The 2010 National Defense Authorization Act authorized DOD to establish LTCs at accredited universities to increase the training capacity in strategic languages and regional studies. KU was awarded a $715K Institute of International Education grant that establishes a DOD Language Training Center (LTC) at the university. KU's LTC will provide language and culture programs designed to meet the stated operational needs of the Special Operations Forces element within the Command and General Staff College at Fort Leavenworth, KS, and the Marine Corps Detachment at Fort Leonard Wood, MO. The KU departments/centers participating in the program include AAAS (Arabic), EALC (Chinese, Japanese and Korean), French and Italian (French), Slavic Languages and Literature (Russian), Spanish and Portuguese (Spanish), Germanic Languages and Literature (German), and the Ermal Garinger Academic Resources Center. For information about KU's Language Training Center program, click here.


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Trippin' is a 1999 American comedy film directed by David Raynr and starring Deon Richmond, Maia Campbell, Donald Faison, and Guy Torry. The film provided one of Anthony Anderson's earliest film roles.

Plot
Greg (Deon Richmond) is nearing the end of his high school days as graduation slowly approaches.  He is also anxiously awaiting prom and has the hopes of going with Cinny (Maia Campbell), the school's local beauty. As he tries to ask his parents for help paying for prom, they begin nagging him after finding out he hasn't filled out one college application, telling him they won't give a dime until he fills one out. Along with these wants, Greg is also an avid daydreamer and  is always daydreaming ("trippin'") over everything.

Production notes
''Trippin was filmed on location in California in the cities of Los Angeles and Long Beach in 1998.  Narbonne High School in Harbor City was used for most of the film's school shots.  Harbor City in Los Angeles was also a location used for filming as some of the film's scenes take place on the . The working title of the film while it was in production was G's Trippin, but this was later shortened to its before release.

Reception
Trippin''' was poorly received by critics.

The film made $2,527,909 its opening weekend and grossed a total of $9,017,070 during its theatrical run.

ReleaseTrippin was released during the start of the summer movie season of 1999.  It was released in a limited number of theaters compared to the summer blockbusters released around the same time.  The film did well enough to crack the top ten in gross receipts during its first few weeks of release.

References

External links

1999 films
1990s teen comedy films
African-American comedy films
American coming-of-age films
Films shot in Los Angeles
American independent films
American teen comedy films
Films produced by Marc Abraham
Films scored by Michel Colombier
Beacon Pictures films
1999 comedy films
1999 directorial debut films
Films directed by David Raynr
1990s English-language films
1990s American films

redpajama_set_name: RedPajamaWikipedia


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Competitive sport Sport Sudan United States
Sudanese basketball star Manute Bol dies
The Sudanese basketball player Manute Bol has died at the age of 47 on Saturday at the University of Virginia Medical Center. He had been hospitalised late in May after returning from Sudan, suffering from a rare skin disorder and severe kidney trouble.
Manute Bol was a Dinka tribesman from Turalei village in South Sudan. He took up basketball in his teens and after he was spotted in Sudan by a US coach, he flew to the United States in 1982 with no English and little formal education.
Three years later he joined the NBA where, with his height of 7' 6", or 2m 28 cm, he would be the tallest NBA player ever for most of his career.
Although he could reach the basketball hoop without jumping, he spent most of his time in defense, blocking shots from the opposition. In his first season in the NBA he set a rookie record, blocking an average of five shots per game.
He began his career with the Washington Bullets and went on to play for the Golden State Warriors, the Philadelphia 76ers and the Miami Heat, for a total of ten seasons.
Bol traveled to Sudan almost every year while he was playing in the NBA, and followed the progress of South Sudan closely, donating much of his earnings to political causes. He had said he dreamed of returning to Turalei to live and was there late last year to check on construction of a school being built in the village.
He is survived by his wife and ten children.

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We've rounded up the best sports centres in Crookes in our quest to discover brilliant family attractions and places to visit near you. There are 10 Crookes sports centres to pick from. Alternatively, why not explore some other sports and activities days out nearby, including cinemas and theatres, trampoline parks or indoor and soft play areas. Find the perfect places to go with your kids and get out on your next adventure!
If you've visited one of these sports centres in Crookes , please consider leaving a review on the attraction page to help others plan their next fun day out.


This paper looks at the impact of various MLTSS policies on access to LTSS. It looks specifically at four states and the policies which these states identify as important to ensuring access. All four states identified network adequacy standards, transition of care, provider reimbursement, and level of care criteria as important factors. In addition, the paper examined participant-directed services policies and care coordination models.


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A YES VOTE would require health insurance carriers to guarantee certain rights to their patients and governing health insurance and health care. providers, and it would prohibit the conversion of non-profit hospitals, HMOs, and health insurers into for profit entities until a system is created to provide
comprehensive health care coverage for all Massachusetts residents.
A NO VOTE would make no change in the laws governing health insurance and health care.
This proposed law would set up a state Health Care Council to review and recommend legislation for a health care system that ensures comprehensive, high quality health care coverage for all Massachusetts residents. Until the Council decided that such a system had been set up, the proposed law would prohibit the conversion of non-profit hospitals, health maintenance organizations (HMOs), and health insurance firms to for-profit status. The proposed law would also require health insurance carriers to provide certain rights to patients and health care professionals, starting January 1, 2001.
The Council would recommend laws to set up, and would decide whether laws had been passed to ensure, a health care system that provides:
·barrier-free access to health care services;
·patients' freedom to choose their health care providers, get second opinions, and appeal denials of care;
·health care professionals' freedom to act solely in the best interests of their patients;
·affordable coverage, with cost increases no greater than national averages;
·preserving and increasing the quality of care and encouraging research;
·at least 90% of all premiums to be used for patient care, public health, and training/research, and no more than 10% for administrative costs, with simpler paperwork and administration;
·a prohibition of financial incentives that limit patient access to health care, and limits on incentives for inappropriate care.
The Council would include 17 members representing health care and other organizations. It would hold public hearings, study proposals, and make recommendations to the state Commissioner of Public Health and the Legislature on laws and other steps needed to set up a system meeting the above requirements. The proposed law would also create a special legislative committee, including legislators and members of the Council, to make recommendations by September 30,2001, for laws to set up a system meeting the above requirements by July 1, 2002.
Starting January 1, 2001, the proposed law would require health insurance carriers to guarantee certain rights to their insured patients and to health care professionals. These rights would include;
·patients' right to choose all of their health care providers, subject to the approval of a freely chosen primary care provider who has no financial incentive to deny care, and subject to payment of a reasonable extra fee to see a provider outside the carrier's network;
·health care professionals' right to make medical decisions in consultation with the patients;
·patients' right to transitional insurance coverage when they are under going a course of treatment from a health care provider whose contract with a carrier is being terminated;
·patients' right to medically necessary referrals to specialists;
·limits on and disclosure of contracts between carriers and health care providers that create financial incentives to delay or limit care or provide inappropriate care;
·health care professionals' right to discuss health benefit plans with insured patients and to advocate on behalf of their patients;
·carriers could not terminate health care providers' contracts without cause;
·patients' right to receive emergency services, subject to authorization procedures, and to be reimbursed when they pay cash for emergency services from providers not affiliated with their carrier;
·utilization review procedures that meet specific standards, including patients' right to appeal to the Commissioner of Public Health;
·in any year at least 90% of a carrier's Massachusetts revenue must be spent on Massachusetts health care, and a carrier that spent more than 10% for non-health care purposes would have to refund the excess to its insured patients. Each carrier would have to report its revenues, premiums, and expenditures to the state Commissioner of Insurance every year.
The proposed law states that it would not interfere with any existing contract, including contract terms (such as automatic renewal or option clauses) that may go into effect after January 1, 2001. The proposed law states that if any of its parts were declared invalid, the rest of the law would stay in effect.
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Working in a construction site is one of the most dangerous fields in which to work. Therefore contractors, sub-contractors, owners and employers have a responsibility to maintain a certain level of safety at a construction site. Those in the field of construction typically handle a wide array of dangerous materials and situations on a day-to-day basis, so maintaining safety on a site is the shared responsibility of several parties. Unfortunately, many construction-related injuries are catastrophic in nature, drastically impacting every aspect of the victim's life and having a long-term negative effect on their physical capabilities.
We are familiar with regulations and proper safety practices that should be taken on construction sites for all the workers and people using the site. If you or your loved one has been injured, then please call us to review your case for any evidence of negligence (failure of people to take due care and follow accepted customary safety procedures.
One option may be to file a worker's compensation claim. Another option that must be evaluated is whether your case involves third party liability, by such persons as a utilities company, subcontractor, equipment manufacturer or others. We are is ready to help first to evaluate the facts and the issues of culpability, and then to represent you if the case is properly founded in fact and the law.


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Military Librarianship
Home Military Librarianship
Uncle Sam wants you! Or at the very least, those excellent LIS skills you possess. In fact, military librarianship can offer opportunities for working abroad, a broad range of choices as to the type of work you might do, and a way to support American troops (and their families) both in the United States and in other countries.
What kind of opportunities exist, and where are they? The U.S. military comprises the Army, the Navy, the Marine Corps, and the Air Force, all under the auspices of the Department of Defense. Within these divisions, the diversity of military libraries reflects the same range of specialization as is found in non-military libraries: that is, public, school, academic, and special.
Public libraries – Sort of
The military's version of public libraries are the 250 base libraries that support the reading, information, reference, and entertainment needs of the military families stationed on base (as well as the non-military personnel), and may offer story hours for youngsters as well as popular paperbacks, CDs, and DVDs, as well as access to electronic databases. In addition, as noted by Ron Chepesiuk in his "Mission: Access" article for the February 2006 issue of American Libraries, the Navy is charged with maintaining a general library for "every one of its 260 ships."
School Libraries on Base
School libraries are found among the K-12 schools located on military bases where families may be present, especially those stationed abroad – the organization that runs the school libraries is www.dodea.edu.
Military Academic
And academic libraries can be found at all of the military training institutes and academies such as the Air Force, Navy & Coast Guard Academies, West Point, the Naval War College, the U.S. Army War College, Naval Postgraduate School, the Army Management Staff College, the Joint Forces Staff College, and the Air University.
Military Academic and Special Libraries
As in the non-military world, special libraries in the military support their organizations' strategic missions, which may be medical and scientific research, historical archives, technology development, or management and leadership training, among others. Examples of these types of libraries are those of, for example, the Military History Institute, the Naval Operational Medicine Institute Library, the Pentagon Library, and the Naval Oceanographic Office. Others include the Army Corps of Engineers' Cold Regions Research and Engineering Laboratory Library, the Signal Corps' Woodworth Library, and the Air Force Research Laboratory Research Library (focusing on such scientific disciplines as geophysics, astronomy, astrophysics, physics, and chemistry, among others).
Outsourced Library Services
Some military bases outsource the management of their libraries to contract firms that employ librarians on behalf of the base management, so that a job as a military librarian might entail working as a subcontractor for the contracting agency, rather than for the federal government. (For an example of one company that provides contract librarians for the military, see Information International Associates, Inc., at www.infointl.com.) Also, many military base libraries are subject to the same closure decisions mandated under the 2005 Base Realignment and Closure Commission (BRAC) recommendations approved by Congress, so it is unclear what may happen over the coming years to those base library collections, and their librarians.
Despite this, many military librarians laud the stable job environment, decent pay, and excellent benefits of this career choice. In addition, for those who are interested in LIS opportunities outside the United States, military librarianship can offer a viable and rewarding path to international library work.
Army Library Program (ALP)
http://mylibraryus.armybiznet.com/
Check out the ALP portal to see how the Army's librarians are delivering services and furthering their mission electronically. The ALP describes itself as "a strategic knowledge management resource that enables the Army to gain and maintain full-spectrum knowledge superiority while concurrently facilitating education, research, training, self-development, well-being, outreach, and lifelong learning for Army soldiers, civilians, and families." From the menu, select "Army Libraries Directory" to see the many different types of Army libraries in existence, or explore the many resources listed under "For Army Library Staffs."
Those interested in military libraries in general should sign up for the "Army Library Listserv."
Navy MWR Library Program (NGLP)
https://www.navymwr.org/programs/libraries – For basic information on the program in three areas: Ashore Libraries, Afloat Libraries & our Digital Library.
https://www.navymwrdigitallibrary.org/ to access the digital library – validated access by Common Access Cards or DS Logon. Over 50+ digital services.
USMC MCCS Libraries
https://usmc-mccs.org/services/education/library/# – For general information on the base libraries and their digital library.
Air Force Library & Information System
http://www.myairforcelife.com/libraries/ – For general information on base libraries, their digital library and all other AF libraries.
Federal and Armed Forces Libraries Round Table (FAFLRT) – ALA Roundtable
http://www.ala.org/ala/mgrps/rts/faflrt/index.cfm
Some 450 federal and military LIS professionals belong to FAFLRT. According to its mission statement, the roundtable's goals are to 1) to promote library and information service and the library and information profession in the federal and armed forces communities; 2) promote appropriate utilization of federal and armed forces library and information resources and facilities; and 3) provide an environment for the stimulation of research and development relating to the planning, development, and operation of federal and armed forces libraries. FAFLRT hosts an electronic discussion list and publishes the quarterly Federal Librarian, whose current and past issues are available to the public at the roundtable's website.
Military Librarians Division, Special Library Association
http://military.sla.org/about-us/
This SLA division provides "a forum for the exchange of ideas, opportunities for networking and career enhancement, and programs to develop specific and unique military interests." Members include librarians and other LIS professionals from all U.S. military services, the Canadian Combined Armed Forces, international military services, Department of Defense agencies, contractors, vendors, academic institutions and anyone with an interest in military librarianship. Check out current and past issues of the division's quarterly newsletter The Military Librarian, archived on the website, for a good overview of issues relevant to military librarianship.
"Mission: Access," Ron Chepesiuk, American Libraries, v. 37, no. 2, February 2006, p. 24-29.
An overview of the broad range of roles and responsibilities currently being undertaken by American military libraries.
https://www.armymwr.com/programs-and-services/libraries/
From the U.S. Army MWR (Morale, Welfare, and Recreation) site (the division under which the Army libraries fall), this is the starting point for information about how the Army libraries present themselves to their military constituencies.
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Равшан, Рапшан, Ровшан ( — «Светлый») — имя персидского происхождения, однокоренное с именами Равшанак (Роксана) и Роушанаван (Светлая душа), а также однокоренное с такими словами как «роушангар» (просветитель) и «роушанфэкри» (интеллигентность). Женская форма имени Равшана является именем-аналогом русского имени Светлана. В арабском языке слово «равшан» является именем нарицательным и обозначает балкон или окно.

Фамилия
 Ровшан, Рамиз — азербайджанский писатель.
 Ровшан, Хассан (род. 1955) — иранский футбольный тренер, менеджер и бывший игрок.

Другие значения
 Равшан — футбольный клуб из города Куляб (Таджикистан)
 Равшан — футбольный клуб из Зафарабадского района (Таджикистан)

См. также
 Рошан, Ритик — индийский киноактёр.
 Равшанабад
 Истаравшан

Литература

 Персидско-русский словарь. ред. Ю. А. Рубинчик

Персидские имена


Use the premium school bus service near Sacramento when you have a group of children, pupils or teens in need of a ride to Game Day manifestations, school band excursions, camp activities, competitions, sporting events and other activities. Limo MGM extraordinary fleet is filled with lots of different vehicles, everything from luxury limos to party buses and wedding coach buses. When you combine our top of the line four-wheelers with the most affordable rates, you will know you made the right choice!
When it comes to our chauffeurs, every hand-picked candidate must complete an extensive training after they pass the background check. So have no doubt, when you book with us, you choose the truest of professionals to drive you places. For the sake of optimal school charter bus service near me, MGM Limo vehicles are always in a spotless condition; they are well-maintained and pass all inspections. All of our buses are approved by a California Highway Patrol and conform to the rules and regulations related to children transportation.Keep in mind that our school coach buses and expert drivers are School Pupil Activity Bus (SPAB) certified.
Limo MGM offers all kinds of transport – from point to point school coach bus rides nearby, and all-day excursions to airport transfers. Rent a certified School Pupil Activity Bus to get the kiddos where they need to go, both internationally and locally (for example from Folsom to Roseville, from Citrus Heights to Midtown, or North Highlands to Davis). Schedule your school coach bus today and ensure a safe, economical and reliable journey to Reno, Las Vegas, San Francisco or Canada.
You can count on us to deliver the perfect limo or bus ride anywhere in Sacramento. If you need a ride to a business meeting, restaurant or from door to door, Limo MGM is here for you. Feel free to contact us with our booking app, through a website or simply by calling at 916-804-LIMO (5466). A budget-friendly and the nearest bus ride to anywhere you desire is a guarantee! Wherever you need to go, whether it is a short or a long trip, you can count on us.


I see openings as we drive through the end of February, on our way to nowhere in particular, just a ride along snowy country roads, because I've been cooped up too long. It is the tiny spaces, the crevices between boards, and panes of glass broken free that seem to call out to me. "Look," these tired structures say, "can you find beauty here?" And I can, I do. The transition from one state of being to another is what I find most alluring these days, a slow fade into beautiful.
Spending time with your daughters is much more important, so have a wonderful visit with them.
and enjoy the week with your babies.
Beauty is in that moment when everything perfect sheds it's facade and the real inner structure breaks through.
It is in the erosion that the substance shines.
For those who can see it.
tears over this one... and also joy that you found this loveliness in the fading.
There is something so alluring about weather-beaten old red barn boards. :) Enjoy your time with your daughters!
Have a great time in your daughters' company - these are such precious moments!
it's slow to arrive in the Midwest too! Have a great time with your girls.
I love pictures of old structures -- old wood, rust -- as if they've lived a good and full life.
Have a wonderful time this week with your girls.
Have a wonderful week with your girls!
The shift of seasons is beginning to reveal itself for us all. May the clear light of spring bring you peace and joy and may your heart take flight into warm blue skies.
I too seem to find the beauty in the up close weathered wood, the cracks and broken parts, the worn and gray and rusty textured surfaces- beautiful images here.
Lovely images Laura. I often get Hubbers to take me for a drive. It has been a long winter. Enjoy the company of your girls! I am having my granddaughter for the week of March break. I can't wait!
"The transition from one state of being to another is what I find most alluring these days, a slow fade into beautiful." Perfect. To embrace transformation in the unique ways she presents herself. Blessings!
"Fading into beautiful....." What a beautiful thought. I love the photos, love the words........have a great week with your girls.
the barn is a beauty! New England has had quite a winter, that is like the old ones. Enjoy your vacation with the girls.
I hope you spend some quality time with your daughters. I really enjoyed this post, and the colour combinations are wonderful.
Absolutely stunning shots, Laura. And beautiful words.
Beautiful for sure! I love old places like this!
i hope you find peace and rest in the love all around you this week. it is everything.
Have a great time with your daughters. We'll catch up with you later.
Such lovely images, dear one.
Have a wonderful break with your beautiful girls. There is nothing like spending unhurried time with our girls, is there? It makes me smile to know that you are getting to do so. Have a great week! We will be here when you return:) I wish I could pop over with my girls and just hang out with the three of you. We could have a tea party!
Have fun this week. As for winter...there is no end in sight.
What a beautiful photo! I wish old places like this could be frozen in time. There is no replacing them!
I love old structures and poetry. You combined both quite well.
beautiful words Laura, simple few and yet really beautifull and the pictures are so helpful to see where you stand!
enjoy the time off...and have a bit of fun...loved the words and the pics...i grew up near a few barns like this and we used to play in them...thanks for taking me back there..
Those are beautiful images! Really gorgeous. Enjoy your time with your girls. See you when you get back, just in time for Spring, hopefully!
Love this and the beautiful pic. Have fun.
how nice...and it's great to see the words "fade to" not followed by "black"...and yes, the images are a view out.
Have a wonferful week with your girls!
Enjoy your time with your girls!
hi laura! i have so much catching up to do here! i've been busy and find myself missing your blog! i will be popping in to read in the next few days.
wishing you sunshine and more trees!
these are wonderful. I love the muted tones. Such depth of feeling.
Wonderful photos, Laura. Your haiku is a perfect accompaniment. But your description of driving to nowhere in search of something is the real poetry for me. The openings to the beauty in those old structures led you to magic.
I agree, old, worn buildings like that are beautiful!
The title in and of itself is enough to sit and ponder for a while. The barn is lovely.


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text:
+6 07-553 3333 corporate@utm.my
Message from the Vice Chancellor
VC in the Media
Photos of VC at UTM Events
Previous Vice-Chancellor
1st Vice Chancellor of UTM (1975-1989)
Tan Sri Dato' Ainuddin Abdul Wahid
B.Sc. Eng University of Bristol, UK (1956)
Special course in Road and Traffic Engineering Ohio State Univ, USA (1962)
Assistant Engineer
Fellowship- International Road federation, Washington, USA
Engineer for Federal Road Development Project, Klang (1692-1963)
Senior Work Engineer, Klang (1965-66)
Senior Work Engineer, JKR HQ K.Lumpur (1966-1969)
Principal, Maktab Teknikal Kuala Lumpur (1969-1972)
Rector, National Technical College (1972-1975)
Vice-chancellor, Universiti Teknologi Malaysia (1975-1989)
2nd Vice Chancellor of UTM (1990-1994)
Datuk Prof. Dr. Muhammad Ridzuan Haji Salleh
B. Eng (Electric) University of Western Australia (1966)
M.Sc. (Electric Power) University of London (1972)
Ph.D (Electric) University of London (1974)
Engineer, Electrical Commision of NWS, Australia (1967-1968)
Engineer, National Electricity Board, Malaysia (1968)
Lecturer, Technical College Kuala Lumpur (1968-1971)
Research Officer, Electrical Power Engineering, Univ of London (1974-1977)
Associate Professor/Dean of Fac of Electrical Engineering, UTM (1974-1977)
Partner, Ranhill Bersekutu Sdn. Bhd., (1977-1981)
Executive Chairman, Ranhill Bersekutu Sdn. Bhd., (1981-1990)
3rd Vice Chancellor of UTM (1994-2001)
Tan Sri Datuk Dr. Ahmad Zaharudin Idrus
B.Sc. Agriculture University Malaya (1969)
M.Sc University of Aberdeen(1971)
Ph.D. University of Aberdeen (1974)
Agriculture Officer (1969)
Scientist/Biochemist (1970-1974)
Director, Food Research Division, MARDI (1975-1981)
Secretary, National Council for Scientific R&D (1981-1986)
Controller & Deputy Chairman, SIRIM (1986-1989)
Director, Petroleum Research Institute, PETRONAS (1989-1994)
4th Vice Chancellor of UTM (2001-2008)
Tan Sri Prof. Ir. Dr. Mohd. Zulkifli Tan Sri Mohd Ghazali
B.Sc. Hons (Civil Engineering) Leeds University (1976)
M.Sc. (Structure Engineering) Strathclyde University (1981)
Ph.D. (Civil Engineering) Sussex University (1974)
Certificate in International Management, INSEAD France (1995)
Civil Engineer, Special Services Section, Public Works Department, K.Lumpur
Engineer in Charge, PWD K.L. International Airport, Dept of Civil Aviation
Assistant Lecturer (1978) and Lecturer (1980), Faculty of Civil Engineering
Director of Works, UTM (1990)
Dean, Faculty of Civil Engineering, UTM (1992-1997)
Deputy Vice Chancellor (Student Affairs), UTM (1997-2001)
UTM Vice-chancellor (2001-2008)
5th Vice Chancellor of UTM (2008 – Jun 2013)
Prof. Dato' Seri Ir. Dr. Zaini Ujang
Bachelor of Chemical Engineering (Hons) Universiti Teknologi Malaysia (1983-88)
M.Sc. (Environmental Engineering) Newcastle University (1990-91)
Ph.D. (Environmental Engineering) Newcastle University (1994-96)
Master of Management (Human Resource Management) Universiti Teknologi Malaysia (1997-8)
Advanced Management Program (AMP) Harvard Business School, Harvard University (2009)
Director of Institute of Environmental & Water Resource Management (IPASA) (2001-2006)
Chairman, UTM Environmental Technology Focus Group (2002-2006)
Chairman of IWA Conference on Environmental Biotechnology (December 2003)
Dean, Faculty of Chemical and Natural Resources (2006- 2007)
Head of ICT Committee of Malaysian Higher Education Institutions (since 2007)
Chairman of IWA Conference and Exhibition (Water & Waste water Management for Developing Country) (October 2001 and 2007)
Deputy of Vice Chancellor (Research & Innovation) (2007-2008)
6th Vice-Chancellor of UTM (Sept 2013 – Aug 2020)
Prof. Datuk Ir. Dr. Wahid bin Omar
Diploma in Civil Eng. UTM (1983),
B.Eng. (Hons) in Civil Eng.-University of Strathclyde, Scotland, United Kingdom (1986),
M.Sc in Bridge Engineering-University of Surrey, United Kingdom (1989),
Ph.D in Civil Engineering, University of Birmingham, United Kingdom (1998).
Fellow of the Institution of Engineers, Malaysia, (MIEM, 19629). Professional Engineer, registered with the Board of Engineers, Malaysia, (10420)
Member, The Concrete Society of Malaysia, PERKOM, (MCSM M0129)
Member, American Concrete Institute, KL Chapter (Membership No. 100)
Member, International Committee on Concrete Model Code for Asia (ICCMC)
Member Asian Concrete Federation (ACF).
Honorary Member of the ASEAN Federation of Engineering Organization (AFEO),
Certified ASEAN Chartered Professional Engineer (ACPE).
Director of Works, Office of Asset and Development, UTM (15 Oct 2008 – 30 Sept 2011),
Deputy Vice-Chancellor (Development) (1 Oct 2011 – 31 Ogos 2013)
Copyright ©2022 Universiti Teknologi Malaysia


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\section{Introduction}

Production networks have grown rapidly in size and complexity, in line with
advances in communications, supply chain management and transportation
technology (see, e.g.,~\cite{coe2015global}). These large and complex
networks are sensitive to uncertainty, trade disputes, transaction
costs and other frictions.  Firms routinely shift production and task
allocation across networks, in order to mitigate risk or exploit new
opportunities (see, e.g.,~\cite{bmk}). There is an ongoing need to predict how
equilibria in production networks adapt and respond to shocks, in order to
understand their impact on domestic employment, industry concentration,
productivity and tax revenue.

Dynamic programming provides one methodology for analyzing such equilibria.
While dynamic programming is typically used to study
\emph{dynamic} models (see, e.g., \cite{stokeyec}), it
can also be applied to static models by reinterpreting the time
parameter as an index over firms or other decision making entities, as seen
in, for example, \cite{garicano2006organization}, \cite{hsu2014optimal},
\cite{tyazhelnikov2019production}, and \cite{antras2020geography}.  Our paper
builds on this literature by providing a systematic way to apply the theory of
dynamic programming to both production chains and production networks, as well
as to a range of other static allocation problems involving firm management
and economic geography.

This research agenda faces a technical hurdle: the dynamic programs
most naturally mapped to the competitive allocation problems we wish to
consider usually fail to be contractive.  Contractivity fails because
frictions such as the transaction costs or failure probabilities in the
production chain models translate into \emph{negative} discount rates in the
corresponding dynamic program.  In this paper, we circumvent the need for
contractivity by drawing on dynamic programming methods originally developed to
solve recursive preference problems.\footnote{See, for example,
    \cite{epstein1989substitution}, \cite{bloise2018convex} or
    \cite{marinacci2019unique}.  In this sense, our work can be viewed as
    building connections between (a) the existing literature on dynamic
    programming for obtaining static competitive equilibria and (b) the modern
theory of dynamic programming with recursive preferences.}

The contributions of this paper fall into two parts.  The
first is providing a theory of dynamic programming in a
loss-minimization setting where discount rates are negative. The
second is applying this theory to a series of competitive equilibrium problems
involving production chains, production networks and other related models.
Through the application of this theory, we show how the dynamic programming
tools can be used to obtain not only existence and uniqueness of equilibria,
but also computational algorithms, results on comparative statics and insights into the
underlying mechanisms.

Regarding application, we build on an analytical framework for analyzing
allocation of tasks across firms first developed by \cite{coase1937nature}.
Subsequently, \cite{kikuchi2018span}, \cite{fally2018coasian} and
\cite{yu2019equilibrium} developed Coasian models in which firms trade off
coordination costs within the firm against transaction costs outside the firm.
We show that competitive equilibria in these models can be recovered as solutions
to dynamic programs and use the associated envelope condition to provide
insight on some of the foundational conjectures of \cite{coase1937nature}.

In the remainder of the paper, we then apply similar methods to study a
range of additional applications, including settings where Coasian
transaction costs are replaced by failures in production or costly
transportation, as found, for example, in \cite{levine2012production} and
\cite{costinot2013elementary}; models of knowledge organization and optimal
management structures originally due to \cite{garicano2000hierarchies}; the
analysis of central place theory in \cite{hsu2014optimal}; and the
configuration of general (nonsequential) production networks in the spirit
of \cite{baldwin2013spiders}, \cite{kikuchi2018span},
\cite{yu2019equilibrium} and \cite{tyazhelnikov2019production}.

The applications discussed above differ in many ways. There are different
trade-offs that characterize each model, each of which leads to a particular
endogenous structure.  The negative discount dynamic programming theory developed here provides
a unifying methodology and brings tools to bear on understanding the structure
of the networks where firms, cities and managers coordinate production.

Regarding our technical contribution, the closest existing work in the
economic literature is \cite{bloise2018convex}, who treat noncontractive
dynamic programming problems that arise from recursive utility.  In addition
to results on existence and uniqueness of fixed points of the Bellman
operator, which parallel analogous results in \cite{bloise2018convex}, we
apply a fixed point result of \cite{du1989fixed} to provide new results on
monotonicity, convexity and differentiability of solutions, as well as a full
set of optimality results linking Bellman's equation to existence and
characterization of optimal solutions.\footnote{This optimality theory is
    related to other studies of dynamic programming where the Bellman operator
    fails to be a contraction, such as \cite{martins2010existence} and
    \cite{rincon2003existence}.  Our methods differ because even the
    relatively weak local contraction conditions imposed in that line of
    research fail in our settings.  The fixed point results in this paper are
    related to those found in \cite{kamihigashi2015application}, but here we
    also prove uniqueness of the fixed point, as well as connections to
optimality and shape and differentiability properties.}

The remainder of this paper is structured as follows. In
Section~\ref{s:model}, we study a dynamic optimization problem under
negative discounting and discuss its solution. In
Section~\ref{s:app:production}, we connect this discussion to Coase's theory
of the firm and elaborate on the relationship between our model and other
related models. In Section~\ref{s:app:knowledge} we show that our model can
also be used to understand organization of knowledge within a firm. In
Section~\ref{s:app:networks} we extend our model to expand the scope of
applications to more complex networks. Section~\ref{s:c} concludes. Most
proofs are deferred to the appendix.

\section{Negative Discount Dynamic Programming}\label{s:model}

In this section, we study a dynamic optimization problem in which an agent
minimizes a flow of losses under negative discounting.
  While our main aim is to develop
techniques for calculating equilibria in production networks, the
topic of negative discount loss minimization does have some independent value.\footnote{
For example, \cite{thaler1981some},
\cite{loewenstein1991negative} and \cite{loewenstein1991workers} document
separate instances of such phenomena.
    \cite{loewenstein1991workers} found that the majority of surveyed workers
    reported a preference for increasing wage profiles over decreasing ones,
    even when it was pointed out that the latter could be used to construct a
    dominating consumption sequence.  \cite{loewenstein1991negative} obtained
    similar results, stating that ``sequences of outcomes that
decline in value are greatly disliked, indicating a negative rate of time
preference'' \cite[p.~351]{loewenstein1991negative}.}

Consider an agent who takes action $a_t$ in
period $t$ with loss $\ell(a_t)$. We interpret $a_t$ as effort
and $\ell(a_t)$ as disutility. Her optimization problem is, for
some $\hat x > 0$,
\begin{equation}\label{eq:dpm}
    \min_{\{a_t\}} \;  \sum_{t=0}^{\infty} \beta^t \ell(a_t)
    \;\; \text{ s.t. } a_t \geq 0 \text{ for all } t \geq 0
    \text{ and } \sum_{t=0}^{\infty} a_t = \hat x.
\end{equation}
Throughout this section, we suppose that
\begin{equation}\label{eq:ndas}
    \beta > 1, \;
    \ell(0) = 0, \;
    \ell' > 0 \;
    \text{ and }
    \ell'' > 0.
\end{equation}
The convexity in $\ell$
encourages the agent to defer some effort. Negative discounting ($\beta > 1$)
has the opposite effect. We call problem~\eqref{eq:dpm} under the
assumptions in~\eqref{eq:ndas} a \emph{negative discount dynamic
    program}.\footnote{The assumption $\ell(0) = 0$ cannot be weakened, since
    $\ell(0) > 0$ implies that the objective function is infinite.
    Conversely, with the assumption $\ell(0)=0$, minimal loss is always
    finite.  Indeed, by choosing the feasible action path $a_0 = \hat x$ and
    $a_t = 0$ for all $t \geq 1$, we get $\sum_{t=0}^{\infty} \beta^t
    \ell(a_t) \leq \ell(\hat x)$.  Also, given our other assumptions, there is
    no need to consider the case $\beta \leq 1$ because no solution exists.
    Because we are minimizing disutility, when $\beta < 1$ any proposed solution
    $\{a_t\}$ can be strictly improved by shifting it one step into the future
    (set $a_0' = 0$ and $a_{t+1}' = a_t$ for all $t \geq 0$).  Furthermore, if
    $\beta = 1$, and a solution $\{a_t\}$ exists, then the increments
    $\{a_t\}$ must converge to zero, and hence there exists a pair $a_T$ and
    $a_{T+1}$ with $a_T > a_{T+1}$.  Since $\ell$ is strictly convex, the
objective $\sum_t \ell(a_t)$ can be reduced by redistributing a small amount
$\epsilon$ from $a_T$ to $a_{T+1}$.  This contradicts optimality.}

\subsection{A Recursive View}

We can express the problem recursively by introducing a state process
$\{x_t\}$ that starts at $\hat x$ and tracks the amount of tasks remaining.
Set $x_{t+1} = x_t - a_t$ and $x_0 = \hat x$. The Bellman equation for this
problem is
\begin{equation}
    \label{eq:epe}
    w(x) = \inf_{0 \leq a \leq x} \, \{ \ell(a) + \beta w(x-a) \}.
\end{equation}
The Bellman operator is
\begin{equation}
    \label{eq:bellop}
    (Tw)(x) = \inf_{0 \leq a \leq x} \, \{ \ell(a) + \beta w(x-a) \}.
\end{equation}
The Bellman operator is not a supremum norm
contraction because $\beta > 1$.\footnote{For example, let $w
  \equiv 1$ and $g \equiv 0$. Then $Tw \equiv \beta > 1$ while $Tg \equiv
  0$. One consequence is that, if we take an arbitrary continuous bounded
  function and iterate with $T$, the sequence typically diverges. For
  example, if $w \equiv 1$, then, $T^n w \equiv \beta^n$, which diverges to
  $+ \infty$.} Nevertheless, we can show that $T$ is well
behaved, with a unique fixed point, after we restrict its domain to a suitable
candidate class $\mathscr I$. To this end, we set
\begin{equation*}
    X := [0, \hat{x}],
    \quad \phi(x) := \ell'(0)x
    \quad \text{ and }  \quad
    \psi(x) := \ell(x).
\end{equation*}
Let $\mathscr I$ be all continuous $w \colon X \to \mathbbm R$ with $\phi \leq w \leq \psi$.
These upper and lower bounds have natural
interpretations.  Since completing all
remaining tasks at once is in the choice set, its value $\ell(x)$ is an upper
bound of the minimized value.  Regarding the lower bound
$\ell'(0)x $, this is the value that could be obtained if $\beta=1$ (no
discounting) and the agent, having no time constraint, subdivided without limit.

\begin{proposition}\label{p:ndp}
    The Bellman operator has a unique fixed point $w^*$
    in $\mathscr I$ and $T^nw \to w^*$ as $n \to \infty$ for all $w \in \mathscr I$.
    Moreover,
    %
    \begin{enumerate}
        \item $w^*$ is strictly increasing, strictly convex, and
            continuously differentiable, and
        \item The policy $\pi^*(x) := \argmin_{0 \leq a \leq x}\{\ell(a)
            + \beta w^*(x-a)\}$ is single-valued and satisfies

            \begin{equation}\label{eq:EN_gen}
                (w^*)'(x) = \ell'(\pi^*(x))
                \qquad (0 < x < \hat x).
            \end{equation}

    \end{enumerate}
    %
\end{proposition}

Stability of the fixed point
is derived from the monotonicity and concavity of the Bellman
operator in Appendix~\ref{ss:model-proofs}.
In Proposition~\ref{p:finite} we show that the convergence $T^nw \to w^*$
always converges in finite time.

\subsection{Equivalence}
So far, we have solved the Bellman equation~\eqref{eq:epe} and derived
properties of its solutions. However, it is not clear whether the Bellman
equation can characterize the solution to the dynamic optimization
problem~\eqref{eq:dpm}, since the constraint $\sum_t a_t = \hat{x}$ is not
in the Bellman equation. We turn to this issue now.

Let
\begin{equation}
    \label{eq:vf}
    W(x)
    := \min \; \left\{
        \sum_{t=0}^{\infty} \beta^t \ell(a_t)
        \,\; : \;\,
        \{a_t\} \in \mathbbm R_+^{\infty}
        \text{ and }
        \sum_{t=0}^{\infty} a_t = x
        \right\}
\end{equation}
be the \emph{value function} of the optimization problem~\eqref{eq:dpm}.
The next proposition shows that $W=w^*$, the fixed point of $T$,
and that the policy correspondence $\pi^*$
solves~\eqref{eq:dpm}. The proof can be found in
Appendix~\ref{ss:model-proofs}.

\begin{proposition} \label{p:policy}
    The sequence $\{a_t^*\}$
    defined by $x_0 = \hat x$, $x_{t+1} = x_t - \pi^*(x_t)$ and $a_t^* =
    \pi^*(x_t)$ is the unique solution to \eqref{eq:dpm}. Moreover, $W =
    w^*$.
\end{proposition}

The envelope condition \eqref{eq:EN_gen} now evaluates to
\begin{equation}
    \label{eq:EN}\tag{EN}
    W'(x_t) = \ell'(a_t^*)
\end{equation}
for all $t\geq 0$, which links marginal value to marginal disutility at
optimal action. Furthermore, \eqref{eq:EN} implies that the sequence
$\{a_t^*\}$ satisfies\footnote{To see this, note that $a^*_t$ solves
  $\inf_{0 \leq a \leq x_t} \left\{ \ell(a) + \beta w^*(x_t - a) \right\}$.
  Since both $\ell$ and $w^*$ are convex, elementary arguments show that
  either $\ell'(a^*_t) = \beta(w^*)'(x_t - a^*_t)$ or $a^*_t = x_t$. It
  follows from \eqref{eq:EN} that either $\ell'(a^*_t) = \beta
  \ell'(a^*_{t+1})$ or $a^*_{t+1} = 0$, which is equivalent to
  \eqref{eq:EU}.}
\begin{equation}
    \label{eq:EU}\tag{EU}
    \ell'(a_{t+1}^*)
    = \max
    \left\{
        \frac{1}{\beta} \ell'(a_t^*), \; \ell'(0)
    \right\}
\end{equation}
for all $t\geq 0$, which is akin to an Euler equation with a possibly
binding constraint. In the applications below we use \eqref{eq:EN} and
\eqref{eq:EU} to aid interpretation and provide economic intuition.

Equation~\eqref{eq:EU} implies that $\{a_t^*\}$ is a decreasing
sequence. This agrees with our intuition, since future losses are given greater
weight than current losses.

\subsection{Additional Results}

Instead of assuming $\ell' > 0$ as in \eqref{eq:ndas}, we can treat the case
$\ell'(0) = 0$, which has hitherto been excluded:

\begin{proposition}\label{p:co22}
    When $\ell'(0) = 0$, a feasible
    sequence $\{a^*_t\}$ solves \eqref{eq:dpm} if and only if \eqref{eq:EU}
    holds.  This sequence is unique, decreasing, and satisfies $a_t^* > 0$ for
    all $t$.
\end{proposition}

Proposition~\ref{p:co22} shows that the Euler equation~\eqref{eq:EU}
becomes necessary and sufficient for
optimality when $\ell'(0)=0$. In fact, \eqref{eq:EU} can be reduced to
$\beta\ell'(a^*_{t+1}) = \ell'(a^*_t)$ in this case, which helps
derive analytical solutions for some of the applications.

As the above results suggest, the set of tasks will be completed in finite
time if and only if $\ell'(0) > 0$.  The proof is in the appendix.

\section{Application: Production Chains}\label{s:app:production}

Now we turn to applications of our negative discount dynamic program
motivated by production problems. We begin with linear production chains.

\subsection{A Coasian Production Chain}\label{ss:cpc}

In this section we consider a version of the Coasian models developed by
\cite{kikuchi2018span}, \cite{fally2018coasian} and \cite{yu2019equilibrium}.
We show how competitive equilibrium in these models can be
calculated using the dynamic programming theory from Section~\ref{s:model}.

\subsubsection{Set Up}

Consider a market with many
price-taking firms, each of which is either inactive or part of the
production of a single good.  To produce a unit of this good requires
implementing a unit mass of tasks.
The cost for any one firm of implementing an interval of
length $v \in [0,1]$ is denoted $c(v)$, where $c$ is
increasing, strictly convex, continuously differentiable, and satisfies
$c(0)=0$.\footnote{Unlike \cite{kikuchi2018span}, we allow $c'(0)=0$.}

Firms face transaction costs, as
a wedge between cost to the buyer and payment
received by the seller.\footnote{This follows \cite{kikuchi2018span} and also
    studies such as \cite{boehm2020misallocation}, where frictions in contract
    enforcement are treated as a variable wedge
    between effective cost to the buyer and payment to the supplier.}
Transaction costs fall on buyers, so that, for a
transaction with face value $f$, the seller receives $f$ and the buyer
pays $(1+\tau) f$ with $\tau > 0$.\footnote{For example, $\tau f$ might be the cost of writing a contract
for a transaction with face value $f$.  This cost rises in $f$ because more
expensive transactions merit more careful contracts.}

Firms are indexed by integers $i \geq 0$.  A feasible allocation of tasks across firms is a
nonnegative sequence $\{v_i\}$ with $\sum_{i \geq 0} v_i
= 1$.  We identify firm $0$ with the most downstream
firm, firm $1$ with the second most downstream firm, and so on.
Let $b_i$ be the downstream boundary of firm $i$, so
that $b_0 = 1$ and $b_{i+1} = b_i - v_i$ for all $i\geq 0$.
Then, profits of the $i$th firm are
\begin{equation}
    \label{eq:prof}
    \pi_i = p(b_i) - c(v_i) - (1+\tau) p(b_{i+1}) .
\end{equation}
Here $p \colon [0, 1] \to \mathbbm R_+$ is a price function, with
$p(t)$ interpreted as the price of the good at processing stage $t$.

\begin{definition}
    \label{d:eq}
    Given a price function $p$ and a feasible allocation $\{v_i\}$,
    let $\{\pi_i\}$ be corresponding profits, as defined in
    \eqref{eq:prof}.  The pair $(p, \{v_i\})$ is called an
    \emph{equilibrium} for the production chain if
    %
    \begin{itemize}
        \item[1.] $\; p(0) = 0$,
        \item[2.] $p(s) - c(s - t) -  (1+\tau) p(t) \leq 0$ for any pair $s, t$
            with $0 \leq t \leq s \leq 1$, and
        \item[3.] $\; \pi_i = 0$ for all $i$.
    \end{itemize}
    %
\end{definition}
Conditions 1--3 eliminate profits for active firms and prevent entry by
inactive firms.

\subsubsection{Solution by Dynamic Programming}

\label{sss:sdp}

An equilibrium of the production chain satisfies
$p(b_i) = c(v_i) + (1+\tau)p(b_i - v_i)$, which has the same form as the
Bellman equation~\eqref{eq:epe}. Moreover, iterating on this relation yields
the price of the final good
\begin{equation}
    \label{eq:p0}
    p(1) = \sum_{i \geq 0} (1+\tau)^i c(v_i),
\end{equation}
which is analogous to the total loss in \eqref{eq:dpm}.
These facts lead us to a version of the negative discount
dynamic program introduced in Section~\ref{s:model} where a (fictitious)
agent seeks to minimize $\sum_{i \geq 0} (1 + \tau)^i c(a_i)$ subject to
$\sum_{i \geq 0} a_i = 1$.  By construction, any
feasible action path is also a feasible allocation of tasks in the
production chain.

Since $\ell = c$ and $\beta = 1 + \tau$,
the assumptions in~\eqref{eq:ndas} are satisfied.  Hence
there exists a unique solution $\{a^*_i\}$ by Proposition~\ref{p:policy}. Let $W$ be the corresponding
value function given by \eqref{eq:vf}. The next proposition shows that the
solution to this dynamic program is precisely the competitive equilibrium of
the Coasian production chain.

\begin{proposition}
    \label{p:oie}
    If $p = W$ and $v_i = a_i^*$ for all $i \geq 0$, then $(p, \{v_i\})$
    is an equilibrium for the production chain.
\end{proposition}

For firm
with downstream boundary $b_i$, the envelope condition~\eqref{eq:EN} yields
\begin{equation}
    \label{eq:dofc}
    p'(b_i) = c'(v_i).
\end{equation}
Since $v_i$ is the optimal range of tasks implemented in-house by firm~$i$
in equilibrium, this expresses Coase's key idea: the size of the
firm is determined as the scale that equalizes the marginal costs of in-house
and market-based operations.
The Euler equation~\eqref{eq:EU} also implies
that $\{v_i\}$ is decreasing, so firm size increases with
downstreamness. This generalizes a finding of
\cite{kikuchi2018span}.

\subsubsection{An Example}

\label{sss:cf}

Suppose that the range of
tasks $v$ implemented by a given firm satisfies $v = f(k, n)$, where $k$ is
capital and $n$ is labor.  Given rental rate $r$ and wage rate $w$, the cost
function is $c(v) := \min_{k, n} \{rk + wn \}$ subject to $f(k, n) \geq v$.
Suppose further that, as in \cite{lucas1978size}, the production
function has the form $\phi(g(k, n))$, where $g$ has constant returns to scale
and $\phi$ is increasing and strictly concave (due to
``span-of-control'' costs).  To generate a closed-form solution, we take
    $g(k, n) = A k^\alpha n^{(1-\alpha)}$ and
    $\phi(x) = x^\eta$,
with $0 < \alpha, \eta < 1$.  The resulting cost function has the form $c(v) =
\kappa v^{1/\eta}$, where $\kappa$ is a positive constant.

By Proposition~\ref{p:oie}, the optimal action path for the fictitious agent
corresponds to the equilibrium allocation of tasks across firms, and the
value function is the equilibrium price function. Since $c'(0) = 0$,
Proposition~\ref{p:co22} applies and~\eqref{eq:EU}
yields $a^*_{i+1} = \theta a^*_i$ for all $i \geq 0$, where $\theta :=
(1+\tau)^{\eta/(\eta - 1)} < 1$. From $\sum_{i = 0}^{\infty} a^*_i = 1$ we
obtain $v_i = a^*_i = \theta^i (1 - \theta)$.  Substituting this path into
\eqref{eq:vf} gives the price function
\begin{equation}\label{eq:wcfe}
    p(x) = W(x) =
    \kappa
    \left(1 - \theta\right)^{(1-\eta)/\eta} x^{1/\eta}.
\end{equation}
As anticipated by the theory, $p$ is strictly increasing and strictly
convex.

Intuitively, firm-level
span-of-control costs cannot be eliminated in aggregate due to transaction
costs, which force firms to maintain a certain size. This leads to strict
convexity of prices. If firms have constant returns to management ($\eta=1$),
then the price function in \eqref{eq:wcfe} becomes linear.\footnote{The above
    result on the size of firms is related to
    \cite{antras2020geography}, who prove it is optimal to locate
    relatively downstream stages of production in relatively central locations
    where trade costs are lower. Their result holds because trade costs have more
    pronounced effects in more downstream stages of production in their model.
    Similarly, in our model, transaction costs have more pronounced effects in
    more downstream states of production, due to~\eqref{eq:EU}.}

\subsection{Specialization and Failure Probabilities}

Production processes typically involve a series of complementary tasks.
Mistakes in any one task can dramatically reduce the product's value.
Implications of such specialization and failure probabilities were studied in,
among others, the O-ring theory of economic development by
\cite{kremer1993ring} and the production chain models of
\cite{levine2012production} and \cite{costinot2013elementary}.
These papers show how equilibrium
allocations can serve to mitigate the potentially exponential cost of failures in
long production chains.\footnote{For example, in \cite{levine2012production}, long chains
    involve a high degree of specialization and produce a large quantity of
    output but are also more prone to failure. However, chains in his model
    are long only if the failure rate is low thus mitigating the exponential
    impact that production failure of a single link has on output.  Similarly,
    \cite{costinot2013elementary},  in a global supply chain model where
    production of the final goods is sequential and subject to mistakes, show
that countries with lower probabilities of making mistakes specialize in later
stages of production.} In this section, we show that these ideas
 are also amenable to analysis
using the negative discount dynamic program from Section~\ref{s:model}.

Consider, as before, a competitive market where producers implement a
mass of tasks contained in $[0, 1]$. We drop the assumption of
positive transaction costs and replace it with
positive probability of defects.\footnote{Defects can alternatively be understood as
iceberg costs, where some percentage of goods are lost in transporting them
from one producer to the next.} Due to these defects, a producer who buys at
stage $t$ and sells at $s > t$ must buy $1+\tau$ units of the partially
completed good at $t$ to sell one unit of the processed good at $s$. Larger
$\tau$ then corresponds to a production process that is more prone to
failure. Profits for such a firm facing price function $p$ are
\begin{equation*}
	\pi = p(s) - c(s-t) - (1 + \tau) p(t).
\end{equation*}
This parallels the profit function \eqref{eq:prof} from the Coasian
production chain model.  If we
adopt the Cobb--Douglass technology from Section~\ref{sss:cf},
then the price of the final good is
\begin{equation}
	\label{eq:final-price}
	p^*(1) = \kappa \left( 1- (1 + \tau)^{\eta/(\eta-1)} \right)^{(1-\eta)/\eta}.
\end{equation}

A rise in the failure probability
leads to only a moderate increase in the final good price. This is because
producers increase their range of internal production to mitigate any rise in cost
associated with a higher production failure of upstream producers. As a result,
there are fewer producers in production chains and the
compounding effect of higher production failures is limited.

To clarify this point, let us compare this outcome with
a hypothetical model where producers do not adjust their
production according to failure probabilities. Suppose in particular that
production chains are simply divided into equal tasks by $N$
producers. In this case, the final good price is
\begin{equation}
	\label{eq:final-price-hypothetical}
	{\hat p^*(1)}
	= \kappa \sum_{i=0}^N(1 + \tau)^i
	\left(\frac{1}{N}\right)^{1/\eta}
	= \kappa \frac{(1+\tau)^N - 1}{(1+\tau) - 1}
    \left( \frac{1}{N} \right)^{1/\eta}
	=O((1+\tau)^N).
\end{equation}
Now a small increase in $\tau$ increases the final good price
exponentially. This is intuitive, as an increase in cost compounds over all
producers involved in the production chain. See Figure~\ref{fig:price} for
a comparison of prices with and without producers adjusting for failure
probabilities.\footnote{In this example, we set $\kappa = 1$, $\eta = 0.5$,
	and $N = 50$.}

\begin{figure}
	\centering
	\includegraphics[width=0.8\textwidth]{price}
	\caption{Final good price and failure probabilities.}
	\label{fig:price}
\end{figure}

Thus, returning to the original model, we see that equilibrium prices induce
producers to adjust to changes in failure probabilities, which optimally
mitigates the potentially exponential impact of failures on the cost of the
final good.

\section{Application: Knowledge and Communication}
\label{s:app:knowledge}

Many firms are characterized by a pyramidal structure, in which employees form
management layers with each layer smaller than the previous
one.  These features were modeled by \cite{garicano2000hierarchies},
where hierarchical organization of
knowledge involves a trade-off between the cost of acquiring problem solving
knowledge and the cost of communicating with others for help.   In this
section, we solve a version of Garicano's model using the dynamic programming
theory from Section~\ref{s:model}.

Consider a firm where production requires solving a
set of problems.
Employees at management layer $i$ are
assigned problems $m_i\in[0,1]$. They learn to solve $z_i$ at cost $c(z_i)$ and pass
on the remainder $m_{i+1} = m_i - z_i$ to the next management layer $i+1$. This
incurs additional communication costs that are proportional to the value
of problems assigned to layer $i+1$ with coefficient $\tau$.

Let $p\colon [0, 1] \to \mathbbm R$ be a (fictitious) price
function that assigns value to problems. Profits
of the $i$th management layer are
\begin{equation*}
    \pi(m_i,z_i)=p(m_i)-(1+\tau)p(m_{i}-z_i)-c(z_i),
\end{equation*}
where $p(m_i)$ is the value of problems assigned to layer $i$, $(1+\tau) p(m_i -
z_i)$ is the cost of communicating and assigning unsolved problems to the
next layer, and $c(z_i)$ is the cost of learning to solve $z_i$.
Setting profits to zero and minimizing with respect to $m_{i+1}$ yields
\begin{equation*}
    p(m_i)=\min_{m_{i+1}\leq m_i}\{c(m_i-m_{i+1})+(1+\tau)p(m_{i+1})\}.
\end{equation*}
This parallels the Bellman equation \eqref{eq:epe} of the negative discount
dynamic program in Section \ref{s:model}.

Suppose that $n$ employees can learn to solve $z = f(n)$ problems.
In other words, for a given
range of problems $z$, the number of employees required to solve $z$ is $n =f^{-1}(z)$.
Assume that $f$ is strictly increasing, strictly concave, and continuously
differentiable with $f(0) = 0$, and that $c(z) = wn = wf^{-1}(z)$ for some
wage rate $w$. Then the assumptions in \eqref{eq:ndas} are satisfied if we let $\ell = c$
and $\beta = 1+\tau$. The Euler equation~\eqref{eq:EU} implies that the
optimal sequence $\{z_i\}$ is decreasing, as is the number of
employees in each layer as $n_i = c(z_i)/w$. This replicates
Garicano's result that the top management layer has the smallest number of
employees and each layer below is larger than the one above.

The Euler equation \eqref{eq:EU} adds additional insight: each layer of
management acquires knowledge up to the point where the marginal cost of
learning equals the marginal cost of communicating and assigning unsolved
problems to the next layer.  The envelope condition~\eqref{eq:EN} implies
$p'(m_i)=c'(z_i)$, which says that, in equilibrium, the marginal value of
problems assigned to a management layer equals the marginal cost of learning
to solve problems within the layer.\footnote{This result is analogous to
    \eqref{eq:dofc} for the production chain model and reminiscent of Coase's
theory of the firm in the context of knowledge organization within a firm.}

\begin{figure}[tb!]
	\centering
	\begin{subfigure}{0.33\textwidth}
		\centering
		\includegraphics[height=0.9\textwidth]{chain1.pdf}
		\caption{$\tau = 0.2$}
	\end{subfigure}%
	\begin{subfigure}{0.33\textwidth}
		\centering
		\includegraphics[height=0.9\textwidth]{chain2.pdf}
		\caption{$\tau = 0.4$}
	\end{subfigure}
	\begin{subfigure}{0.33\textwidth}
		\centering
		\includegraphics[height=0.9\textwidth]{chain3.pdf}
		\caption{$\tau = 0.6$}
	\end{subfigure}%
	\caption{Optimal organizational structures.}
	\label{fig:garicano}
\end{figure}

Figure~\ref{fig:garicano} plots the optimal organizational structures of
three firms given by the model above.\footnote{We set $c(z) = z^{1.2}$ and
	$m_0 = 1$.} Each node corresponds to one management layer, who asks the
layer above for help, and its size is proportional to the number of
employees in that layer. As shown in the graphs, each firm has a pyramidal
structure and higher communication costs increase the relative knowledge
acquisition of lower layers and reduce the number of layers.

\section{Extension: Nonlinear Networks}
\label{s:app:networks}

In this section we treat more general network models that cannot be directly
handled by the theory in Section~\ref{s:model}.  Unlike the linear chains
discussed above, agents can interact with multiple partners. In
Section~\ref{ss:spatial}, we study a problem from economic geography.  In
Section~\ref{ss:network} we study chains with multiple upstream partners using
a general dynamic programming theory developed in Appendix~\ref{ss:gdp}.

\subsection{Spatial Networks}
\label{ss:spatial}

The distribution of city sizes shows remarkable regularity, as described by the
rank-size rule.\footnote{See \cite{gabaix2004evolution} and \cite{gabaix2009power} for
surveys.} One early attempt to  match the empirical city size
distribution is found in the central place theory of \cite{christaller1933central}.
\cite{hsu2012central} and \cite{hsu2014optimal} formalize Christaller's theory.
  In this section, we develop a model with similar insights
 by extending our earlier dynamic programming results.

Consider a government that opens competition for many developers to build
cities to host a continuum of dwellers indexed by $[0, 1]$. Each developer can
build a large city that hosts everyone or
build a smaller city and pay other developers to build
``satellite cities'' that host the rest of the
population. Further satellites can be built
for existing cities until all dwellers are accommodated.
This chain of city building
starts with a single developer, who is assigned the whole population, and
ends with a network of cities consisting of multiple layers.

Building satellite cities incurs extra costs that are charged as an ad
valorem tax on the payments to
the developers. We can think of the extra costs as costs of
providing public goods that connect different cities such as roads,
electricity, water, telecommunication, etc.
Developers are paid according to a price $p \colon [0, 1] \to \mathbbm R$, which is a
function of the population assigned. The cost function of building a
city is $c \colon [0, 1] \to \mathbbm R$ and the tax rate is
$\tau$. A developer assigned to host $s$ dwellers maximizes profits by
solving
\begin{equation*}
    \max_{0 \leq t \leq s}
    \left\{
        p(s) - c(s-t) - (1+\tau) k p\left( \frac{t}{k} \right)
    \right\},
\end{equation*}
where $p(s)$ is the payment to the developer, $c(s-t)$ is the cost of
building a city of population $s-t$, $k$ is the number of satellite cities,
and $(1+\tau) k p(t/k)$ is the cost of assigning population $t/k$ to $k$
satellites.  In equilibrium, a city network is formed
where every dweller is accommodated and every developer makes zero profits.
The equilibrium price function satisfies
\begin{equation}
    \label{eq:city}
    p(s) = \min_{0 \leq t \leq s}
    \left\{
        c(s-t) + (1+\tau) k p\left( \frac{t}{k} \right)
    \right\}.
\end{equation}
To find the equilibrium price function, we first solve a negative discount
dynamic program and then show that its value
function is the solution to \eqref{eq:city}.

Consider a dynamic optimization
problem with value function given by
\begin{equation}
    \label{eq:city_W}
    W(x) := \min_{\{v_i\}} \left\{
        \sum_{i=0}^\infty (1+\tau)^i k^i c(v_i):
        \{v_i\}\in \mathbbm R_+^\infty \text{ and } \sum_{i=0}^\infty k^i v_i = x
    \right\}.
\end{equation}
The problem in \eqref{eq:city_W} is a modified version of \eqref{eq:dpm}
that also features negative discounting and a convex loss function. In the
context of our city network model, \eqref{eq:city_W} describes a social
planner who minimizes the total cost of hosting the whole population, where
$v_i$ stands for the size of cities on layer $i$.

In what follows we let $c(s) = s^\gamma$ with $\gamma > 1$. To emulate the
bifurcation process in \cite{hsu2012central} and \cite{hsu2014optimal}, we let
$k = 2$.  A similar argument to the proof of Proposition~\ref{p:co22} gives
the Euler equation
\begin{equation}
    \label{eq:EU_city}
    c'(v_i) = (1 + \tau) c'(v_{i+1}).
\end{equation}
Using this equation, it can be shown with some algebra that
$v_i = \theta^i (1-2\theta)$ for $\theta := (1+\tau)^{1/(1-\gamma)} < 1/2$
and the value function is $W(s) = (1-2\theta)^{\gamma-1} s^\gamma$.
It is
straightforward to verify that $p=W$ satisfies \eqref{eq:city}. Hence, the
value function for the social planner is also the equilibrium price function
under which all developers make zero profits.

The Euler equation~\eqref{eq:EU_city} describes the emergence of
optimal city hierarchy where each developer expands a city to accommodate
more dwellers until the marginal cost of expanding equals the marginal cost
of building and expanding satellite cities.
An envelope condition
similar to \eqref{eq:EN} also
holds: if a developer is assigned $s$ dwellers and delegate $t$ dwellers to
satellite cities, the equilibrium is reached when $p'(s) = c'(s-t)$. This
shows that the marginal value that a city provides must be equal to the
marginal cost of accommodating one more city dweller.

\begin{figure}
	\centering
	\includegraphics[width=0.8\textwidth]{city}
	\caption{Illustration of optimal city hierarchy.}
	\label{fig:city}
\end{figure}

Figure~\ref{fig:city} illustrates the optimal city hierarchy by placing
cities according to \cite{hsu2012central} and
\cite{hsu2014optimal}.\footnote{We set $\gamma = 1.2$ and $\tau = 0.2$.} It
replicates the relative sizes of cities on different layers as in
\cite{hsu2012central} and \cite{hsu2014optimal}. Moreover, since the number
of cities doubles from one layer to the next, the rank of a city on layer
$i$ is $2^i$. Hence, the city size distribution generated by our model
follows a power law similar to \cite{hsu2012central}. In fact, the rank and
size of a city satisfy
\begin{equation*}
    \ln(Rank) = - \frac{\ln(1/2)}{\ln(\theta)} \ln(Size) + C,
\end{equation*}
where $C$ is a constant determined by $\theta$. When $\theta$ approaches
$1/2$, the slope approaches one, which corresponds to the well-documented
rank-size rule.

\subsection{Snakes and Spiders}\label{ss:network}

Modern production networks are characterized by processes that are both
sequential and non-sequential.
\cite{baldwin2013spiders} refer to the sequential processes  as ``snakes'' and
the non-sequential processes as ``spiders'', and analyze how the location of
different parts of a production chain is determined by unbundling costs of
production across borders. Here we study a model of production
networks featuring both snakes and spiders.

As in \cite{kikuchi2018span} and \cite{yu2019equilibrium}, we consider a
generalization of the production chain model in Section~\ref{ss:cpc}, where
each firm can also choose the number of suppliers.
 To account for costs of
extending spiders, we assume that firms bear an additive assembly cost $g$
that is strictly increasing in the number of suppliers, with $g(1) = 0$. Then
for a firm at stage $s$ that subcontracts tasks of range $t$ to $k$ suppliers,
the profits are
\begin{equation*}
p(s) - c(s-t) - g(k) - (1+\tau)kp(t/k),
\end{equation*}
where $p$ is the price function. Having multiple suppliers leads to another
trade-off: firms potentially benefit from subcontracting at a lower price
but also have to pay additional assembly costs.

We index the layers in the production network by integers $i\geq 0$ with layer 0
consisting only of the most downstream firm. Let $b_i$ be the downstream
boundary of firms on layer $i$, each producing $v_i$ and having $k_i$
suppliers. Then the boundary of firms on the next layer is given by $b_{i+1}
= (b_i - v_i)/k_i$.  We call $(p, \{v_i\},
\{k_i\})$ an equilibrium for the production
network if (i) $p(0) = 0$, (ii) $p(s) - c(s-t) - g(k) - (1+\tau)kp(t/k) \leq
0$ for all $0 \leq t \leq s \leq 1$ and $k\in\mathbbm N$, and (iii) $\pi_i = 0$ for
all $i\geq 0$ where
\begin{equation}\label{eq:prof_mp}
    \pi_i := p(b_i) - c(v_i) - g(k_i) - (1+\tau)k_ip
    \left( \frac{b_i - v_i}{k_i} \right).
\end{equation}

As in Section~\ref{sss:sdp}, we seek to find an equilibrium using dynamic
programming methods. Let $p^*$ be the solution to the following Bellman
equation
\begin{equation}\label{eq:mp}
    p(s) = \min_{\substack{0 \leq t\leq s\\ k\in\mathbbm N}}
    \left\{
    c(s-t) + g(k) + (1+\tau)kp(t/k)
    \right\}.
\end{equation}
Let $v_i = b_i - t^*(b_i)$ and $k_i = k^*(b_i)$ where $t^*(s)$ and $k^*(s)$
are the minimizers under $p^*$. Let $\mathscr I$ be all continuous $p$ such that
$c'(0)s \leq p(s) \leq c(s)$ for all $s\in [0, 1]$.

\begin{proposition}
	\label{p:eq_mp}
	If $c'(0) > 0$ and $g(k) \to \infty$ as
	$k\to\infty$, then \eqref{eq:mp} has a unique solution $p^*\in\mathscr I$ and $(p^*,
	\{v_i\}, \{k_i\})$ is an equilibrium for the production network.
\end{proposition}

In Appendix~\ref{ss:networks-proofs}, we show that the unique solution $p^*$ can be
computed by value function iteration. We then prove that $p^*$ induces an
equilibrium allocation. Theorem~\ref{t:con} can also be used to show the
monotonicity of $p^*$.

Figure~\ref{fig:network} plots two production networks with different
transaction costs, where each node corresponds to a firm in the network and
the one in the center is the most downstream firm.\footnote{We set $c(v) =
    v^{1.5}$ and $g(k) =
  0.0001(k-1)^{1.5}$.} The size of each node is proportional to the size of
    the firm, represented by the sum of assembly and transaction costs.
    Figure~\ref{fig:network} shows that more downstream firms are larger and
    have more upstream suppliers. Comparing panels (A) and (B), we can see
    that lower transaction costs increase the number of firms involved in the
    production network, encouraging the expansion of snakes. This is in line
    with the model prediction of \cite{baldwin2013spiders} that decreasing
    frictions leads to a finer fragmentation of the
    production.\footnote{\citeauthor{tyazhelnikov2019production}'s \citeyearpar{tyazhelnikov2019production} model of international
        production chains shares some features with the model above.  His
        model nests both snakes and spiders.  Each firm makes optimal decision
        conditional on its production location at the next stage. If we
        interpret market transactions as offshoring, the multiple upstream
        supplier model becomes a model in which firms decide to produce parts
    of a production chain in any number of countries.}

\begin{figure}[tb!]
  \centering
  \begin{subfigure}{0.5\textwidth}
    \centering
    \includegraphics[height=0.7\textwidth]{network1.pdf}
    \caption{$\tau = 0.2$}
  \end{subfigure}%
  \begin{subfigure}{0.5\textwidth}
    \centering
    \includegraphics[height=0.7\textwidth]{network2.pdf}
    \caption{$\tau = 0.05$}
  \end{subfigure}
  \caption{Examples of production networks.}
  \label{fig:network}
\end{figure}

\section{Conclusion}

\label{s:c}

This paper shows how competitive equilibria in a range of production chain and
network models can be recovered as solutions to dynamic programming problems.
Equilibrium prices are identified with the value function of a dynamic
program, while competitive allocations across firms are identified with
choices under the optimal policy.  Dynamic programming methods are brought to
bear on both the theory of the firm and the structure of production networks,
providing new insights, as well as new analytical and computational methods.
In addition to production problems, we also consider related competitive
problems from economic geography and firm management.

Apart from the model of snakes and spiders in Section~\ref{ss:network}, all of
the problems faced by individual firms are convex.  This assumption allowed us to obtain
sharp results and useful characterizations.  An important remaining task is to
extend our results to a range of cases that feature non-convexities. This work
is left for future research.

redpajama_set_name: RedPajamaArXiv


text:
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		var db = Ti.Database.open('routes_db');

		var rows = db.execute("SELECT * FROM stream WHERE bus_route_number = '"+bus_number+"' ORDER BY run,stop_sequence");
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		var i = 0;
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				bus_number:rows.fieldByName('bus_route_number'),
				run:rows.fieldByName('run'),
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				stop_id:rows.fieldByName('stop_id'),
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redpajama_set_name: RedPajamaGithub


Roll-up blanket is a great way to keep them warm at outdoor events and promote your brand! Add to your company store or giveaway at the company picnic.
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Edkins's examples and comparisons which she cites in her explanation of the trauma also link to violence against the women. Authoress states that trauma happens when people who are closest to us betray us. There are several questions which she brings up in order to explain the term trauma such as: What is trauma? How does it happen? Are human beings subject to political trauma in everyday situation? How can we cope and overcome trauma? How can we live with the fact that we have experienced trauma in certain period of our life? Based on Edkins's trauma definition the purpose of this paper is to analyze psycho-social aspects of trauma and its transmission in post war BosniaHerzegovina.
Keywords: Trauma, Individual and Collective Trauma, Transmission, Socio-psychological Approach.


text:
Roman Polanski compares US justice system to Nazis'
| Updated: Aug 23, 2017 11:20 IST
Los Angeles [USA], Apr. 15 (ANI): After getting denied to be assured of no more jail time for the 1977 rape of a 13-year-old-girl, director Roman Polanski is not giving up on hopes to return to the US and has compared the country's justice system to that of 'Nazis.' As per the Hollywood Reporter, his attorney Harland Braun said, "The Court should consider why Mr. Polanski was not charged with unlawful flight by either the State or federal authorities. Mr. Polanski was as justified in fleeing this Court's illegal conduct as he was to flee the Germans who invaded Poland." The attorney argued that Gordon failed to mention in his decision the reason Polanski fled because it eviscerates his theory for applying the doctrine of fugitive disentitlement, which holds that a fugitive from justice can't seek relief from the judicial system whose authority he or she is evading. Earlier, the Oscar-winning director asked the court to state on the record, whether they believe he has served his time for the 1977 case but Judge Scott Gordon denied this request. Polanski's attorney Braun, recently filed a motion to reconsider and called the judge's order morally incoherent, legally illogical, and factually deceptive. Braun writes, "Rather than the 90 days promised Mr. Polanski, this Court threatened Mr. Polanski with up to 50 years in state prison and deportation. f a defendant flees because of an illegal judicial threat, that threat should be removed before the defendant is expected to return to court." Braun states that the only question before the court is a simple one - what was Polanski promised 40 years ago? He says declarations of defense counsel, the victim's lawyer and former Deputy District Attorney Roger Gunson all show that Polanski's 43 days of psychiatric evaluation were intended to satisfy his total custody time. Gunson's sworn testimony is currently sealed, and Braun has filed a motion to make that public. "Once the promise is established, this case solves itself .The Court has no legal alternative but to give Mr. Polanski credit for his total custody time in California and Switzerland," wrote Braun noting that while 43 days had been deemed sufficient, Polanski later served more than 9 months in Swiss custody while authorities were deciding whether or not to extradite him. "What if the People represented to the Court that Mr. Polanski owes no more custody time," Braun asks. "Does that not simplify this proceeding?," said Braun stating that judges asking prosecutors "what is the peoples position?" is a commonplace occurrence in criminal courtrooms and there is nothing strange or unprecedented about Polanski wanting that question answered in his case. A hearing on the motion to unseal Gunson's testimony is currently set for April 25, which will likely also be the date the motion to reconsider is heard. (ANI)


I wouldn't think they have a fixed format in mind.
Just make sure that you organise your thoughts logically, plan out a basic structure and write clearly.
You can always post it here for comments.
Hunt around and see what you can find. Good luck!


Take a look outside. You've probably already noticed the once-green trees have now turned beautiful shades of red, yellow and orange. Aren't we fortunate to have the ability to observe the gorgeous colors of fall? For those of us who have clear vision or glasses, it's not uncommon for us to take our sight for granted, but it's important to remember that not everyone has the same opportunities.
You may be surprised to learn that approximately 1.2 billion people don't have access to glasses – that amounts to over 3 out of 4 people around the globe. You can help increase the world's awareness of eye care issues by helping us celebrate World Sight Day on Tuesday, October 11.
2018 is the sixth year of the World Health Organization Action Plan and this year's call to action is "Eye Care Everywhere." The International Agency for Prevent Blindness is encouraging all of us to focus on eye care issues, so that everyone, everywhere has access to good eye health.
How can you help? One way is by utilizing one of our most prized resources, the Eyeglass Recycling Center. The Wisconsin Lions Foundation's Eyeglass Recycling Center (ERC) is one of only 18 worldwide facilities that collects used glasses to share with the world and is located right here on the Wisconsin Lions Foundation Headquarters.
At any given time, the ERC inventory is about 125,000 pairs of glasses. These glasses are then provided without costs to sponsors of Vision Mission Projects to developing countries. Some mission groups are Lions, but there are several others, often including vision professionals.
To commemorate World Vision Day, consider organizing an eyeglass collection drive or simply promote your area collection box. Of course, there are many other ways to help, including conducting eye and vision screenings within your local community, working with eye care professionals to create an eye health presentation or holding an educational event promote diabetes awareness and related vision loss.
No matter how you choose to serve, know that you are making a big difference to the sight of your community and to others who live all over the world. Let's work together to ensure that everyone, everywhere has access to sight.
World Vision Day information provided by your friends at Lions Pride!
Parents of school-aged children have a huge laundry list of items that they need to get through before the new the school year begins. They need to go-back-to-school shopping, get their children registered and see the primary doctor, but there is an important task that doesn't often make the cut – scheduling an appointment with the optometrist.
Eighty percent of a child's learning is related to sight; however, vision problems affect one in twenty preschoolers and one in four school-aged children. The biggest issue is that children sometime don't know or can't tell when they aren't seeing correctly. After visiting the eye care professional, there is no question.
Without early detection and treatment, some vision problems can lead to more serious complications such as permanent vision loss, learning disabilities and delayed development. Checking for these conditions is part of a routine eye exam.
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For the rest of the month, Lions Pride is encouraging your loved ones to schedule an eye exam for their children as well as themselves. Let's work together to be sure everyone is seeing clearly!


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        script: 'server.js',
        ext: 'js',
        ignore: [
            paths.app + '/**',
            paths.jade.src + '/**',
            paths.dist + '/**',
            'node_modules/**'
        ]
    }).on('start', function () {
        cb();
    });
});

/* ========== */
/* PRODUCTION */
/* ========== */

gulp.task('build', function() {
    return runSequence('build:clean', ['build:js', 'build:icons', 'build:images', 'build:scss']);
});

gulp.task('build:scss', function() {
    gulp.src(paths.sass.src + '/*.scss')
        .pipe(plumber({
            errorHandler: onError
        }))
        .pipe(compass({
            project: __dirname,
            css: paths.css.dist,
            sass: paths.sass.src,
            require: ['compass/import-once/activate', 'bootstrap-sass']
        }))
        .pipe(autoprefixer({
            browsers: ['last 2 versions']
        }))
        .pipe(minifyCSS())
        .pipe(gulp.dest(paths.css.dist));
});

gulp.task('build:images', function() {
    return gulp.src(paths.images.src)
        .pipe(gulp.dest(paths.images.dist));
});

// just a icon hack
gulp.task('build:icons', function() {
    return gulp.src('app/assets/icons/**', {base:'app/assets/'})
        .pipe(gulp.dest('public/assets'));
});

gulp.task('build:js', function() {
    return gulp.src(paths.js.src)
        .pipe(plumber({
            errorHandler: onError
        }))
        .pipe(replace(/GULP_APP_VERSION/g, version))
        .pipe(jshint())
        .pipe(jshint.reporter(stylish))
        .pipe(babel())
        .pipe(sourcemaps.init())
            .pipe(concat('bundle.min.js'))
            .pipe(ngAnnotate())
            .pipe(uglify())
        .pipe(sourcemaps.write())
        .pipe(gulp.dest(paths.js.dist));
});

gulp.task('build:clean', function(cb) {
    del([
        paths.dist
    ], cb);
});

/*========*/
/* OTHERS */
/*========*/

// Gulp plumber error handler
var onError = function(err) {
    console.error(err.message);
    this.emit('end');
};


You're invited to the opening reception for our group exhibit, Perspective: In Depth on Friday, July 14th!
Come celebrate the latest exhibition at Studio Oh! in Pilsen. Then explore 30+ creative spaces for 2nd Fridays Gallery Night in the Chicago Arts District.
When: The opening Reception is Friday evening, July 14th from 6 – 10 PM at Studio Oh gallery, 1837 S. Halsted Street in Chicago. It is free and open to the public. Enjoy light refreshments and see vivid, engaging artwork. The exhibit is on display from July 11 until August 31st. Closing reception is on August 11.
What: Perspective In Depth is a group exhibit curated by Erwin Overes and Lisa Stefaniak at Studio Oh! gallery. Exhibiting artists include: Lydia Cheng, John Cline, Eric Cortez, Jazmin Dua, Janet Hamilton, Eddie Parach, Drew Reynolds, Leon Sarantos, Ronit Wiener.
Two of my cityscape paintings are on display including Coffee Shop, UChicago and Art Fair On Oliver Street.
Where: Studio Oh! is in Pilsen in the heart of the Chicago Arts District at 1837 S. Halsted Street, Chicago. Hours: Tuesdays and Saturdays from 1 PM till 6 PM. Outside of these hours, you are welcome to make an appointment. Phone (773) 474-1070.
Posted on June 30, 2017. Share on Facebook or Pinterest.


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Second Deputy Chief John Roach: All three deaths occurred between 9 and 9:20 a.m.
(CNN) -- Three runners died Sunday during the Detroit Free Press/Flagstar Marathon in Detroit, Michigan, police told CNN.
An EMT vehicle is at the scene Sunday in Detroit after three runners collapsed at a marathon.
All three deaths occurred between 9 and 9:20 a.m. ET, Second Deputy Chief John Roach said.
A man in his 60s fell and hit his head, Roach said. The cause of the fall was unknown. The man was transported to Detroit Receiving Hospital, where he was pronounced dead.
Two other men, ages 36 and 26, also collapsed during the race and were pronounced dead at the hospital, Roach said.
The weather at the time was overcast, Roach said, with temperatures in the low 40s.


Plant & Machinery Trade Shows in Johannesburg - Plant & Machinery Trade Fairs, Conferences, Events & Business Exhibitions in Johannesburg.
Find out comprehensive information on Plant & Machinery trade shows, trade fairs, conferences, events & business exhibitions to be held in Johannesburg.
Safety Control Systems Conference 2010 is a leading event, targeted on safety control systems for industrial processes and machinery, in South Africa.
Comprehensive Industrial Extractive Metallurgical Workshops is the most important event focusing on metallurgical industry in South Africa.
The Manufacturing Show Africa 2011 is one of the grandest and magnificent trade conference and exhibition for manufacturing sector, in Johannesburg.


Dileep and Kavya Madhavan are moving to Australia for the shooting of a song for their film Inspector Garud.
The movie recounts the story of a police inspector, Madhavan who takes care of the Thevara police station. Written by Sibi-Uday, the movie is produced by Milan Jaleel. Johny Anthony directs the film.
The movie that is in its final stages of shooting will be released on the republic day in 2007. This marks the first movie of Dileep in the New Year.