

Referenser

Externa länkar
A Boy and His Blob: Trouble on Blobolonia på Nintendo.com

NES-spel
Plattformsspel
Datorspel 1989
Virtual Console-spel till Wii
Pusselspel


text:
Vodafone targets partnerships for global growth
by Anne Morris |
Jan 11, 2012 8:54am
Following a period during which it considerably scaled back its global portfolio, Vodafone has now outlined how it plans to make increasing use of partnerships to expand into fast-growing markets in Asia and South America in order to support international customers.
According to a Reuters report, the company said it will focus on securing new agreements with local operators, rather than making expensive investments as it has done in the past. This marks a renewed emphasis on partnerships by the UK-based operator, which has now sold non-controlling stakes in operators in France, China and Poland. Vodafone has already secured a deal in with SFR France, in which it used to own a 44 per cent stake: the Register reported that the two operators have now joined forces to deliver enterprise solutions.
Indeed, the provision of enterprise solutions is a major driver of the need to find new partnerships: in order to compete in this market, Vodafone needs to show multinational customers that it is able to support them on an increasingly global basis.
According to Reuters, Vodafone announced a new partnership in French Polynesia and said it expected to agree new deals in further territories in Asia and South America through 2012 and beyond.
Analysts welcomed the move, and see it as a reassurance that Vodafone is less likely to spend large amounts of cash on M&A: "Investors will take comfort that rather than splurging cash...they're seeking to get all the benefits of the brand, all the benefits of roaming, all the benefits of being big without blowing a lot on control premiums," Liberum analyst Mark James told Reuters.
Nevertheless, the Register noted that the MNO is still pouring money into India--despite that market only yielding an average revenue per user of around $2 a month.
According to Bloomberg, Vodafone remains confident that it will be able to increase revenue from the growing take-up of data services in India. The contribution of data to the unit's total revenue will rise to 10 per cent in two years from about 3 per cent at the end of September, Samaresh Parida, the Mumbai-based director of strategy at Vodafone India Ltd., told Bloomberg.
- see this Reuters article
- see this Register article
- see this Bloomberg article
Analysts: Vodafone/Verizon merger would make sense
Mallinson: Would Vodafone put Verizon Wireless' free cash flow to better use?
Vodafone hikes full-year outlook on growth in emerging markets
Rumour Mill: Vodafone plans widespread brand overhaul
Vodafone overhauls Asian partnerships
Vodafone rewards shareholders with £2B Verizon dividend payment
Anne Morris
https://twitter.com/fiercewirelesse
https://fr.linkedin.com/in/annelmorris


text:
Brun amarant (Lagonosticta nitidula) är en fågel i familjen astrilder inom ordningen tättingar.

Utbredning och systematik
Fågeln förekommer från Angola till Demokratiska republiken Kongo, Zambia, södra Tanzania, norra Namibia och norra Zimbabwe. Den behandlas som monotypisk, det vill säga att den inte delas in i några underarter.

Status
IUCN kategoriserar arten som livskraftig.

Noter

Externa länkar

Astrilder
Fåglar i etiopiska regionen


text:
New Children's Book Teaches Shark Conservation
These days, you can find just about any shark-themed items marketed for kids: There are t-shirts, board games, pencils, plush toys and even a remote-controlled flying shark. But try to find material that explains to kids what sharks really do for the oceans and what dangers they face, and you are out of luck.
Karen Lamberson noticed this too. An art teacher for 16 years, Karen is fascinated by sharks and wants to share her passion with others. She caught the attention of her students and staff by showing clips from informative films like "This is Your Ocean: Sharks," featuring Jim Abernethy (Shark Savers Advisor), Dr. Guy Harvey, and Wyland. Karen created lesson plans centered on the importance of sharks in the ecosystem.
But when it came to providing educational materials, everything Karen could find portrayed sharks as an evil villain to be feared but not understood. There needed to be a spokesperson, or "spokeshark," that could encourage the next generation to see sharks as the fascinating animals they are, not man-eating monsters. So Karen sat down and created Professor Clark the Science Shark.
Professor Clark the Science Shark follows the life and adventures of an extraordinary tiger shark who wants to teach others about ocean ecosystems after he discovers his family was overfished.
The beautifully illustrated series of books follows the little pup on his journey to become a professor in poignant storylines that reflect the message of shark conservation. Karen contacted Shark Savers to make sure that her message was backed by sound science and we were happy to provide her with the most effective conservation messages that she weaved into her story to reflect the natural world of a tiger shark as much as possible, without losing the magic of an imaginary, talking shark professor!
Karen is now working closely with Shark Savers to create more stories about endangered marine life like Hannah the manta ray, and Shiv the whale shark, as well as teaming up with Coast Ecology and Jim Abernathy's Scuba Adventures for stories on ocean pollution, coral reef protection, the Sargasso Sea and other issues affecting the ocean's ecosystems.
The first book in the Professor Clark Series, The Beginning, will soon be available in the Shark Savers store and it can be currently bought at www.ProfessorClark.com.


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text:
Tisdale ist eine Kleinstadt in der kanadischen Provinz Saskatchewan mit einer Einwohnerzahl von 3235 (Stand: 2016).

Geographie
Tisdale liegt ca. 40 Kilometer östlich von Melfort und 60 Kilometer südlich von Nipawin. Die Verbindungsstraßen Saskatchewan Highway 35 und Saskatchewan Highway 3 kreuzen sich im Ort. Tisdale wird von der Canadian National Railway und der Canadian Pacific Railway bedient.

Geschichte
Aufgrund des fruchtbaren Bodens ließen sich Siedler in der Gegend nieder. Die Infrastruktur entwickelte sich mit der 1904 erfolgten Anbindung an die Canadian Northern Railway weiter positiv. Die offizielle Stadtgründung fand im Jahr 1920 statt. Der Ort wurde zu Ehren des Eisenbahnangestellten Frederick W. Tisdale benannt.

Tisdale ist in der Provinz Saskatchewan für den Anbau von Raps (rape) und die Gewinnung von Honig (honey) bedeutend. Für über 60 Jahre warb die Stadt deshalb mit dem Slogan: Land of Rape and Honey (Das Land von Raps und Honig). Da aber in der englischen Sprach rape gleichzeitig Vergewaltigung bedeutet, kam es häufig zu Missverständnissen. Im Herbst 2015 entschloss sich die Stadtverwaltung deshalb, den Slogan in: Opportunity Grows Here, frei übersetzt etwa "Hier wachsen Möglichkeiten" zu ändern. Zu dem Spruch sind auf dem neuen Logo noch eine Sonne, ein grüner Acker und Kornähren zu sehen. Im Jahr 2006 wurden in Tisdale und Umgebung mehr als vier Millionen Kilogramm Honig hergestellt, was ca. 10 % der gesamten kanadischen Produktion entspricht. Als Touristenattraktion ist im Ort die überdimensionale Skulptur einer Honigbiene aufgestellt (World's Largest Honey Bee).

Demografische Daten
Im Jahre 2011 ergab sich eine Bevölkerungszahl von 3180 Personen. Dies bedeutet eine Zunahme um 6,0 % gegenüber 2006.

Persönlichkeiten
 Susan Aceron (1972–2016), Synchronsprecherin und Schauspielerin

Einzelnachweise

Weblinks
 bigthings.ca – Bienenstandbild
 tisdale-and-district-museum – Tisdale and District Museum

Ort in Saskatchewan
Ort in Nordamerika
Town in Saskatchewan
Gegründet 1920


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text:
layout: post
title: "The Evolution of Convolutional Networks"
description: ""
category: Machine Learning
tags: [Neural networks]
---

This blog post briefs the evolution of  Convoluational Neural Networks (CNN).  The selected CNNs were developed for the ImageNet Large-Scale Visual Recognition Challenges (ILSVRC).  They are reviewed according to their time of publications chronologically.

1989: LeNet
==

LeCun proposed LeNet (LeCun, 1989), one of the first CNNs, for the application of digit recognition.  The LeNet laid the foundation for Modern CNN models.  Some of  its characteristics, such as local connectivity,  weight sharing, and sub-sampling, are still shared by recent CNNs.  Detailed discussion of LeNet can be found in my previous [post](https://const-yield.github.io/2017-04-12-What-is-a-convolutional-network/)  "What is a convolutional neural network".

2012: AlexNet
==

After an incubation time of almost 20 years (from 1989 to 2012), the machine learning community witnessed the debut of AlexNet  (Krizhevsky, 2012) in 2012, a breakthrough for deep learning.  AlexNet was a CNN designed to recognize pictures in the ImageNet dataset, which contains over 15 million images in over 22,000 categories.

Recognizing such a large volume of object categories requires  a model with a large learning capacity.  CNNs are good candidate for such a learning task due to:

- The capacity of CNN models are controlled by their depth and breadth
 - They have strong and mostly correct assumptions about the nature of images
 - They have fewer connections than standard feed-forward neural networks

AlexNet was one of the largest convolutional neural network at the time of publication used in ILSVRC-2010 and ILSVRC-2012 competitions.  Its architecture consists of eight learned layers: five convolutional and three fully-connected layers (See Figure 1).

Figure 1.  The architecture of AlexNet (Krizhevsky, 2012)

It was written with a highly-optimized GPU implementation, with a number of new features to improve its performance and reduce its training time:

-  Rectified Linear Units (ReLU) for faster training: the experiment results showed that networks with ReLUs consistently converge faster than those with saturating neurons.
-  Training on multiple GPUs: the parallelization scheme puts half of the kernels on each of the two GPUs
-  Local Response normalization: though ReLUs have the property that they do not require input normalization to prevent them from saturating, local normalization was still found to aid generalization.

The following techniques were used in AlexNet to reduce over-fitting:

- Data augmentation -- artificially enlarge the data set using label-preserving transformations
- Dropout- randomly set zero to the output of each hidden neuron with a probability of 0.5

The AlexNet (single-CNN) obtained a top-5 error of 18.20% on the ILSVRC-2012 validation set.

2014: VGG Net
==
After the debut of AlexNet in 2012, a number of attempts had been made to tweak the structure of AlexNet to achieve better performance. The VGG network is a successful one of those attempts.

One prominent feature of the VGG net is that filters with very small receptive fields were employed throughout the whole network.  According to (Simonyan, 2014),  the
benefit of using small receptive field is two-fold:

- It makes adding more convolutional layers feasible due to its low computational cost
- Multiple convolutional Layers without spatial pooling in between has effectively bigger receptive field ( See [here](https://www.quora.com/What-is-a-CNN%E2%80%99s-receptive-field) for detailed explanation )

Another salient feature of the VGG net is its depth. In comparison with the AlexNet, it extended its depth to up to 19 layers.

The features of VGG's architecture are summarized below:

- Filters with very small 3-by-3 receptive field were used throughout the whole  net, which were convolved with stride 1.
- 1-by-1  convolutional filters were also incorporated to enhance the nonlinearity of the design function without affecting the receptive fields
- Spatial padding is such that the spatial resolution after convolution was preserved
- Spatial pooling is carried out by five max-pooling layers.
- Max-pooling is performed over a 2-by-2 pixel window, with stride 2.

Details of its architecture can be found in Figure 2.

Figure 2.  The architecture of VGG Net (Simonyan, 2014)

The VGG net (single net) obtained a top-5 error of 6.8% on the ILSVRC-2012 validation set.

2015: GoogLeNet
==
Increasing the size of a deep neural network is perhaps the most straightforward way of improving its performance.  This can be done by increasing the depth ( the number of network levels) or the width ( the number of units at each level). However the drawbacks of this simple solution comes with a larger number of parameters , and increased use of computational resources.

GoogLeNet is the efficient network architecture proposed in (Szegedy, 2015). Its goal is to keep a computational budget of 1.5 million multiply-adds at inference time, so that the networks can be put into practical use at a reasonable cost.  A new  level of network organization named "Inception module" was introduced into the architecture to enable GoogLeNet to "go deeper with convolution".

The Inception architecture considers how an optimal local sparse structure of a convolutional vision network can be approximated and covered by readily available dense components.  Two types of Inception architectures were introduced, namely the na?ve version, and a dimention-reduced version.

The na?ve Inception architecture (shown in Figure 3) has the following features :
- As suggested by (Arora, 2014), a  layer-by-layer construction is employed, where one should analyze the correlation statistics of the last layer and cluster them into groups of units with high correlation. These clusters form the units of next layer and are connected to units in the previous layer.
- It is assumed that each unit from an earlier units  corresponds to some region of the input image and these units are grouped into filter banks. As a result, lots of clusters will concentrate in a single region and they can be covered by a layer of 1-by-1 convolution.
-  To avoid patch-alignment issues,  the implementation of  current Inception architecture is restricted to 1-by-1, 3-by-3 and 5-by-5 filter sizes
-  Due to the prevalence of the  pooling operations are in convolutional networks, the Inception architecture adds an alternative parallel pooling path in each stage for additional benefits

Figure 3.  The na?ve Inception architecture (Szegedy, 2015)

However this na?ve Inception module has excessive number of outputs due to the merge of pooling and convolutional outputs.  To tackle this problem, 1-by-1 convolutions are used to reduce the output dimension before performing the expensive 3-by-3 and 5-by-5 convolutions (See Figure 4).

Figure 4.  The Improved Inception architecture (Szegedy, 2015)

The GoogLeNet is a 22-layer-deep network which deploys the Inception modules at higher layers, while keeping lower layers in traditional convolutional manner.  This is for obtaining memory efficiency during training but not necessary.  GoogLeNet employs only 5 million parameters, which is only 1/12 of the number of parameters in its predecessor AlexNet. The architecture of GoogLeNet is described in Figure 5.

Figure 5.  The GoogLeNet architecture (Szegedy, 2015)

The GoogLeNet obtained a top-5 error of 6.67% on the ILSVRC-2014 validation set, ranking first among other participants.

2015: BN-Inception
==

Stochastic Gradient Descent (SGD) has proved to be a simple and effective means of training deep networks,  however it requires careful tuning of the hyper-parameters for the model,  especially the learning rates, and initialization values.   As the input to each layer is affected by  the parameters of preceding network layers,  the distribution of layers' input changes from one layer to another.  This has caused issues to the training  as the layers need to continuously adapt to new distributions.   Having a fixed distribution across layers makes training more efficient, as the parameters do not need to readjust to compensate for the change in the distribution.

The change in the distributions of internal nodes of a deep network is referred to as ***Internal Covariance Shift.*** A new mechanism called ***Batch Normalization*** is proposed to reduce internal covariance shift. This is done by a normalization step that fixes the means and variances of layer inputs.  Experiment results show that Batch normalization allows higher learning rates without the risk of divergence, and it regularizes the model and reduces the need for dropout.

The BN-Inception model reached a top-5 error of 4.9% on the ILSVRC-2012 validation set.

2015: The Highway networks
=

Network depth, i.e., the number of successive computational layers,  has played an important role in the success of convolutional networks.  This is due to that deep networks can represent certain function classes much more efficiently than the shallow ones.  However as the network depth increases, the training of the network also gets difficult.

Inspired by the skip connections between layers used in neural networks, Srivastava proposed the Highway Networks in (Srivastava, 2015). The Highway Networks modified the architecture of very deep feed-forward networks to make it easier to flow information across layers.  This was realized through an LSTM-inspired adaptive gating mechanism.

The experiment results in Figure 6. show that Highway network achieves lower training accuracy with deeper networks.

Figure 6.  Comparison of optimization of plain networks and highway networks of various depths. (Srivastava, 2015)

2016: Inception V2 and V3
==

In comparison with VGG net, the computational cost of Inception is much lower. However the complexity of the Inception architecture    hinders the changes to the network.  It makes it difficult to adapt the Inception architecture to new use-cases.

Szegedy et al. described a few general principles and optimization ideas for scaling up the Inception architecture efficiently in (Szegedy, 2016a) :

- Higher dimensional representations are easier to process locally within a network. Increasing the activation per tile in  a convolutional network allows for more disentangled features, and thus the network can be trained faster.
- Spatial aggregation can be done over lower dimensional embedding without much or any loss in representation power.
- Avoid representational bottlenecks, especially early in the network.
- Balance the width and depth of the network

In light of these guidelines, they proposed Inception V2 and V3 architectures. One outstanding feature of those architectures is the reduction of activation before aggregation.  This feature is implemented due to that the outputs of near-by activation in vision networks are expected to be highly-correlated. And therefore their activation can be reduced before aggregation.  By doing so, similar expressive local representations can still be achieved.

The features of Inception V2 and V3 include:

- Factorization into smaller convolutions. Similar to VGG Net,  Inception V2 replaces convolutions with large spatial filters  by a two-layered convolutional architecture.  Specifically It replace the 5x5 convolution with two layers of 3x3 convolutions.

Figure 7. Mini-network replacing the 5x5 convolutions. (Szegedy, 2016a)

Figure 8.Inception modules where each 5x5 convolution is replaced by two 3x3 convolution. (Szegedy, 2016a)

-              Spatial factorization into asymmetric convolutions

                Convolutions with 2 dimensional filters (e.g., 3x3 filters) can be factorized into asymmetric convolutions.  One example is that, a 3x1 convolution followed by a 1x3 convolution is equivalent to a 3x3 convolution with the same receptive field.  In theory, any n-by-n convolution can be replaced by a 1xn convolution followed by a nx1 convolution. The savings in the computational cost increases as n grows.

Figure 9. Mini-network replacing the 3x3 convolutions. (Szegedy, 2016a)

-  Efficient Grid Size Reduction
                Traditionally pooling operations are used to decrease the grid size of the feature maps.  To avoid a representational bottleneck,  the activation dimension of the network filter is expanded.  That means the overall computational cost is dominated on the convolution on the expanded grid.  The solution to reduce the computational cost is to employ two parallel blocks,  pooling and convolutional  layer.

Figure 10. Inception modules that reduces the grid-size while expands the filter banks. (Szegedy, 2016a)

- Model Regularization via Label Smoothing
A mechanism is proposed for encouraging the model to be less confident to alleviate over-fitting.  The idea is to replace the ground-truth label distribution with a mixture of the original ground-truth distribution and a fixed prior distribution on labels.  Such mechanism is termed label-smoothing regularization (LSR).

Inception V3, which ships with label smoothing, factorized 7x7, and batch normalization,  reached a top-5 error of 3.585% on the ILSVRC-2012 validation set.

2016: The Residual networks (ResNet)
==

Deep network models have been exploited on ImageNet databases.  However learning better networks is not as easy as stacking more layers.  For one thing, vanishing/exploding gradients hamper convergence from the beginning. Though this problem has been largely addressed by normalized initialization and intermediate normalization layers, accuracy gets saturated with the network depth increasing. Since the degradation of accuracy is not caused by over-fitting, adding more layers leads to higher training error, as depicted in Figure 11.

Figure 11. Training error (left) and test error (right) on CIFAR-10 with 20-layer and 56-layer plain networks. The deeper network has higher training error, and thus higher test error. (He, 2016)

Given a deep learning architecture, its deeper counterpart can be constructed by adding more identity mapping layers on top of its original layers. Due to the identity mapping, such construction solution should produce no higher training error than its shallower counterpart. However experiments show that the current solvers might have difficulties in  approximating identity mappings by multiple nonlinear layers. This prompts the use of residual mapping.

The ResNet was proposed (He, 2016) to address the degradation problem by fitting a  residual mapping, instead of the desired underlying mapping.  Formally, Let the desired underlying mapping be H(x),  ResNet let the stacked nonlinear layers fit another mapping F(x) := H(x) -x.  The original mapping is recast into F(x)+x.  It is hypothesized that it is easier to optimize the residual mapping than the original mapping. The formulation of F(x) + x can be realized by "shortcut connections", as shown in Figure 12.

Figure 12.  Residual learning: a building block. (He, 2016)

In ResNet, short cut connections are simply identity mappings, which introduce neither extra parameters nor computational complexity.  As a result, the constructed network can still be trained in an end-to-end manner by SGD with backpropagation.

In ResNet, the residual learning is adopted to every few stacked layers.  Note that the form of function is flexible. Experiments in (He, 2016) concern a function F that has two or three layers.  The architecture for ResNet is demonstrated in Figure 13.

Figure 13. The ResNet achictecture (He, 2016)

The ResNet achieved reached a top-5 error of 3.57% on the ILSVRC-2015 validation set.

Summary
==

The evolution of CNN dated from 1989, when LeNet was proposed. However due to the insufficient support of hardware for its computational cost,  the development of CNN experienced an incubation time of 20 years.  The introduction of AlexNet in 2012 was a leap in the history of CNN.  AlexNet has inspired its successors, in the sense that some of its features are still shared by them.

A number of CNNS have been developed, based on the architecture of AlexNet, for example, VGG Net (2015),  GoogLeNet (2015),  BN-Inception (2015),  Highway Net(2015) Inception V2 and V3 (2016), and the ResNet(2016). The evolution and relation of these networks are depicted in Figure 14.

Generally speaking, they can be divided into two streams. One stream focused on extending the network depth to exploit the expressiveness of depth network; VGG Net, Highway Net, and ResNet are representatives.   Another stream emphasized on developing efficient network architectures by deploying modules of mini-networks inside a network; GoogLeNet, BN-Inception, Inception V2 and V3 all contain  modules of mini-networks. Both streams had achieved gains in performance for ILSVRC.

Figure 14.   The CNN evolution

We have only covered a selected number of CNNs in this blog post. The evolution of CNNs is still on-going. With the advance of GPU, and open-source library, it is expected that the evolution would be happening at a much faster pace then before.

References
=
(LeCun, 1989) LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., & Jackel, L. D. (1989). Handwritten digit recognition with a back-propagation network, 1989. In Neural Information Processing Systems.

(Krizhevsky, 2012)  Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems  (pp. 1097-1105).

(Arora, 2014) Arora, S., Bhaskara, A., Ge, R., & Ma, T. (2014). Provable Bounds for Learning Some Deep Representations. In ICML (pp. 584-592).

(Simonyan, 2014)  Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556.

(Szegedy, 2015) Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., & Rabinovich, A. (2015). Going deeper with convolutions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1-9).

(Loff, 2015) Ioffe, Sergey, and Christian Szegedy. "Batch normalization: Accelerating deep network training by reducing internal covariate shift." arXiv preprint arXiv:1502.03167 (2015).

(Srivastava, 2015) Srivastava, R. K., Greff, K., & Schmidhuber, J. (2015). Training very deep networks. In Advances in neural information processing systems (pp. 2377-2385)

(Szegedy, 2016)  Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., & Wojna, Z. (2016). Rethinking the inception architecture for computer vision. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2818-2826).

(Szegedy, 2016)  Szegedy, C., Ioffe, S., Vanhoucke, V., & Alemi, A. (2016). Inception-v4, inception-resnet and the impact of residual connections on learning. arXiv preprint arXiv:1602.07261.

(He, 2016) He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770-778).

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I was thinking of organising a little ride out down to the Ace and then do some bowling after that. Speaking to bikerbabe earlier she recommends a Friday night as the Ace is always pack with bikes. No dates has been fixed yet , I just wanted to run pass here first and see how many people would be up for it and then I could arrange it.
If any of you would rather do something else instead of bowling or know of a nice chilling place then let me know. I would prefer for it not to be local because I want it to be a rideout and enjoy the bikes .
Excellent idea Bowling would be alot of fun!
Riding from a Crystal Palace seems to work with everyone but someone would need to lead who knows their way to Ace Cafe.
lol someone borrowed my "L"
I take it that there's not many interested in this ???
so we got 4 so far ! Any more ??
if any body has got a good meeting where it would be ideal for every one pls let me know .
Some people say I am crazy, personally I think it's everyone that is craz y n I am the only sane one left and the voices agree !


text:
Q: Codeigniter sort by date array i merge my array then i want to sort them by date but my loans and colls have different names in date
heres my code for the merging
 $loan = $this->db->get('loans')->result_array();
 $coll = $this->db->get('collectables')->result_array();
 $result = array_merge($loan, $coll);

and heres the output
Array
(
[0] => Array
    (
        [loan_id] => 175
        [loan_fullname] => Albano, Zester Quinn
        [loan_amount] => 15000
        [loan_interest] => 2
        [loan_date] => 2017-05-30
        [loan_total_amount] => 15300
        [loan_collectables] => 1
        [loan_user_id] => 30
    )

[1] => Array
    (
        [loan_id] => 176
        [loan_fullname] => Amamio, Alyanna
        [loan_amount] => 15000
        [loan_interest] => 2
        [loan_date] => 2017-05-31
        [loan_total_amount] => 15300
        [loan_collectables] => 2
        [loan_user_id] => 32
    )

[2] => Array
    (
        [coll_id] => 92
        [coll_date] => 2017-05-30
        [coll_amount] => 15300
        [coll_loan_id] => 175
        [coll_user_id] => 30
    )

[3] => Array
    (
        [coll_id] => 93
        [coll_date] => 2017-05-28
        [coll_amount] => 7650
        [coll_loan_id] => 176
        [coll_user_id] => 32
    )

 [4] => Array
    (
        [coll_id] => 94
        [coll_date] => 2017-06-21
        [coll_amount] => 7650
        [coll_loan_id] => 176
        [coll_user_id] => 32
    )
)

but i want to sort them by date.. any ideas?? thanks

A: Hello yes you cant sort the arrays by date you need to use the function asort(if you want to do ascending sort), user arsort(if you want to do decending sort). here is the example that will make you understand.
$age = array("Peter"=>"2017-05-30", "Ben"=>"2017-01-31", "Joe"=>"2017-05-30");
asort($age);
foreach($age as $x => $x_value) {
    echo "Key=" . $x . ", Value=" . $x_value;
    echo "<br>";
}

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Voltage-Sourced Converter (VSC) based Static Synchronous Compensator (STATCOM) is used in transmission and distribution systems for the purpose of voltage regulation and reactive power compensation. In the transmission level, angle-controlled STATCOMs are of primary interest due to their high efficiency and excellent waveform quality. This type of the STATCOM is fired at line frequency to lower the switching losses. There are considerable numbers of angle-controlled STATCOMs installed in the different utilities in the United States. Despite the high efficiency and good voltage quality, this type of the STATCOM is showing poor performance under AC-system faults. They are usually tripped under severe unbalanced condition and system faults to protect the switches from huge negative sequence current flow. This paper provides a solution to improve the transmission level STATCOM performance under power system faults. Proposed solution is based on adding a single phase inverter in series with converter DC-bus. This single phase inverter generates controllable oscillations with twice the line frequency on the DC-link voltage which will be reflected as negative sequence voltage at VSC output terminals. Generated negative sequence voltage limits the fault negative sequence current flow on the STATCOM tie line. Based on the proposed Solution one specific controller is designed which provides the capability of simultaneous controlling of the both positive and negative sequence voltages. The results are supported by detailed simulation studies on the New York Power Authority (NYPA) STATCOM model using the PSCAD/EMTDC.


Citation: HENRY CAHYADI WILLEM (2006-12-09). Thermal and indoor air quality effects on physiological responses, perception and performance of tropically acclimatized people. ScholarBank@NUS Repository.
Abstract: This thesis focuses on the occupantsa?? responses to the thermal environment (air temperature) and indoor air quality (outdoor air supply rate). Results are derived from a series of independent intervention studies in real offices and two field laboratory experiments. The mechanisms for transducing the effects of indoor conditions to work performance were explored. The intervening variables are perceptual responses including the SBS symptoms and physiological measures such as cutaneous responses and salivary biomarkers. Thermal environment and indoor air quality significantly affect the work performance of tropically acclimatized office workers. These effects are associated with changes of perceptual responses, SBS symptoms and/or physiological measures. Two mechanisms via perceptual constructs and psycho-physiological measures are established as plausible pathways related to work performance. A structural model, termed: Man - Performance - Indoor Environment Structural Model (MPIESM), is developed. Increased performance of 3.0-8.2% justifies the costs of improved thermal condition or indoor air quality.


TPID students from all Departments will be required to take the core courses (1-4) below. In addition, Molecular Medicine Students will be required to take part in (5); Biomedical Engineering in (6); Microbiology in (7); and Pathology students in (8). Required courses for Departments not listed above will be developed with the Graduate Director of the respective Departments. Representative course syllabi for the courses listed below are provided in the following websites: (www.bumc.bu.edu/gms and www.bu.edu/bme/graduate/courses).
(GMS FC701 2 credits – www.bumc.bu.edu/gms) This first module will provide students with a quantitative understanding of protein structure, function, posttranslational modification and the turnover of proteins in the cell. In addition, students will gain facility with thermodynamics, catalysis, kinetics and binding equilibriums as they apply to proteins and also to other molecules in biological systems (e.g. nucleic acids, lipids, vitamins, etc.).
(GMS FC702, 2 credits – www.bumc.bu.edu/gms) The second module will focus on the mechanisms of biological processes that influence the inheritance, regulation, and utilization of genes. Genetic and genomic, molecular, cell biological, and biochemical experimental approaches to understanding these processes will be explored. In addition, we will discuss the possibilities of utilizing these technologies in medical therapies.
(GMS FC703, 2 credits – www.bumc.bu.edu/gms) The third module will focus on the movement of proteins and membranes with the cell, the secretory process, the cytoskeletal framework of the cell and the resulting cell-cell interaction and communication with the matrix. Molecular, cell biological, and biochemical experimental approaches to understanding these processes will be explored. In addition, we will discuss the possibilities of utilizing these technologies in medical treatments.
(GMS FC704, 2 credits – www.bumc.bu.edu/gms) The fourth module will focus on the mechanisms of cell communication. This module will begin by discussing overarching concepts before examining the specific types of molecules that initiate and transduce signals. Examples of cell signaling and subsequent cellular responses will be considered in different contexts to provide a framework on which future learning can be applied. As the module progresses, the complexity of the systems explored will increase from individual cells to multicellular environments such as tissues, organs, and organisms.
(2) Comprehensive Immunology (GMS MI 713, 4 credits- www.bumc.bu.edu/gms): This course is a comprehensive introduction to immunologic principals and applications. Emphasis is placed on analysis and interpretation of data from the primary literature.
(3) Immunological Basis of Disease (GMS MI 715; 4 credits- www.bumc.bu.edu/gms): This course is an in depth analysis of historically significant and contemporary topics in cellular and molecular immunology with a focus on immunologically based diseases. Emphasis is placed on the in-class discussion of research papers.
(4) Inflammatory Diseases and Therapeutics (GMS MM 2 credits). This course examines modalities that have been used to alter inflammation to either enhance the process to aid in protection from pathology, or to minimize inflammatory responses to treat sequelae associated with an over-exuberant immune response. This course examines common mechanisms of inflammatory processes with regard to disease induction, and to interventions to prevent or alleviate these inflammatory disorders.
(5) Genetics and Epidemiology of Human Diseases (GMS MM701, 4 credits- www.bumc.bu.edu/gms). This course covers fundamentals of the genetics of common human diseases and discusses examples of epidemiological approaches to study human disease.
(6) Molecular Bioengineering (ENG BE505, 4 credits- www.bu.edu/bme/graduate/courses). This course is an engineering science based introduction to the building blocks of living cells and materials for biotechnology. Throughout the course, detailed structural and energetic properties of molecules are emphasized.
(7) Concepts in Microbiology (GMS MI 700, 4 credits- www.bumc.bu.edu/gms): This course provides a fundamental understanding of the world of microbes and the concepts and mechanisms involved as microbes adapt in changing environments.
(8) Basic and Experimental Pathology (GMS PA 700, 6 credits- www.bumc.bu.edu/gms). This course provides an overview of the basic principles of Pathology through a lecture format. Topics include acute and chronic inflammation, pathology of auto-immunity, cancer immunology, and wound healing.


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What A Nuisance (1978–2005) was a New Zealand-bred Thoroughbred  racehorse. He was best known for winning the Melbourne Cup at Flemington Racecourse in November 1985.

Background
What A Nuisance was a bay horse with a white sock on his right hind foot bred in New Zealand by. He was sired by St Puckle, a British-bred son of the 1960 Epsom Derby winner St. Paddy. His dam, Fashion Bell was a descendant of The Witch, a British mare who was exported to Australia in the late 19th century, becoming the grand-dam of the 1902 Melbourne Cup winner The Victory.

Racing career
In early 1984 What A Nuisance, trained by Ken Rogerson won four consecutive races and was made favourite for the Sydney Cup in April despite being treated for a leg injury on the eve of the race. The gelding finished sixth in the race, aggravating the injury. What A Nuisance had recently been one of a group of fifteen horses bought from Rogerson's stable by the businessman Lloyd Williams who along with Dennis Gowing co-owned the gelding for the remainder of his racing career. Williams had previously owned the 1981 Melbourne Cup winner Just A Dash. Attempts to bring What A Nuisance back in the spring failed, as he developed problems with his suspensory ligaments and was kept off the racecourse for a further nine months. He was then sent to be trained by John Meagher.

In the winter of 1985, What a Nuisance returned to racing at Bendigo where he ran five times, winning once. He then finished second to Black Knight at Moonee Valley Racecourse in September and then finished sixth in the Group 1 Caulfield Stakes. He completed his Cup preparation by running fourth in the Moonee Valley Cup and fifth in the Mackinnon Stakes.

At Flemington Racecourse on 5 November What A Nuisance started at odds of 15/1 in a field of twenty-three runners for the Melbourne Cup. The race was sponsored for the first time by the Foster's Group and carried record prize-money of over A$1,000,000, making it the most valuable race ever run in Australia. The race attracted a crowd of 79,126 which included the Prince and Princess of Wales. Ridden by the veteran Pat Hyland, What A Nuisance was drawn badly but appeared well-suited by the wet conditions. Hyland allowed the gelding to relax in the early stages before producing a strong late run to win by a nose from the mare Koiro Corrie May.

Retirement
What A Nuisance was retired to Hyland's property at Clyde, near Cranbourne, Victoria. He  died suddenly on 19 April 2005 at the age of 26. An emotional Hyland described him as "a truly honest and game racehorse".

Pedigree

What A Nuisance was inbred 3 × 4 to Aureole, meaning that this stallion appears in both the third and fourth generations of his pedigree.

Namesake
Australian rail operator CFCL Australia named locomotive FL220 after the horse.

References

1978 racehorse births
2005 racehorse deaths
Melbourne Cup winners
Racehorses bred in New Zealand
Racehorses trained in Australia
Thoroughbred family 1-o


The course aims to provide the trainees with introduction knowledge and understanding of basic theory and practical skills necessary for a Yacht Skipper up to 200GT.
The course is designed for all candidates that want to become Yacht Skipper up to 200GT and meet the conditions set out in the Regulation on ranks and certification of seafarers (Official Gazette of Montenegro number 55/2013).
Candidates successfully completing the course will be competent to navigate, determine the position on paper and electronic charts, use instruments and nautical publications on the yacht, steer and manoeuvre, understand the yacht engine systems (engine, installation – switchboard, autopilot, mooring and berthing equipment). Will gain knowledge about rules and regulations referring to safety at sea, maritime meteorology and oceanography and maritime law together with communication in English language in case of distress, urgency and safety using Standard Marine Communication Vocabulary and Standard Maritime Communication Phrases.
Officers who would like to undertake this course must have approved seagoing service of not less than 12 months as Yacht Skipper up to 100 GT orbe in possession of a valid CoC (minimum Officer in charge of a navigational watch or Officer in charge of an engineering watch).
The course takes full account of the detailed outline set in D.10. part of the Regulation on ranks and certification of seafarers (Official Gazette Montenegro number 55/2013).


text:
Glenlochy war eine Whiskybrennerei in Fort William, Inverness-shire, Schottland. Die Brennereigebäude sind in den schottischen Denkmallisten in die Kategorie B einsortiert.

Geschichte
Die Brennerei wurde 1898 im damals noch außerhalb von Fort William liegenden Inverlochy gegründet. Da zur Zeit der Gründung eine schlechte Wirtschaftslage vorherrschte, wurde die Brennerei ab Eröffnung am 4. April 1901 im Minimalbetrieb gefahren. Sie wurde später von Scottish Malt Distillers (SMD) übernommen, hatte jedoch stets mit wirtschaftlichen Schwierigkeiten zu kämpfen und produzierte selten am Maximum. Am 31. Mai 1983 schlossen SMD die Brennerei. Nach einem fehlgeschlagenen Versuch die Gebäude abzureißen, wurde das Gelände 1992 verkauft. Die Gebäude wurden teils abgerissen, teils in Ferienwohnungen umgebaut.

Produktion
Die Brennerei bezog das benötigte Wasser aus dem Glen Nevis. Zum Brennen standen jeweils eine Grobbrandblase (Wash Still) und eine Feinbrandblase (Spirit Still) zur Verfügung. Es wurden Malt Whiskys produziert.

Abfüllungen
Von Glenlochy sind keine Originalabfüllungen bekannt. Jedoch existierte eine Reihe von Abfüllungen unabhängiger Abfüller. Unter diesen wurden von Douglas Laing die längstgereiften als 38- und 49-jährige Abfüllungen auf den Markt gebracht.

Weblinks

Einzelnachweise

Ehemalige Whiskybrennerei (Schottland)
Ehemaliges Unternehmen (Highland, Council Area)
Kategorie-B-Bauwerk in Highland (Council Area)
Erbaut im 19. Jahrhundert
Gegründet 1898


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No, The Wuhan Virus Won't Cause A U.S. Population Decli...
"Please, Somebody Help Us!": Eye Of Slow-Mo...
A World of Malice
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Families Turn to Homeschooling as the Education Establishment Fumbles Its Pandemic Response
Posted by Reason | Jul 11, 2020 | Politics & Culture | 0
President Donald Trump got a lot of pushback for his criticism of school reopening guidelines from the Centers for Disease Control and Prevention (CDC)—including from the CDC itself. But even many people who share the CDC's goal of minimizing health risks in the midst of a pandemic agree that the guidelines aren't especially practical. Keeping kids masked and separated in a learning environment intended for groups makes sense only to those who have little experience with schools—or children. That has lots of parents looking at alternatives such as homeschooling that allow them to implement their own guidelines not just for health, but for their kids' education.
"I disagree with @CDCgov on their very tough & expensive guidelines for opening schools. While they want them open, they are asking schools to do very impractical things. I will be meeting with them!!!" the president tweeted on July 8. Not content to just voice his displeasure, he also threatened to cut federal funding for schools that don't fully reopen.
When Trump tweets, his critics automatically respond. California Gov. Gavin Newsom shot back that his state's schools will make their own decisions without regard to the president's desires. Fair enough—local decisions are usually preferable to one-size-fits-none orders from on-high.
But Trump isn't alone in finding the CDC's guidelines unwieldy.
"To prevent the spread of the coronavirus, school leaders must ensure social distancing—limiting group sizes, keeping students six feet apart, restricting non-essential visitors, and closing communal spaces. Those measures run counter to how schools usually operate, with teachers and students working together in close quarters, children socializing throughout the day, and the buildings serving as a community gathering space," Education Week noted in June.
"Schools are not designed for social distancing," Megan Tuttle, president of the National Education Association of New Hampshire, agrees. "Classes and hallways are already overcrowded and many of our schools have inadequate HVAC systems resulting in poor air circulation. These are prime COVID-19 transmission conditions. If we're not ready to make the investments necessary to make our buildings safe, then we're not ready to reopen them."
Leave it to a labor union official to turn a health crisis into an argument for a deeper dip into taxpayers' pockets even as the economy tanks… But Tuttle is right that schools weren't designed for keeping kids isolated from one another. That has educators across the country scrambling to un-crowd classrooms so that social distance can be maintained.
Remote learning via online classes, and hybrid approaches that have kids in school some days and learning remotely on others, are the go-to solutions for now.
"Through a mix of in-school and at-home learning we can make more space in every classroom and building. That means most kids coming to school 2 days a week," New York City's Mayor Bill de Blasio announced on July 8. His plan sets creaky wheels turning for the nation's largest public school district.
On its face, that hybrid plan is a reasonably innovative approach to teaching. Unfortunately, schools—particularly those run by government—are almost as incapable of successful innovation as they are at physically expanding the square footage of their classrooms and cafeterias.
"Some schools, particularly those with ample resources and some experience with remote learning, had a far easier time of it than most," reports the Wall Street Journal of pandemic-prompted efforts at teaching online. But for most schools, "it was a failure" because of inexperience with the approach, limited access to technology, and a lack of commitment on the part of participants.
In addition, many families, especially those with younger children, rely on schools to mind their kids while parents are at work. If you're going to lose the day care function of schools, and not be able to count on them to perform their core educational responsibilities, why wouldn't you look elsewhere? There's not much to lose in emulating Newsom's revolt against orders from on-high in favor of personal decisions about education.
Unsurprisingly, there's an upswing in families planning to homeschool their kids this fall, either through their own efforts or through dedicated online classes and schools that have experience with remote learning. While it's difficult to track numbers when it comes to homeschooling, "several states, including Texas, Utah and Washington, have reported sharp upticks in interest," according to NBC News. North Carolina's website for families announcing plans to homeschool crashed at the beginning of July "due to an overwhelming submission of Notices of Intent."
Parents asked about their reasons for pulling their kids from schools cite both concerns about their kids contracting COVID-19 in the classroom as well as worries that traditional school districts aren't up to the challenges of teaching through remote and hybrid models. They can either place their faith in an education establishment that hasn't earned that sort of trust, or they can experiment with alternatives that have grown increasingly popular in recent years precisely because they satisfy the demand for flexible and effective learning approaches.
"It looks like the high school is only offering a remote learning options," a friend who has three teenage daughters and lives outside Chicago told me. "Could you resend me that list you made of homeschooling resources?"
Why, yes. Here it is!
A lot of homeschooling options are online, given the low cost involved in delivering complete schools, classes, lectures, and the like over the Internet. The internet can also mean easy ways to order books, tools, and materials for families who prefer hands-on learning.
Splitting the difference between family-based education and institutional schooling is a growing movement of home- and community-based microschools that deliver lessons to small groups of kids. That allows parents who need to work to pool their resources while ensuring adult supervision. For a monthly fee (or free in Arizona), Prenda offers its curriculum for use by both microschools and by families for their own children.
All of this experimentation has the establishment worried. Harvard Law's Elizabeth Bartholet infamously calls for "a presumptive ban" on homeschooling because of the supposed danger it represents to children and society.
That prohibitionist impulse comes a little late. Traditional schools right now are fumbling the response to a crisis and convincing much of the public that they are dangerous to children and society. Families fleeing from those schools in search of alternatives are going to prove a tough audience for arguments that kids should be trapped in poorly managed classrooms that aren't up to the latest challenge.
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Home Blog How Is GIScience Different From Geographic Information Systems?
How Is GIScience Different From Geographic Information Systems?
Acronyms can be confusing, especially when two abbreviations relate to the same field. An example is geographic information systems (GIS) and geographic information science (GISc). Although both acronyms are rooted in the science of geography, the roles of GIS and GISc differ.
In this guide, we'll review the functions of geographic information systems and geographic information science, explore similarities and differences and provide examples of use cases for both terms.
What Is GISc?
Geographic information science, also known as GIScience, is a field of science that explores how to use and understand geographic data. It refers to the knowledge and research used as a foundation for geographic information systems. Moreover, GISc provides the conceptual context behind the GIS implementation process, meaning developments in GISc can lead to changes in the tools and methods deployed in GIS.
GISc relies on research and analysis to solve problems relating to multiple topics and industries. GISc professionals use, create and improve geographic information systems. Consequently, people in informational science fields have an in-depth understanding of computational languages and may specialize in various aspects of GIS. The main areas of study include:
Functions of Geographic Information Science
GISc includes technical, scientific aspects while looking at how people interact with machines and the earth. Emerging elements consider implications for decision and policy-making by reviewing the potential political, societal and ethical effects.2 Short and long-term challenges for geographic information science consists of:
GIS and society
Geospatial cyberinfrastructure
Dynamic modeling
Public participation GIS
Spatialization
Geovisualization
GI resource management
Due to the diverse nature of GIScience and its relation to nearly any position reliant upon spatial data, GISc job roles cover many industries. Geographers can work with government agencies to explore solutions for public health or social services, transportation or economic development. In the private sector, a geographer can assist with planning, engineering and training.
Geographic information systems refer to software, hardware and processes for gathering, storing, manipulating, analyzing, managing and visualizing spatial information. Analysts use raster and vector data types during the process.3 Along with geographic data, GIS looks at attribute data, also called tabular data. This information provides details about a location, such as a site name, type, number of people who go there or other qualities that further define a spatial area. In short, GIS describes the "where" and "what" of geographical data.4
Functions of Geographic Information Systems
GIS can be applied widely across industries. For instance, utility providers rely on maps of existing systems alongside regional details about points of interest, population or service areas. When planning upgrades, providers can overlay the "what" and "where" of new infrastructure to see how it alters current equipment placement while identifying affected populations.
Additionally, corporations use GIS in marketing and business decision-making. Maps show existing sites and customers while providing demographic information required to make decisions about outreach efforts. When planning to open new locations, leaders look at GIS data to reduce cannibalization and select areas with the necessary attributes, from public infrastructure to population density.
Therefore, geospatial data gives users a clear view of locations that can be used to see how spaces and attributes change over time. Through analysis, technicians can uncover details used to solve problems and make decisions.3 Geographic information systems, such as mapping tools, allow users to determine:
The features of an area, from geology to demographics
Relationships between various elements in that space
The number of sites with specific attributes
The density of locations or features in an area
Potential effects to populations or buildings within an area of interest
Nearby factors affecting a location, such as streets or speed limits
Consequences of the site or feature changes affecting the earth or people
GISc Versus GIS
Although both terms relate to spatial data, the phrases can't be used interchangeably. GIS focuses on hardware and software tools. In contrast, GISc is the science behind geographic information systems.5 GIS concentrates on the systems used for handling geographic data, whereas GISc explores "how to implement" GIS5 and answers the question "what does everyone need to know."6
Professionals use geographic information science to fix issues stemming from GIS use, assess spatial data and refine GIS processes. Furthermore, industry breakthroughs and tool development come from the practice of GISc. Examples of GISc include:
Figuring out ways to improve the usability of the geographic information systems
Exploring options to define and track errors with GIS hardware and software
Utilizing scientific methods to analyze geographic data, such as quantitative or scale analysis
Developing agent-based or spatial models to visualize GIS data
Use Cases for GIS and GISc
Organizations deploy geographic information systems to manage and visualize data, while GIScience aims to assess, enhance and leverage spatial systems. The combination of fields supports a wide range of use cases, making spatial information science in high demand.7 With the right skill sets, professionals can move into job positions overseeing:
Management of corporate or government assets and resources, such as vehicles, equipment, properties and human capital
Delivery or provider route optimization, used in many sectors including healthcare, hospitality and education
Risk assessments, preparedness efforts and mitigation methods for environmental, emergency and public health concerns
The search for and acquisition of real estate properties meeting specific location or attribute requirements
The visualization of targeted marketing efforts based on spatial data, demographics, points of interest and nearby features
Master GISc Technology
The world faces significant challenges that data and technology may be able to solve. Increasingly, government and private organizations employ geoscientists with a comprehensive understanding of geographic information systems and geographic information science. If you want to enter the field or move up in your current industry, consider how Kent State University's online Master of Geographic Information Science (GISc) program can help you reach your objectives. Set up a call with an Admissions Advisor to learn more about what you can accomplish with this program.
Retrieved on April 29, 2021, from techopedia.com/definition/1932/geographic-information-science-gisci
Retrieved on April 29, 2021, from researchguides.library.wisc.edu/GIS
Retrieved on April 29, 2021, from gisgeography.com/giscience-geographic-information-science/
Retrieved on April 29, 2021, from onlinedegrees.kent.edu/geography/geographic-information-science/community/what-is-geographic-information-science-gisc
Retrieved on April 29, 2021, from tandfonline.com/doi/pdf/10.1080/19475680903250715
Retrieved on April 29, 2021, from mapasyst.extension.org/what-are-some-uses-for-gis/
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GISc Master's
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Kent State GISc Professor Chosen for AGU Diversity, Equity and Inclusion Academy
Scott Sheridan, Ph.D., professor and chair of the Department of Geography and professor in the online Geographic Information Science (GISc) programs was recently appointed to the inaugural cohort of the American Geophysical Union (AGU) Leadership Academy and Network for Diversity and Inclusion in the Geosciences (LANDInG).
Geography Faculty Member Receives NASA New Investigator Award
He Yin, Ph.D., assistant professor in Kent State University's Department of Geography in the College of Arts and Sciences, recently received NASA's New (Early Career) Investigator Award in Earth Science. The award will provide funding for Yin's research on the effects of the Syrian civil war on croplands throughout the eastern Mediterranean region.
Select input field Program of Interest GISc Master's Environmental Certificate General Certificate


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VIP Handling
Ambulance Handling
Private Handling
Egypt Base
UAE Base
Plane makes emergency landing after wife discovers husband's affair mid-flight
Nov 24, 2017 | News | 0 comments
A plane passenger who spied on her husband's phone and discovered he was having an affair mid-flight. Caucusing such a commotion the flight had to make an emergency landing.
The Iranian woman, who was with her husband and their young child on a Qatar Airways flight from Doha to Bali on Sunday. Unlocked her sleeping hubby's phone by putting his finger on the home button. And found evidence he was cheating on her, the Times of India reported.
The woman, who had reportedly been drinking alcohol. Then started a fight with her husband and "misbehaved" when flight crew tried to calm her down, according to the paper.
The situation then got "out of hand" and the pilot made the decision to divert to Chennai, India. The family of three were offloaded at Chennai airport and the plane continued its journey to Bali.
As there was no security issue, the family were soon able to fly to Kuala Lumpur, where they boarded a flight back to Doha.
In a statement, an official from India's Central Industrial Security Force official confirmed the incident.
"A lady along with her husband and a child, all Iranian nationals. Were offloaded by Qatar Airline as the lady passenger (who was intoxicated) misbehaved with crew members in-flight," the official said.
"They were sent to Kuala Lumpur by Batik Air flight 6019 for further travel to Doha."
Qatar Airways told the Times of India: "In respect of passenger privacy we do not comment on individual cases."
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