text:
<?php

class dmRecordLoremizer extends dmConfigurable
{
  protected
  $record,
  $table;

  public function __construct(array $options = array())
  {
    $this->initialize($options);
  }

  public function getDefaultOptions()
  {
    return array(
      'override' => false,
      'create_associations' => true
    );
  }

  protected function initialize(array $options)
  {
    $this->configure($options);
  }

  public function execute(dmDoctrineRecord $record)
  {
    $this->record = $record;
    $this->table  = $record->getTable();

    if($this->table->hasI18n())
    {
      $this->record->getCurrentTranslation();
    }

//    $this->record->clearRelated();

    foreach($this->getLoremizableColumns() as $columnName => $column)
    {
      $this->loremizeColumn($columnName, $column);
    }

    if ($this->getOption('create_associations'))
    {
      $this->loremizeAssociations();
    }

    return $this->record;
  }

  protected function loremizeColumn($columnName, array $column)
  {
    if ($this->table->isI18nColumn($columnName))
    {
      $defaultValue = $this->table->getI18nTable()->getDefaultValueOf($columnName);
    }
    else
    {
      $defaultValue = $this->table->getDefaultValueOf($columnName);
    }

    /*
     * Non override on existing records
     * pass if columns value is different than its default value
     */
    if (!$this->getOption('override') && (!$this->record->isNew() || $this->record->get($columnName) !== $defaultValue))
    {
      return;
    }

    // skip auto-generated slug
    if ($columnName === 'slug' && $this->table->hasTemplate('Sluggable'))
    {
      return;
    }

    // skip i18n lang
    if ($columnName === 'lang' && $this->table->hasI18n())
    {
      return;
    }

    // if the field can be null, set it to null sometimes
    if (!dmArray::get($column, 'notnull') && !dmArray::get($column, 'unique') && !mt_rand(0, 3))
    {
      $val = null;
    }
    // handle local keys
    elseif ($localRelation = $this->table->getRelationHolder()->getLocalByColumnName($columnName))
    {
      $val = $this->getRandomId($localRelation->getTable());
    }
    // handle i18n local keys
    elseif ($this->table->hasI18n() && ($localRelation = $this->table->getI18nTable()->getRelationHolder()->getLocalByColumnName($columnName)))
    {
      $val = $this->getRandomId($localRelation->getTable());
    }
    else
    {
      $val = $this->getRandomValue($columnName, $column);
    }

    $this->record->set($columnName, $val);
  }

  protected function loremizeAssociations()
  {
    foreach($this->table->getRelationHolder()->getAssociations() as $relation)
    {
      $this->record->clearRelated($relation->getAlias());

      if (mt_rand(0, 4))
      {
        $ids = (array) dmDb::query($relation->getClass().' t')
        ->select('t.id, RANDOM() AS rand')
        ->orderBy('rand')
        ->limit(mt_rand(1, 6))
        ->fetchFlat();

        $this->record->link($relation->getAlias(), array_unique($ids));
      }
    }
  }

  protected function getLoremizableColumns()
  {
    return $this->table->getHumanColumns();
  }

  protected function getRandomValue($columnName, array $column)
  {
    $column['name'] = $columnName;

    switch($column['type'])
    {
      case 'string':
        $val = $this->getStringValForColumn($column);
        break;
      case 'boolean':
        if('is_active' === $columnName)
        {
          $val = (bool)mt_rand(0, 2);
        }
        else
        {
          $val = (bool)mt_rand(0, 1);
        }
        break;
      case 'blob':
      case 'clob':
        if ($this->table->isMarkdownColumn($columnName))
        {
          $val = dmLorem::getMarkdownLorem(1);
        }
        else
        {
          $val = dmLorem::getBigLorem();
        }
        break;
      case 'time':
      case 'timestamp':
      case 'date':
        $val = date("Y-m-d H:i:s", mt_rand(strtotime('-10 year') , time()));
        break;
      case 'year':
        $val = date("Y", mt_rand(strtotime('-10 year') , time()));
        break;
      case 'enum':
        $val = $column['values'][array_rand($column['values'])];
        break;
      case 'integer':
      case 'int':
        $val = mt_rand(0, pow(10, $column['length']) - 1);
        break;
      case 'float':
      case 'decimal':
        $val = mt_rand(0, pow(10, $column['length']) - 1)/pow(10, dmArray::get($column, 'scale', 2));
        break;
      default:
        throw new dmException(sprintf('Diem can not generate random content for %s column', $columnName));
    }

    return $val;
  }

  protected function getStringValForColumn($column)
  {
    if (dmArray::get($column, 'email'))
    {
      return dmString::random(mt_rand(4, 30)).'@localhost.com';
    }

    if ($this->table->isLinkColumn($column['name']))
    {
      return $this->getRandomLink();
    }

    if($column['length'] < 40)
    {
      $nbCarac = mt_rand(1, $column['length']);
    }
    else
    {
      $maxLen = $column['length'] > 80 ? $column['length'] / 2 : $column['length'];
      $nbCarac = mt_rand(min(4, $column['length']), max(40, $maxLen));
    }

    $val = trim(dmLorem::getLittleLorem($nbCarac));

    if (dmArray::get($column, 'unique'))
    {
      $val = substr(dmString::random(4).' '.$val, 0, $column['length']);
    }

    if (dmArray::get($column, 'nospace'))
    {
      $val = str_replace(' ', '-', $val);
    }

    return $val;
  }

  protected function getRandomLink()
  {
    if(mt_rand(0, 1))
    {
      return sprintf('http://'.dmString::random().'.random.com');
    }

    if(!class_exists('DmPageTranslation', false))
    {
      new DmPage();
    }

    $page = dmDb::query('DmPageTranslation p')
    ->select('p.id, p.name, p.lang, RANDOM() AS rand')
    ->where('p.lang = ?', dmDoctrineRecord::getDefaultCulture())
    ->orderBy('rand')
    ->limit(1)
    ->fetchPDO();

    return sprintf('page:%d %s', $page[0][0], $page[0][1]);
  }

  protected function getRandomId(dmDoctrineTable $table)
  {
    $id = $table->createQuery('t')
    ->select('t.id, RANDOM() AS rand')
    ->orderBy('rand')
    ->limit(1)
    ->fetchValue();

    if (!$id)
    {
      $recordLoremizer = new self($this->getOptions());
      $id = $recordLoremizer->execute($table->create())->saveGet()->get('id');
    }

    return $id;
  }
}

redpajama_set_name: RedPajamaGithub


Today Sony announced a rights management system using blockchain. The project is based on an existing system for authenticating, sharing and rights management of educational data.
The new initiative targets rights for written works. It logs the data and time of creation of the electronic data as well as the creator, making it hard to falsify. Similar implementations have been done in the past, ranging from proving that a press release came from a particular organization to Austria's verification of public documents such as bus timetables.
The aspect that is novel is Sony says that it will "automatically verify the rights generation of a piece of written works, which has conventionally proven difficult." Hence verification is not just the content as a whole but also any part of it. Usually, proof is logged on the blockchain by creating a hash or representation of the data. The announcement provides no detail about methodology. But if it uses the same process, then it implies that there could be many hashes each representing a sentence or paragraph.
Sony also stated that the system lends itself to rights management for other types of digital content. This includes textbooks, music, film, VR content, and e-books.
The project is a joint initiative between Sony Corp, Sony Music Entertainment and Sony Global Education. Sony Global Education may commercialize the service. And Sony stated it is exploring numerous other blockchain applications.
In China, Baidu launched a copyright protection blockchain for media, especially photography. Koch Industries is working on a blockchain-based intellectual property licensing platform. EY and Microsoft announced a royalties blockchain for games. And GoDaddy acquired a company that proves the use of trademarks.


Learning programs that focus solely on developing technical skills are a missed opportunity. Promote engagement and performance by developing competencies and behaviors that reflect your organization's cultural values. In this HCI Keynote video, David J. DeFilippo, Ed.D., Chief Learning Officer of Suffolk Construction, explains how this mid-sized construction company is using modern learning science to build a culturally aligned, highly skilled workforce as it expands.
Prevent early attrition and promote long term engagement with culturally immersive onboarding programs that reflect who you are as a company.
Use values and personality traits as the basis for selecting your next generation of leaders; technical skills are easier to teach than attitudes.
Integrate technology systems to give employees and managers visibility into learning opportunities.


Do you find yourself wishing for palm trees and fresh plucked fruit? Create your own tropical paradise in your very own kitchen with refreshing mists of lime, lemongrass, and grapefruit. Lively, balance, awareness.


Idaho is home to many talented individuals and award-winning agencies. The following is, by no means, a complete list of agencies in Idaho. It should, however, give you a feel for agencies in and around the state, and the types of services that they offer.
Should your shop be listed here? Feel free to contact us and let us know.


Katherine White, PhD joined the Psychology Department at the University of Waterloo in 2010, after completing her PhD in Cognitive Science at Brown University (Providence, Rhode Island, USA) and postdoctoral research in the department of Brain & Cognitive Sciences at the University of Rochester (Rochester, New York, USA). She studies the earliest stages of language development in infants and toddlers.
Dana completed her Bachelor of Science (Bsc) Honours in Psychology and MA in Psychology from the University of Manitoba. Her MA project examined infants' ability to hear speech directed at them in a noisy, multi-speaker environments.
Currently, she is in the PhD program investigating toddlers' and adults' ability to understand children's speech.
Her other interests include the development of vowels in bilingually exposed infants, and examining noise levels across child care environments using LENA.
 Emily Shiu completed her Bachelor of Arts (BA) in Psychology with a Japanese Certificate I from the University of Waterloo. Currently, she is in the Masters of Applied Science program. Her research interests include adult studies in bilingual language development - particularly in Cantonese-English bilinguals.
Ashley completed her Bachelor of Science Honours (BSc) at McMaster University in Psychology, Neuroscience and Behaviour. She is currently completing her Masters of Applied Science at Waterloo. She is interested in how audio-visual speech impacts speech perception and learning in infants.
Sarah is currently in her fourth year of a Bachelor of Arts in Honours Psychology with a minor in Social Development Studies. She is the Lab Coordinator for both the Lab for Infant Development and Language and the Developmental Learning Lab. Upon graduation, she hopes to pursue a Masters of Social Work degree.
Ashley is currently in her third year of a Bachelor of Science in Honours Kinesiology, with a minor in Psychology. She is the Community Testing Coordinator for both the Lab for Infant Development and Language and the Developmental Learning Lab. She hopes to continue working with child development and pursue a career in Pediatric Occupational Therapy.
Bronte Smith is in her fourth year of a Bachelor of Science in Psychology with a minor in Biology at University of Waterloo. After Graduation, she is interested in pursuing a career in Speech Language Pathology.
Phoebe is in her fourth year of Honours Psychology (BA). In the future she hopes to pursue graduate studies in Developmental Psychology.
Janey is in her final year of Bachelor of Arts (BA) in Psychology at the University of Waterloo. She is currently interested in research on visual-auditory associations in language-learning and hopes to continue her studies in developmental psychology.
Rebecca is completing her third year of a Bachelor of Arts in Honours Psychology with a Research Intensive Specialization. She has a history teaching ESL with children, which inspires her interest in language acquisition in infants. Assisting the LIDL research team is an essential part of her growth as an undergraduate student. She hopes to pursue graduate school in the stream of developmental psychology and eventually conduct research full-time.
Rachel is in her fourth year of Arts and Business, Honours Psychology (BA) at the University of Waterloo. She is currently researching children's imagination, as well as their beliefs about and processing of accented speech. She hopes to pursue graduate studies in either clinical or developmental psychology, and would love to continue working with children.
Shaneene recently completed her Bachelor of Arts in Psychology and German at the University of Waterloo. She hopes to pursue graduate studies in Developmental Psychology.
 Annika is currently in her fourth year of Honours Psychology (BA) with a minor in French. In the lab, she helps with a variety of lab duties as a research assistant. In addition, she is currently working on her honours thesis in our partnered lab, the Developmental Learning Lab, where she is looking at how infants use probability and physical reasoning. In the future, she plans to pursue graduate studies in developmental psychology.
Riley is currently in her final year of her undergraduate program. She is in Honours Psychology, and plans to pursue Speech-Language Pathology when she is finished her degree.
 Chloe is in her final year of her Health Sciences degree at Wilfrid Laurier University. She is very interested in the research process especially with language learning in children. In the future she hopes to pursue a career in nursing, with a focus in research.
Amy is in her fourth year of her Psychology degree with a minor in Human Resource Management. Amy is particularly interested in bilingualism in language development and hopes to pursue a career in Developmental Psychology or Human Resource Management.
Rachel is in her second-year psychology major with a minor in applied language studies and sexuality, marriage, and family studies. She hopes to pursue graduate studies in the future.


Skanska, Laing O'Rourke, Costain and Winvic are among contractors that will share a pot of government funding that aims to transform the construction industry through digital technology.
The firms are all part of four different projects to win funding under the £5m Research Leaders programme announced by UK Research & Innovation. The 24 winners of another £13.3m from UKRI to fund collaborative research and development projects has also been announced this week.
Cementation Foundations Skanska is a partner on a project led by University College London to develop an innovative scheme to develop robots to communicate and build structures together.
Laing O'Rourke and Aecom are part of a team led by the University of Bath's Automating Concrete Construction (ACORN) project looking at how to automate concrete construction.
And Costain and Winvic are supporting a project run by the University of West England that aims to integrate conversational artificial intelligence (AR) and augmented reality (AR) with BIM for faster onsite assembly.
A fourth scheme under Loughborough University's leadership is investigating the construction of building components using 3D concrete printing technology.
Bouygues is involved in Globalhom, a project aimed at increasing productivity and quality in mass housebuilding using connected, modular homes made from an interchangeable kit of parts.
Costain is supporting Gearbuddy, a programme designed to increase the productivity on site by 15% or more by using BIM, IoT and data analytics to increase plant and equipment utilisation.
Severfield has teamed up with the British Constructional Steelwork Association (BCSA), the Steel Construction Institute, Trimble and WSP to increase productivity through the use of integrated offsite steel modules.
And BAM Nuttall is working with Cranfield University and Iotic Labs on "The Learning Camera" project, which allows users to train a standard web camera attached to a ruggedised computer to recognise a scenario on site and send an alert if the content of that view changes, which it hopes can be applied to various different use cases on sites.
All of the funding provided within the two pots is part of the total £170m Transforming Construction Challenge, which aims to identify innovative new construction processes and techniques.
Announcing the awards as he visited offsite manufacturer Vision Modular, construction minister, Richard Harrington, said: "The use of artificial intelligence, digital techniques and offsite manufacturing, help us harness new methods of working. This delivers on the government's Construction Sector Deal which pledges to build better performing buildings, using less energy and providing better value for taxpayers.
A full list of the 24 collaborative R&D projects can be found here.


text:
Christian Frederik Emil Horneman (* 17. Dezember 1840 in Kopenhagen; † 8. Juni 1906 ebenda) war ein dänischer Komponist.

Leben
Der Sohn des Komponisten Johan Ole Emil Horneman studierte am Leipziger Konservatorium bei Ignaz Moscheles, Ernst Friedrich Richter, Moritz Hauptmann und Julius Rietz. Nach seiner Rückkehr nach Dänemark komponierte er Divertimenti und Opernfantasien, Orchesterstücke für die Aufführung im Tivoli, ein Streichquartett und 1863 die Oper Aladdin.

Mit Gottfred Matthison-Hansen und anderen gründete er 1865 das Konzertinstitut Euterpe, dessen Konzerte er dirigierte. Während einer Deutschlandreise 1867 komponierte er in München die Ouverture heroique und führte bei einem Gewandhaus-Konzert in Leipzig die Aladdin-Ouvertüre auf.

1874 gründete er mit Otto Malling die Koncertforeningen, deren Konzerte beide abwechselnd dirigierten, 1879 das Konservatorium von Kopenhagen, das heute seinen Namen trägt. Daneben entstanden für das Dagmartheatret mehrere Schauspielmusiken, darunter zu Holger Drachmanns Esther und Frederik Paludan-Müllers Kalanus, und die Kantate In memoriam Christian IX.

Literatur
 Yvonne Wasserloos: Kulturgezeiten. Niels W. Gade und C.F.E. Horneman in Leipzig und Kopenhagen. (Zugleich Dissertation, Münster 2002). Hildesheim, Zürich u. New York 2004.
 Yvonne Wasserloos: Kopenhagen, ein Leipzig an der Ostsee? Das musikpädagogische Schaffen Niels W. Gades und C.F.E. Hornemans. In: Lorenz Luyken, Stefan Weiss (Hrsg.): Professionelle Musikausbildung und Internationalität. Hannover 2006 (= Monographien des Instituts für Musikpädagogische Forschung der Hochschule für Musik und Theater Hannover 16), S. 46–80.
 Yvonne Wasserloos: Wider "alte Schnecken von anno Tobak". Edvard Grieg, C.F.E. Horneman und die Euterpe. In: Die Tonkunst, 1 (2007), S. 268–279.
 Yvonne Wasserloos: Die Dänen in Leipzig. Formen des Kulturtransfers im 19. Jahrhundert. In: Stefan Keym, Katrin Stöck (Ed.): Musik in Leipzig, Wien und anderen Städten im 19. und 20. Jahrhundert: Verlage – Konservatorien – Salons – Vereine – Konzerte. Leipzig 2011 (= Musik – Stadt. Traditionen und Perspektiven urbaner Musikkulturen. Bericht über den XIV. Internationalen Kongress der Gesellschaft für Musikforschung in Leipzig 2008) Bd. 3, S. 165–181.

Weblinks

 Yvonne Wasserloos: Christian Frederik Emil Horneman (1840–1906). Europäische Geschichte Online, hrsg. vom Institut für Europäische Geschichte (Mainz), 3. Dezember 2010.

Komponist (Dänemark)
Däne
Geboren 1840
Gestorben 1906
Mann

redpajama_set_name: RedPajamaWikipedia


Most Georgia public school students don't master reading early enough to give them a strong chance of success the rest of their school careers, a trend that has so alarmed superintendents, CEOs and even former military leaders that they are calling it a threat to the state's economy and even to national security.
Students are taking the Georgia Milestones tests right now, and last year around this time, as in the years before, nearly two out of three third-graders — close to 90,000 students — failed the English test that includes reading, a crucial skill for learning other subjects in fourth grade and beyond. Research shows that as many as one in six who can't read proficiently by third grade either drop out or won't graduate on time. A poor education leads to low pay, a rocky work life and maybe even prison.
There is a growing movement to fix the problem by starting more kids earlier in school, but it hasn't become a top political issue. Only the two Democratic candidates for governor are talking about the idea.
Long-running studies indicate that schooling from birth through age 3, when the brain is growing fastest, can yield enduring academic, career and even health benefits, especially for children from low-income homes. But it must be high-quality, and it's unlikely even Georgia, a leader in pre-K, can muster the resources to reproduce at scale the kind of life-altering interventions found in successful small programs, though advocates say any inclusion of more babies and toddlers would help.
The cost of providing an earlier education to all who need it would be considerable. The Pre-K program serves 84,000 Georgia children, about 60 percent of the state's 4-year-olds, at a cost of nearly $370 million a year. There are about a half million Georgia children under age 4, and experts say it's more expensive to serve them since they need more attention.
This election aside, there is a history in Georgia of bipartisan collaboration on educating kids before kindergarten. Democrats and Republicans worked together to develop a highly-regarded pre-K program open to all. It was founded a quarter century ago by then-Gov. Zell Miller, a Democrat, and later embraced by Gov. Nathan Deal, a Republican, who increased the lottery-funded budget by $11 million and raised teacher pay. Deal and other Republican leaders, including U.S. Sen. Johnny Isakson, have also increased the state and federal tax dollars, now more than $200 million, that help the low-income working parents of 54,000 children afford preschool and other child care. Deal also developed a quality-rating system to help parents choose a child care program.


text:
\section{Conclusions and Future Research}
\noindent In the Competition setting, we showed the impact of competition on optimal prices, quantities, and capacity under two scenarios: Exogenous Model and Endogenous Model. Under the Exogenous model, we showed the impact of the foreign manufacturer price on local sales and the firm's decision to enter the foreign
market. As the foreign manufacturer's price increases, it becomes more appealing for the firm to enter the foreign manufacturer, sales at home country decreases, and the optimal capacity increases. Also, as exchange rate volatility increases, optimal capacity decreases.

Under the Endogenous Model, where capacity is ample, it becomes attractive to export to the foreign market when "cross-price", cost per unit for the foreign manufacturer, potential demand at the foreign country, and consumer sensitivity for the foreign price increases. We presented exchange rate thresholds when the firm generate more money than the foreign manufacturer, and when the prices at the foreign country are identical. Also, we showed that high cost per unit for the foreign manufacturer makes the firm the only player at the foreign market. When capacity is ample, sales at the home market stays constant. However, when capacity is limited, the firm must allocate its capacity properly between the two markets to attain optimal profit. We drove exchange rate thresholds where: the firm split capacity between the two markets, sell only to home market, and sell only to foreign market. We showed that an increase in the drift of exchange rate, potential demand, and "cross-price" increase optimal capacity. On the other hand, an increase in consumer price sensitivity, and exchange rate volatility decreases optimal capacity.

In future study, The future work is to make demand uncertain. Also, using different demand functions such as Cobb-Douglas function (see Gallego and Hu (2006)), the CES function (see Varian (1992)), or the Transcendental Logarithmic (translog) function (see Christensen et al. (1973)). In addition to exchange rate, we also aim to integrate the impact of after-tax profit calculations and tariffs into our analysis.

\section{The Duopoly  Model}

In this section, we are assuming that both firms make their prices simultaneously at the incumbent's market. We consider two scenarios, 1) both firms has ample (unlimited) capacities,  and 2) the entrant has limited capacity and the incumbent manufacturer has unlimited capacity. We will derive the Nash equilibrium (optimal prices and quantities) for each manufacturer and show the impact of exchange rate and competition parameters on the manufacturer's capacity allocations.

The entrant manufacturer's objective function is given by
\begin{equation}
\max_{P_{ei}, \, P_{ee} \geq 0}\Pi_{e}=\left(P_{ee} -C_e\right) \left(\alpha_{e} -   P_{ee} \right)+\left(I P_{ei} - C_e - s \right) \left( (1-\phi) \alpha_{i}- P_{ei}+ \theta P_{ii} \right)   \label{entrant profit function}
\end{equation}
\begin{equation}
s.t.\,\, Q_{ee} + Q_{ei} \leq K  \ ,  \label{constraint condition 1}
\end{equation}
where,
\begin{equation*}
Q_{ee} = \alpha_{e} - P_{ee}  \tag*{$(4.1a)$} \,\,\, \text{and} \,\,\, Q_{ei} = (1-\phi) \alpha_{i}- P_{ei}+ \theta P_{ii} \ .
\end{equation*}
The incumbent manufacturer's optimization problem is given by:
\begin{equation}
\max_{P_{ii} \geq 0} \Pi_{i}=\left(P_{ii}- C_i\right)\left( \phi \alpha_{i} -  P_{ii} +\theta P_{ei}\right) \ .  \label{incumbent profit function}
\end{equation}

\subsection{Entrant Manufacturer with Unlimited Capacity}

When the entrant's capacity is unlimited, then constraint condition give in (\ref{constraint condition 1}) is relaxed. The entrant manufacturer will set its prices according to the objective function given in (\ref{entrant profit function}).  Solving the problem with respect to $P_{ei}$ and $ P_{ee}$, we get:
\begin{equation}
P^{u}_{ei}(P^{u}_{ii}) =  \frac{(C_e + s) + I ((1-\phi) \alpha_{i} +\theta   P^{u}_{ii})}{2 I} \label{entrant price incumbent un}
\end{equation}
\begin{equation}
P^{u}_{ee} (P^{u}_{ii}) = \frac{\alpha_{e}+ C_e}{2} \label{entrant price own un}
\end{equation}
The incumbent manufacturer will set its prices according to the objective function given in (\ref{incumbent profit function}) and
we can get
\begin{equation}
P^{u}_{ii} (P^{u}_{ei}) = \frac{\phi \alpha_{i}+ C_{i}+\theta  P^{u}_{ei}}{2} \ . \label{incumbent price un}
\end{equation}
Simultaneously solving (\ref{entrant price own un}), (\ref{entrant price incumbent un}), and (\ref{incumbent price un}) for $P^{u}_{ee}$, $P^{u}_{ei}$, and $P^{u}_{ii}$, we can get the equilibrium outcomes of $P^{u}_{ee}$, $P^{u}_{ei}$, and $P^{u}_{ii}$ and hence other equilibrium results given in the Appendix.

Substituting $P^{u}_{ee}$ into
$ D_{ee}=  \alpha_{e} - P^{u}_{ee}  $, we can get the optimal quantities the entrant manufacturer will sell in its own market:
\begin{equation}
Q^{u}_{ee} = \frac{\alpha_{e} -  C_{e}}{2}  = K_Q \ . \label{entrant quantity own unlimited}
\end{equation}
Substituting $P^{u}_{ei}$ and $P^{u}_{ii}$ into $
D_{ei}= (1-\phi) \alpha_{i} -  P_{ei}+\theta P_{ii}
$, we can get  the optimal quantities the entrant manufacturer will sell in the incumbent market as:
\begin{equation}
Q^{u}_{ei} = \frac{ I (\alpha_i ( 2  -2  \phi+\theta  \phi )+ C_{i} \theta )  - (C_e+s) (2 -\theta ^2)}{I \left(4  - \theta ^2 \right)} \label{entrant quantity incumbent unlimited}
\end{equation}

\noindent \MakeUppercase{L{\small emma }}4.1: {The firm will export to foreign market if
\begin{equation}
I > \frac{(C_e + s) \left(2 -\theta ^2\right)} {\alpha_i ( 2  -2  \phi+\theta  \phi )+ C_{i} \theta} = I_{z}  \label{iz}
\end{equation} Otherwise, the firm will sell only to domestic market.
}

Equation (\ref{entrant quantity incumbent unlimited})  and  (\ref{iz})  show that it is more attractive to enter into the incumbent's market  as  $C_i$ and $\alpha_{i}$ increase. That is, if the market potential or the production cost of the incumbent market is high, then the entrant manufacturer has more incentive to export their products into the incumbent's market. This result can explain why there are so many manufacturers are pouring their products into the U.S. market since the potential demand in the U.S. is very big and the production cost (including the labor cost) is also very high. \\

If the exchange rate $I(t)$ is low, i.e.,  $ I < I_{z} $, then even the entrant manufacturer has unlimited capacity, it will still not enter into the incumbent's market. Therefore, the entrant manufacturer will sell only to it's own domestic market with profit given by:
\begin{equation}
\Pi^{EU}_{e} = \frac{(\alpha_e -  C_{e})^2}{4} \ . \label{entrant home profit unlimited}
\end{equation}
Here we slightly abuse the notation by using "$EU$" as the case of "manufacturer selling only to the entrant's own market with unlimited capacity".
When the exchange rate is enough high, i.e.,  $ I >I_{z}$,  then the entrant manufacturer can export to the incumbent market and compete with the incumbent manufacturer. Substituting $P^{u}_{ei}$ and $P^{u}_{ii}$ into the entrant's objective function, we can get the entrant's profit:
\begin{equation}
\Pi^{BU}_{e} = \frac{(\alpha_e - C_{e})^2}{4}+\frac{ \left(I (\alpha_i ( 2  -2  \phi+\theta  \phi )+ C_{i} \theta )  - (C_e+s) (2 -\theta ^2) \right)^2}{I \left(4 - \theta ^2 \right)^2} \label{entrant profit unlimited}
\end{equation}
Here we use the notation by using "$Ub$" as the case of "selling in both market with unlimited capacity".  We can see from equation (\ref{entrant profit unlimited}) that  the profit generated from entrant's own market is independent of the price competition in the incumbent's  market and the exchange rate when entrant's capacity is unlimited. The second term is the profit generated from the sales at the incumbent's market and this profit is zero if the exchange rate falls below the threshold value $ I_{z}$. \\

Substituting $P^{u}_{ei}$ and $P^{u}_{ii}$ into the incumbent's objective function, we can get the incumbent's profit function as:
\begin{equation}
\Pi^{u}_i =\left(\frac{\theta  (C_{e}+s) - I (C_{i}(2-\theta ^2) - \alpha_{i} (2-\theta ) \phi -\alpha_{i} \theta )}{(4 - \theta^2) I}\right)^2 \ .
\end{equation}

\noindent \MakeUppercase{C{\small orollary }} 1: {\it The profit for the incumbent firm is monotonically decreasing in the exchange rate when the entrant manufacturer has unlimited capacity.}

This corollary shows how the entrant can benefit from higher exchange rate and as a result, we can derives the next lemma. \\

\noindent \MakeUppercase{L{\small emma }}4.2: {The incumbent manufacturer can not make sales if
\begin{equation}
I > \frac{\theta  (C_e + s)}{C_{i} \left(2 - \theta^2) - \alpha_{i} (\theta  (1- \phi ) + 2  \phi )  \right)}  = I_v   \label{I v unlimited}
\end{equation}
where
\begin{equation}
C_i > \frac{\alpha_{i} (\theta  (1- \phi ) + 2  \phi )}{2 - \theta^2}  = C_v   \label{C v unlimited}
\end{equation}
if $ C_i < C_v$, then the entrant can not force the incumbent manufacturer out of the game. }

The above lemma shows that if the exchange rate is above a certain thresholds, $I_v$, then the incumbent manufacturer will be forced out of its own market by the entrant manufacturer  if and only if $C_i > C_v$. Intuitivley, if the production cost of the incumbent is not too high then it is not possible that the entrant could drive the incumbent market out of the market if the exchange rate satisifies $I  > I_v$.

\subsection{Entrant Manufacturer with Limited Capacity}

The entrant manufacturer and incumbent face the same objective functions as the case in the unlimited capacity. However, with limited capapcity, the constrait condition (\ref{constraint condition 1}) will be activated.

The entrant manufacturer will set its prices according to the objective function given in (\ref{entrant profit function}).  Using Lagrange relaxation and solving the problem with respect to $P_{ei}$ and $ P_{ee}$, we get:
\begin{equation}
P_{ee}(P_{ii}) = \frac{ I (2 \alpha_{e} +\alpha_{i} - \alpha_{i} \phi  -2 K+ \theta  P_{ii}) + ( \alpha_{e}-  s)}{2  (1 + I)}  \label{entrant price own}
\end{equation}
and
\begin{equation}
P_{ei}(P_{ii}) = \frac{ I  (\alpha_{i} -\alpha_{i} \phi +\theta  P_{ii} ) +   (\alpha_{e} + 2 \alpha_{i} (1-\phi) - 2 K + 2 \theta  P_{ii} +\beta_{ee} s)}{2  (1 + I)} \ . \label{entrant price incumbent}
\end{equation}
The incumbent manufacturer will set its prices according to the objective function given in (\ref{incumbent profit function}) and we can get:
\begin{equation}
P_{ii}(P_{ei}) = \frac{ \phi \alpha_{e} +  C_{i}+\theta  P_{ei}}{2} \ . \label{incumbent price}
\end{equation}
Simultaneously solving (\ref{entrant price own}), (\ref{entrant price incumbent}), and (\ref{incumbent price}) for $P_{ee}$, $P_{ei}$, and $P_{ii}$, we can get the equilibrium prices of $P^{*}_{ee}(K)$, $P^{*}_{ei}(K)$, and $P^{*}_{ii}(K)$,  equilibrium quantity of $Q^{*}_{ee}(K)$, $Q^{*}_{ei}(K)$, and $Q^{*}_{ii}(K)$, and hence both players' profit $\Pi^{*}_{e}(K)$, $\Pi^{*}_{i}(K)$.
In equilibrium, the entrant manufacturer's profit can be given as:
\begin{equation}
\Pi_{e}^{BC}(K)=\left(P^{*}_{ee}(K) -C_e\right) \left(\alpha_{e} -  P^{*}_{ee}(K) \right)+\left(I P^{*}_{ei}(K) - C_e - s \right) \left( (1-\phi) \alpha_{i}-  P^{*}_{ei}(K)+ \theta P^{*}_{ii}(K) \right)
\end{equation}
Here, we use the notation "BC" as the entrant selling in both markets with limited capacity. \\

\noindent \MakeUppercase{P{\small roposition}} 4.1: {The firm's capacity is fully utilized if and only if }
\begin{equation}
I \geq \frac{2 (C_{e} + s) (2 -\theta^2)}{ 4 \alpha_{i} - 2 \alpha_{i} (2- \theta) \phi + 2 C_{i} \theta + (4 - \theta ^2) (\alpha_{e} - C_{e} -2 k)} = I_{t}      \label{It}
\end{equation}

\noindent or
\begin{equation}
K < \frac{4 \alpha_{i} - 2 \alpha_{i} (2- \theta) \phi + 2 C_{i} \theta + (4 - \theta ^2) (\alpha_{e} - C_{e})}{2 \left(4 -\theta^2 \right)} = K_{t} \label{Kt}
\end{equation}

\noindent Otherwise, the firm will sell constrained optimal.

The above proposition shows that the entrant can implement the unconstrained solution and hence does not need to split her capacity across markets if $I(t) < I_{t}$. In contrast, if the inequality in (\ref{It}) does not hold then the capacity is limited. As such, the entrant faces the problem of allocating the capacity between the two markets. Depending on the market potentials and the realized exchange rates the entrant may also choose to sell only in one of the markets. The next proposition indicates that if the exchange rate is significantly high, the entrant manufacturer in fact may opt out of its own market. \\

\noindent \MakeUppercase{P{\small roposition}} 4.2: {In equilibrium, (a) the entrant manufacturer chooses to sell in the domestic market if and only if
\begin{equation}
I < \frac{ (2 - \theta ^2) (\alpha_{e} +  s)}{  (\alpha_{e} (2  (1-\phi) + \theta  \phi )+  C_{i} \theta ) - K \left(4 - \theta ^2\right)} = I_{h}   \label{Ih2}
\end{equation}
otherwise, the firm sells only in the foreign market; (b)  entrant manufacturer will export its product to the incumbent manufacturer's market if and only if
\begin{equation}
I > \frac{(2 - \theta ^2) (\alpha_{e}+ s - 2 K)}{ \alpha_{i} (\theta  \phi + 2 (1-\phi))+ C_{i} \theta } = I_{f}  \label{If2}
\end{equation}
That is, the entrant splits the capacity between the domestic and foreign markets only when $I_{f}<I(t)<I_{h}$. }

Note that from (\ref{Ih2})  the entrant manufacturer will always sell to the domestic market (its own market) if
\begin{equation}
K \geq \frac{ \alpha_{i} (\theta  \phi + 2 (1 - \phi))+ C_{i} \theta}{4  - \theta ^2} = K_{h} \ .
\end{equation}
When the capacity is unlimited, it is always profitable to sell in the entrant's own market. However when capacity is scarce, as the foreign exchange rate increases, it becomes less appealing to allocate capacity to its own market.

Proposition 4.2 also shows how competition can increase the appeal to enter the foreign market especially when cost of production ($C_i$),  potential demand alpha ($\alpha_i$) for the incumbent manufacturer, and cross price effect ($\theta$) increase. Proposition 4.2 implies that the optimal policy for the entrant manufacturer at any given period is a ``cherry-picking'' policy when the capacity is scarce. That is, when the exchange rate is significantly high the entrant manufacturer sells only in the incumbent market whereas when it is too low she will sell exclusively in the domestic market. For exchange rates is not too high or too low, the capacity is split between the two markets. \\

\noindent \MakeUppercase{L{\small emma }} 4.3: (a) When the entrant manufacturer with limited capacity  sells only in its own market, the entrant's profit is given by
\begin{equation}
\Pi_e^{EC} = (\alpha_{e} -  C_{e} - K) K \ ;
\end{equation}
(b) when the entrant manufacturer with limited capacity  sells only in the incumbent's market, the entrant's profit is given by
\begin{equation}
\Pi_e^{IC} = \frac{[I (2 \alpha_{i}  (1- \phi) + \alpha_{i} \theta  \phi +  C_{i} \theta -2  K) - (C_{e}+s) ( 2 - \theta ^2 ) ] K}{2 -\theta ^2} \ .
\end{equation}
\noindent \MakeUppercase{L{\small emma }} 4.4: The entrant manufacturer's profit function $\Pi^{IC}_{e}(K)$, $\Pi^{BC}_{e}(K)$,  $\Pi^{EC}_{e}(K)$ are concave functions of its capacity $K$.

\noindent \MakeUppercase{L{\small emma }} 4.5: If $\alpha_{e} >  \frac{\alpha_i (2(1-\phi) + \theta \phi) + C_{i} \theta }{4 - \theta ^2} +C_e $ then the entrant manufacturer will always be willing to sell in its own market.

This lemma shows that when the entrant manufacturer's market size is higher than some threshold value then the entrant will never give up its market.

\subsection{The Endogenous Model Optimal Capacity}

\noindent \MakeUppercase{L{\small emma }} 4.6:  Define $K_{Q} = \frac{(\alpha_{e} -  C_{e})}{2} $. (1) If $K_Q < K_{h} < k_{t}$ then $I_{h}>I_{f}$ on $[0, K_Q]$; $I_{h}>I_{f} > I_z $ on $[K_Q, K_h]$; and $I_{t}>I_{z}$ on $[K_h, K_t]$; (2) If $K_{h} < K_Q < k_{t}$ then $I_{h}>I_{f}$ on $[0, K_h]$;  $I_{t}>I_{z}$ on $[K_Q, K_t]$.  \\

\subsubsection{$K_Q < K_{h} < k_{t}$}
Based on Proposition 4.2 and Lemma 4.6, we conclude that at the beginning of the planning horizon the optimal pricing and allocation policy falls in one of the following five scenarios:

\noindent EU:  The capacity is unlimited (unconstrained) and the entrant manufacturer sells only in its own market. \\
BU:  The capacity is  unlimited (unconstrained) and the entrant manufacturer sells in both markets. \\
EC:  The capacity is limited and the entrant manufacturer allocates all of its capacity to its own domestic market.\\
IC:  The capacity is limited and the entrant manufacturer allocates all of its capacity to the incumbent market.\\
BC:  The capacity is limited and the entrant manufacturer allocates all of its capacity between the two markets. \\

\begin{figure}[ht]
\begin{center}
  \includegraphics[scale=0.5]{figure2_regions.pdf} \\
  \caption{Regions}
\label{five regions}
\end{center}
\end{figure}

First we note that when capacity is unlimited, i.e., $K \geq K_{t}$, there is always incentive for the entrant manufacturer to sell in its own domestic market. From Lemma 4.1, the entrant manufacturer sells in the incumbent market in the beginning of the planning horizon if the exchange rate is above the threshold given in (\ref{iz}). In case of limited capacity, any one of the three scenarios (home only, foreign only or split capacity) may occur depending on the exchange rate as shown in Proposition 4.2.

Suppose that capacity is very limited (high-cost case), that is, lower than $K_{Q} $. This situation is more likely to happen when the cost of capacity is too high that the entrant manufacturer cannot fully satisfy the demand in the domestic market alone. In this case, the capacity is fully utilized. As shown in Figure \ref{five regions}, the entrant manufacturer allocates all of its capacity to its own market (EC) if the exchange rate is below $I_{f}$. In this case the low exchange rate prohibit the manufacturer from exporting to the incumbent market. The entrant manufacturer  chooses to allocate the capacity between the two markets (BC) if the exchange rate $I(t)$ falls between $I_{h}\,$ and $I_{f}$.
If the exchange rate is too high, i.e., $ I(t) > I_{h}$,  the entrant manufacturer will allocate all the limited capacity to the incumbent's market (IC).

Under this scenario ex-ante expected profit function before the start of the selling season can be written as follows:
\begin{equation}
\max_{K}: \Pi_{e} (k) = - u  K + \int_0^{I_{f}}\Pi_e^{EC}A(I)dI +\int_{I_{f}}^{I_{h}}\Pi_e^{BC}A(I)dI+\int_{I_{h}}^{\infty}\Pi_e^{IC}A(I)dI
\label{capacity decision 1}
\end{equation}
Where:
\begin{equation*}
\Pi_e^{EC} = (\alpha_{e} -  C_{e} - K) K \,
\end{equation*}
\begin{equation*}
\Pi_{e}^{BC}(K)=\left(P^{*}_{ee}(K) -C_e\right) \left(\alpha_{e} -  P^{*}_{ee}(K) \right)+\left(I P^{*}_{ei}(K) - C_e - s \right) \left( (1-\phi) \alpha_{i}-  P^{*}_{ei}(K)+ \theta P^{*}_{ii}(K) \right)  \,
\end{equation*}
\begin{equation*}
\Pi_e^{IC} = \frac{[I (2 \alpha_{i}  (1- \phi) + \alpha_{i} \theta  \phi +  C_{i} \theta -2  K) - (C_{e}+s) ( 2 - \theta ^2 ) ] K}{2 -\theta ^2} \ .
\end{equation*}
To find the optimal capacity, we need to take the derivative of (\ref{capacity decision 1}) with respect to $ K $:
\begin{equation*}
\frac{d\Pi_{e} (k)}{dK}=-u +\int_0^{\frac{I_{f}}{I_o}}  (\alpha_{e} -  C_{e} - 2 K)  f(\epsilon)d\epsilon + \int_{
\frac{I_f}{I_o}}^{\frac{I_{h}}{I_o}}\lambda f(\epsilon)d\epsilon
\end{equation*}
\begin{equation}
\hspace{5cm} + \int_{\frac{I_{h}}{I_o}}^\infty[\frac{I (2 \alpha_{i}  (1- \phi) + \alpha_{i} \theta  \phi +  C_{i} \theta -4  K)  }{2 -\theta ^2}  - C_{e}+s] f(\epsilon)d\epsilon =0 \label{capacity decision 1d}
\end{equation}
where $\lambda$ is the Lagrangian multiplier defined in (5.21). It is straightforward to see from the function above that the second derivative with respect to $K$ is strictly negative for any $K \geq 0$ implying concavity. Hence solution to (\ref{capacity decision 1d}) gives the unique optimal value for the capacity to be built at home in advance of the selling season. Unfortunately, there is no close form solution. However, the optimal capacity can be calculated easily with a simple line search.

Recall that the condition given in (\ref{capacity decision 1d}) applies when the capacity scarce. This is expected to occur when capacity is very expensive. Suppose that capacity is bigger than $K_{Q}$ then capacity allocation decision according to the following four regions as shown in Figure \ref{five regions} :

(1) if the spot exchange rate is below $I_{z}$, then the manufacturer satisfies all the demand in its own market and stays out of the incumbent market.

(2) if the spot exchange rate falls between $I_{z}$ and $I_{t}$, then the manufacturer satisfies all demand in both markets.

(3) if the spot exchange rate falls between $I_{t}$ and $I_{h}$, then the manufacturer splits its limited capacity between the two markets.

(4) if the spot exchange rate is higher than $I_{h}$, then the manufacturer allocates all the capacity to the incumbent market.

Consequently, the manufacturer's profit function in this case can be written as:
\begin{equation}
\max_{K}: \Pi_{e} (k) = - u  K + \int_0^{I_{z}}\Pi_e^{EU}A(I)dI+ \int_{I_{z}}^{I_{t}}\Pi_e^{BU}A(I)dI +\int_{I_{t}}^{I_{h}}\Pi_e^{BC}A(I)dI+\int_{I_{h}}^{\infty}\Pi_e^{IC}A(I)dI
\label{capacity decision 2}
\end{equation}
In order to find the optimal capacity, we need to take the derivative of equation (\ref{capacity decision 2}) with respect to $K$ and we get:
\begin{equation}
\frac{d\Pi_{e} (k)}{dK}= -u +  \int_{
\frac{I_f}{I_o}}^{\frac{I_{h}}{I_o}}\lambda f(\epsilon)d\epsilon+
\int_{\frac{I_{h}}{I_o}}^\infty[\frac{I (2 \alpha_{i}  (1- \phi) + \alpha_{i} \theta  \phi +  C_{i} \theta -4  K) }{2 -\theta ^2}  - C_{e}+s] f(\epsilon)d\epsilon =0 \label{capacity decision 2d}
\end{equation}

Suppose that capacity falls between $K_{h}$ and $K_{t}$ where the firm will always satisfy demand at home market. The capacity allocation decision is based on  the following four regions as shown in Figure \ref{five regions} :

(1) if the spot exchange rate is below $I_{z}$, then the manufacturer satisfies all the demand in its own market and stays out of the incumbent market.

(2) if the spot exchange rate falls between $I_{z}$ and $I_{t}$, then the manufacturer satisfies all demand in both markets.

(3) if the spot exchange rate is higher than $I_{h}$, then the manufacturer splits its limited capacity between the two markets.

Therefore,  the manufacturer's profit function in this case can be written as
\begin{equation}
\max_{K}: \Pi_{e} (k) = - u  K + \int_0^{I_{z}}\Pi_e^{EU}A(I)dI+ \int_{I_{z}}^{I_{t}}\Pi_e^{BU}A(I)dI +\int_{I_{t}}^{I_{h}}\Pi_e^{BC}A(I)dI
\label{capacity decision 3}
\end{equation}
In order to find the optimal capacity, we need to take the derivative of equation (\ref{capacity decision 3}) with respect to $K$ and we can get:
\begin{equation}
\frac{d\Pi_{e} (k)}{dK}= -u +  \int_{
\frac{I_f}{I_o}}^{\frac{I_{h}}{I_o}}\lambda f(\epsilon)d\epsilon \ . \label{capacity decision 3d}
\end{equation}

Although we cannot find closed form solutions for (\ref{capacity decision 1d}), (\ref{capacity decision 2d}), and (\ref{capacity decision 3d}) we can derive the following conclusions from the property of concavity. \\

\noindent \MakeUppercase{P{\small roposition }} 5.3:  {There exit two capacity cost thresholds $u^{t1}$ and $u^{t2}$ such that $u^{t1}$>$u^{t2}$.  if $u >u^{t1}$, then $K^{^{\ast}}$ will be obtained from (\ref{capacity decision 1d}), if $u_l^{t2}>u_l>u_l^{t1}$, then $K^{^{\ast}}$will be obtained from (\ref{capacity decision 2d}), and if $u^{t2}_l>u_l$, then $K^{^{\ast}}$will be obtained from (\ref{capacity decision 3d}). }

The above proposition shows that when capcity cost is expensive, then the optimal capacity falls between $0$ and $k_{Q}$. However, as capacity cost gets cheaper, then optimal capacity falls between $K_{h}$ and $K_{Q}$, otherwise, the optimal capacity falls between $K_{h}$ and $K_{t}$. \\

\begin{figure}[ht]
\begin{center}
  \includegraphics[scale=0.5]{figure3_regions.pdf} \\
  \caption{Regions II}
\label{five regions II}
\end{center}
\end{figure}

\section{Introduction}
\linespread{1.5}\selectfont

\normalsize{Exchange rate is one of the important key decisions for a multinational manufacturer to introduce its products to international markets in order to increase its wealth and gain markets share. During the past 20 years, firms are expanding their product and services to foreign market, Lowe et al. (2002). Therefore, if the manufacturer made a decision to enter the foreign market, based on the realization of a favorable exchange rate, it must coordinate its supply chains (supply/manufacture/distribute) properly to maximize its net profit. To achieve this goal, the manufacture has to allocate its capacity properly and flex its prices accordingly. Unfavorable exchange rate will force the manufacturer to not enter the international markets, financial losses due to poor foreign currency exchange. For example, a British company called Lakers Airlines offered low cost tickets for the masses (Jet Blue is an example of current companies that uses their technique) and it was successful, however the company collapsed in 1982 because of the exchange rate. The demand was high and the company was paying for aircraft in strong dollar and earning their profit in weak sterling (Anderson 1997). }

Mainly in this paper, the manufacturer produce its product in the home country and sales occur in both markets, however we will consider the case when the manufacture invests capacity in the foreign country and this capacity will be dedicated only to the foreign demand. The goal of the manufacture is to maximize its net profit which is equal to the difference between discounted expected profit from sales and capacity cost investment.

In this paper, we consider capacity as all the resource available for the manufacture to produce, such resources are technology, funds, man power, logistics, raw materials, and offices. By using multi-period setting, price sensitive demand, and modeling the exchange rate as a Geometric Brownian Motion, we investigate the effect of exchange rate parameters, specifically drift, volatility, and initial exchange rate, on capacity allocation and prices in the two scenarios. Also, we show the cases: when it's optimal for the global manufacturer to serve both markets, deny service to one market, and invest capacity in the foreign market. Finally, we show the effect of the planing horizon on optimal capacity, and investing capacity at the foreign market.

This paper is organized as follows. In the preceding section, we present the literature review. In section 3, we present our basic settings, assumptions, and nomenclature. In section 4, we present the Early Commitment to Price and Quantity Model where the manufacturer commits to prices and quantities at the beginning of the planning horizon. In section 5, we present the Postponement of Prices and Quantities Model where the manufacturer flexes its prices and quantities from period to period. For each model we discuses the allocation scenarios under capacity investment at home and in both countries. In section 6, we will have a summary and conclusion.

\section{Literature Review}
\linespread{1.5}\selectfont

\normalsize{Multinational firms are facing daily challenges such as demand volatility, governmental regulations, distribution constraints, and exchange rate uncertainties. The area if this proposal is to tackle the exchange rate uncertainties. Exchange rate fluctuations from 1\% a day to 20 \% a year is common and this changes could affect capacity and cost, Dornier (1998), which will ultimately affect profit. For a global firm to continue operating internationally and stay in business, the firm must be flexible and proactive in responding to uncertain shocks in exchange rate movements and adjust its operations based on unexpected movement by exchange rate. Therefore, multinational firms incorporate multiple risk-management techniques to handle exchange rate uncertainty. }

Two types of techniques have been developed by researches to tackle such a challenge: financial hedging and operational hedging. The multinational firm has to apply one of the two methods or combine both methods, an e.g. of combining both strategies done by Ding, Dong, and Kouvelis (2007), to gain market share and increase the firm's wealth and prosperity. Before operational hedging, there was financial hedging where the multinational firms buy option contracts; an example of financial hedging is currency option: a contract that grants the multinational firm the right to buy or sell currency at a specified exchange rate during a specified period of time. The multinational firm can opt out of the contract if the future exchange rate is not favorable. According to O'Brien (1996), currency option is used regularly by firms to protect itself against exchange rate volatility. Another example that used frequently is forward exchange contract: an agreement between two parties to exchange a specified amount of one currency for another currency at a specified foreign exchange rate on a future date. Another advantage of using this method, besides hedging against hedging against unfavorable exchange rate fluctuations, is cost and budget are accurate. However, there are critical disadvantages that could hit the firm with financial losses. Huchzermeier and Cohen (1996) assert that the firm could loss profit because the firm will not catch in the upside of exchange rate volatility and it could be risky for a firm to enter foreign market. They also mentioned that if the firm is not hitting the targeting sales and the exchange rate is weak, then the result of implementing the forward contract will be financial loss for the multinational firm. Any cancellation of the contract will result in a financial loss for the multinational firm.

This work focuses on operational hedging; where we propose operational hedging mechanism for the firm to implement to hedge against exchange rate fluctuations. In this dissertation, we do not implement any financial hedging on our model for the reasons mentioned above. Hence, operational hedging could also be used to hedge against demand uncertainty (see Mieghem and Dada 1999).

Operational hedging strategies is clearly defined and illustrated in Cohen and Huchzermeier (1999), Cohen and Mallik (1997), and Kouvelis (1999). Ding et al. (2007) defined operational hedging strategies as "real compound options that are exercised in response to the demand, price, and exchange-rate contingencies faced by the firm in a global supply chain context." Such operational techniques (real options) can be found in the literature. Some work include postponing prices (Kazaz, Dada, and Moskowitz 2005), switching production between countries (Dasu and Li 1997), choosing the optimal path in the supply chain network (Huchzermeier and Cohen 1996), reserving extra capacity (Cohen and Huchzermeier 1999), and producing less than the total demand before the selling period (Kazaz, Dada, and Moskowitz 2005).

Operational flexibility consists of the above real options. According to Cohen and Huchzermeier (1999), changes in market conditions, e.g. exchange rate or demands, are anticipated by the firm's operational flexibility. By implementing these options, the multinational firm can take advantages of the market volatility.

{Huchzermeier and Cohen (1996) consider a supply chain consisting of supplying countries, production facilities, and markets. Similar to our model, capacity decision is made before realizing the exchange rate. They developed model to select the optimal supply chain. For example, one optimal supply chain option is to supply the material form home country and manufacture the product at all factories and each factory sells it to its market. They implement a multinomial approach to approximate exchange rate. In their paper, they showed how operational hedging can lower the risk of exchange rate fluctuations. Our work is different, we save money by eliminating switching cost between production locations and we assume a multi-period horizon where the firm can change its prices from period to period, our third model, to hedge against exchange rate.

Kogut and Kulatilaka (1994) implemented shifting production between factories located in different countries, depending on exchange rate movement, as a mean of operational hedging. Our work differs in the sense that we do not shift production between countries, we use pricing as a hedging mechanism.

Kouvelis et al. (2001) introduce a new and interesting kind of shifting; shifting between strategies. Moreover, they proposed three types of strategies: exporting where capacity is at home, joint venture with a firm at the foreign market, and investing capacity at the foreign market. Exchange rate volatility can affect the shifting between those strategies. For example, increasing volatility would force the firm to implement the exporting strategy. In their work, they assume that the firm entered the foreign market, our work differs in a sense that we show when it is profitable to enter the foreign market, because it be costly to enter the foreign market under unfavorable exchange rate as we will show in our first model.

Kouvelis and Rosenblatt (2001) show how government subsidies such as: tariffs, financing of facilities and rules of trading can affect global manufacturing and distribution networks. They provided a mixed-integer program to evaluate the affected of those factors. We differ in our analytical approach.

Kazaz et al. (2005) developed a two staged stochastic program. The goal of this program is to hedge against uncertain exchange rate. This program chooses the optimal allocation policy based on the realized exchange rate. In their model, capacity is built and unites are manufactured before the realization of the exchange rate. Then, the exchange rate is know, the firm will decide if it is going to serve all markets or serve one market and deny the other market. They called the first step ``production hedging'' and the second step ``allocation hedging''. Similar to this proposal, they employed multiple period model. However, they do invest capacity at the foreign country unless it is more profitable, otherwise we assume that capacity investment is made at home. Also, if the manufacturer decided to invest capacity at the foreign market, that capacity will be used only for the foreign demand.

Ding et al. (2007) present a multinational firm that invests capacity in either one of the two markets or one in each market. They assume that the firm will make capacity commitment before the realization of the exchange rate and demand in both markets. In their paper, they used both financial hedging and operational hedging in order for the firm to protect itself against exchange rate uncertainty. The multinational firm will employ financial hedging, at the time of capacity building, by purchasing financial option contracts. This scheme is famous and mentioned by several researchers such as: Mello, Parsons, and Triantis (1995) and Chowdhry, and Howe (1999). The other method is operational hedging where the multinational firm postpones its allocation of capacity to both markets until the demand and exchange rate are known.

Ding et al. (2007) is similar to Kazaz et al. (2005) paper in a sense that both implement a two-stage stochastic program. In the first stage, both of them invest capacity before the realization of the exchange rate and in the second stage they allocate capacity after the realization of the exchange rate. The main difference is that ding et al. (2007) incorporate financial hedging techniques in the fist stage and Kazaz et al. (2005) look at the multi-period planning horizon.

There are two key differences that distinguish our model from Kazaz et al. (2005) and Ding et al. (2007): the modeling of the exchange rate and the demand function. We assume that the exchange rate follows a geometric Brownian motion and, in Kazaz et al. (2005), they assume that exchange rate is modeled as distributed random variables while, in Ding et al. (2007), they assume that exchange rate follows a lognormal distribution. Even though, in Ding et al. (2007) , they show the affect of exchange rate volatility on optimal capacity and expected profit but it lack more parameters such as: exchange rate drift and initial exchange rate which could greatly affect optimal capacity and expected profit. We assume that our demand is to be a price sensitive demand, additive demand, while Ding et al. (2007) and Kazaz et al. (2005) assume demand is a random variable. A minor difference between our work and Ding et al. (2007) is that they do not take into consideration transportation cost; if transportation cost is relatively big, this could affect the allocation of capacity between the two markets.

Aytekin and Birge (2004) favors financial hedging when exchange rate has a small volatility and operational hedging when exchange rate has a strong volatility. They modeled their problem as a continuous time while we used multi-period setting. They looked at three scenarios where production is done at home, production is done at home and foreign country and home production supply the shortage at the foreign market, and production is done in both countries and each production country can serve either market.

Competition has a major impact on pricing. Bitran and Caldentey (2003) claim that selecting a certain pricing policy depends mainly on the price competition among players. Chan et al. (2004) claim that product price and service are the major factors that firms compete on and that should be taken into account by firms when setting the pricing policies. The work done in the area of competition is ample, however most of it are trying to drive the optimal prices and quantities under demand uncertainty for different demand functions. Here an example of some: Bernstein and Federgruen (2004) addresses the problem of two echelon system (one supplier and competing retailers) under demand uncertainty. They derive the Nash equilibrium in terms of price and base-stock level for each retailer. Also, they show the impact of different parameters such as cost, and distribution parameters on optimal price and optimal base-stock level of a retailer.

Mieghem and Dada (1999) shows how price postponement strategy can generate more profit to the firm under competition and demand uncertainty. Anupindi and Jiang (2008) show that flexible firms (price and quantity postponement) can make more profit that inflexible firms (price postponement) under demand uncertainty (multiplicative and additive demand). However, Bernstein and Federgruen (2004), Mieghem and Dada (1999), and Anupindi and Jiang (2008) did not consider the impact of exchange rate uncertainty on capacity investment and price.

This work is unique in a sense that we are combning exchange rate uncertantity and competition and we investigate the impact of them on optimal prices, optimal capacity, and capacity allocations.

\section{Basic Settings, Assumption, and Nomenclature}

We consider a multinational firm that produces a single product at home and sell it to domestic and foreign markets. At the foreign market, we consider a foreign manufacturer that manufacturers the same product and sell it to the foreign market only. Therefore, the firm is competing with the foreign manufacturer on market share at the foreign market only. We consider a monopolistic setting at domestic market, and a duopoly setting at the foreign market, Figure \ref{basic model} (Wang 2014). Such examples of duopoly is: Visa Vs Mastercard, Pepsi Vs Coca-Cola, and Intel Vs AMD in the Microprocessor market.
\begin{figure}[ht]
\begin{center}
  \includegraphics[scale=0.5]{figure1_competitivemarket.pdf} \\
  \caption{The Model}
\label{basic model}
\end{center}
\end{figure}

\indent We consider a single period where the firm must decide on its initial capacity investment before the selling season,  selling price at each market, and the production allocation across the selling season after the realization of the exchange rate. In this model, the capacity investment is irreversible and must be made in the home country only. The domestic and the foreign markets differ in their demand base and disparity in currencies. In each market demand is assumed to be linearly decreasing in price which is expressed in local currency. The demand base is steady. In this paper, we assume a deterministic demand function of prices and can be "interpreted as expected demand in many applications" (Gallego and Hu 2006). We model the exchange rate as a random variable. It is assumed that the firm does not carry any inventory. The product can be produced and shipped to both markets at the beginning of the selling season. We used the following nomenclator in our analysis:

\noindent {\bf Parameters}

$n$: players index where n = $i$ for the incumbent, and n = $e$ for the
entrant

$j$: market index where $j=i$ for the incumbent's market, and $j$ = $e$ for the
entrant's market

limited capacity

$I_o$: The initial foreign exchange rate expressed in entrant's (home) currency per unit in incumbent's (foreign) currency.

$I$: exchange rate between the currency of entrant's home market and the incumbent's market

$C_i$: unit manufacturing cost at market $\,i$ expressed in market
$i\,$currency

$s$: unit shipment cost to the incumbent market expressed in the entrant's home currency

{\bf Decision Variables }

$K$: \  capacity invested by the entrant,

$P_{ij}$: \ unit selling price set by the player $i$ in market $j$

$Q_{ij}$: \ quantity sold by the player $i$ in market $j$

\noindent We assume that demand functions are differentiable and satisfy the following conditions:

\begin{equation*}
\frac{\partial D_{ei}}{\partial P_{ei}},\,\frac{\partial D_{ii}}{\partial
P_{ii}}\leq 0  \tag*{$(C1)$}
\end{equation*}
\begin{equation*}
\frac{\partial D_{ei}}{\partial P_{ii}},\,\frac{\partial D_{ii}}{\partial
P_{ei}}\geq 0  \tag*{$(C2)$}
\end{equation*}

Conditions $(C1)\,$and $(C2)\,$are common conditions in the oligopoly pricing literature (see Bernstein and Federgruen (2005) and Gallego and Hu (2006)). $(C1)$ shows that each player's demand decrease in its price. $(C2)\,$indicates that each player's demand increase in the other player's price. We are considering the additive demand function mentioned in Varian (1992), which satisfies $(C1)\,$and $(C2)$:
\begin{equation}
D_{ij}=\alpha_{ij}- P_{ij}+\theta P_{\text{-}ij} \ ,
\end{equation}

\noindent where $D_{ij}$ denotes the demand for player $i\,$ in market $j\,$ while $\alpha_{ij}$
represents the demand potential
for manufacturer $\,i\,$ in market $\,j\,$.
$\theta\,$ is the ``cross-price effect'' which is symmetric for ``well-behaved consumer demand function''. $\theta$  measures the degree of competition between the two manufacturers (Vives (1999) and Varian (1992)). In this study we focus on non-complementary product (substitutable product). According to Baumann et al. (1998) positive $\theta$ (e.g., an increase in the foreign manufacturer price increases the demand of the firm) means the products of both manufacturer are substitutable and if $\theta$ is a negative value that means that the two products are complements. Therefore, equation (3.1) can be formulated as follows (see Wang et al. (2016))  :
\begin{equation*}
D_{ee}=\alpha_{e} - P_{ee} \tag*{$(3.1A)$}
\end{equation*}
\begin{equation*}
D_{ei}= (1-\phi) \alpha_{i} - P_{ei}+\theta P_{ii} \tag*{$(3.1B)$}
\end{equation*}
\begin{equation*}
D_{ii}=  \phi \alpha_{i} -  P_{ii} + \theta P_{ei} \tag*{$(3.1C)$}
\end{equation*}

The total size of the imcumbent manufacturer's market is equal to $\alpha_{i}$, and $\phi $ represents the consumer's preference for its product.

In our setting, the exchange rate fluctuations across periods are modeled by a Weiner Process, $B(t)$, where $B(t)=\epsilon\sqrt{t}\,.\,$Here, $\epsilon$ is the random error term that follows the Standard Normal distribution. As such, it is assumed that the exchange rate follows a Geometric Brownian motion:

\begin{equation}
dI(t)=\mu I(t)dt+\sigma I(t)dB(t)  \ . \label{brownian}
\end{equation}

where $I(t)\,$is driven by the Ito process. The parameters $\mu$ and $\sigma$ are the mean and the standard deviation of the Normal exchange rate drift. The solution to equation \ref{brownian} is given by Davis (2001) as $I(t)=I_0e^{\left(\left(\mu-\frac{1}{2}\sigma^2\right)t+\sigma B(t)\right)}$. Assuming $B(t)=\epsilon\sqrt{t}$ and \ replacing in \ref{brownian}, we get

\begin{equation}
I(t)=I_0 e^{\left(\left(\mu-\frac{1}{2}\sigma^2\right)t+\sigma\epsilon\sqrt{t} \right)} \ .
\end{equation}

\section*{References}

\begin{hangref}

\item Ahmed A., M. Erkoc, and S. Cho. 2012. Capacity investment, pricing, and production allocation across international markets with exchange rate uncertainty. {\it Asia-Pacific Journal of Operational Research} {\bf 29}(01) 1240008 --1/34.

\item Anderson, K. (February 21, 1997). The Uses and Abuses of Risk Management: How Men Learnt to Bet Against the Gods. Times Literary Supplement

\item Anupindi,  R.,  L. Jiang.  2008.  Capacity  investment under  postponement strategies,  market competition,  and demand  uncertainty. {\it Management Science} {\bf 54}(11) 1876--1890.

\item Aytekin, U., J. R. Birge.  2004. Optimal Investment and Production Across Markets with Stochastic Exchange Rates. Working paper, Northwestern University and The University of Chicago.

\item Bernstein, F., A.  Federgruen. 2004. Dynamic inventory and pricing models for competing retailers. {\it Naval Research Logistics} {\bf 51}(2) 258--274.

\item Bernstein, F.,  A.  Federgruen. 2005. Decentralized supply chains with competing retailers under demand uncertainty. {\it Management Science} {\bf 51}(1) 18--29.

\item Bitran, G., R. Caldentey.  2003.  An overview of pricing models for revenue management. {\it Manufacturing $\&$ Service Operations Management} {\bf 5}(3) 203--229.

\item Chan, L. M. A.,  Z. J. M. Shen, D. Simchi-Levi, and J. L. Swann.  2004. Coordination of Pricing and Inventory Decisions: A Survey and Classification. In D. Simchi-Levi, S. D. Wu, $\&$ Z. J. M. Shen, (Eds.), Handbook of Quantitative Supply Chain Analysis: Modeling in the E-Business Era 335-392. Kluwer Academic Publishers.

\item Chowdhry,  B.,   J. T. B.  Howe  1999.  Corporate  risk  management  for multinational corporations: Financial and operational hedging policies. {\it European Finance Review} {\bf 2}(2) 229--246.

\item Cohen, M.A., S. Mallik. 1997. Global supply chains: Research and applications. {\it Production and Operations Management} {\bf 6}(2) 193--210.

\item Cohen, M. A., A. Huchzermeier. 1999. Global Supply Chain Management: A survey of research and applications. In S. Tayur, M. Magazine, $\&$ R. Ganeshan (Eds.) Quantitative Models for Supply Chain Management. Kluwer Academic Publishers.

\item Dasu, S., L. Li.  1997. Optimal Operating Policies in the Presence of Exchange Rate Variability. {\it Management Science} {\bf 43}(5), 705--722.

\item Davis, M. 2001. Mathematical of financial markets. Mathematics unlimited. Bjorn
Engquist; and Wilfried Schmid ed. In The Statistical In The Statistical Mechanics of Financial Markets, 3rd edn., pp. 361--380. Berlin: Springer.

\item Ding, Q., L. Dong, and P. Kouvelis.  2007.  On the integration of production and financial hedging decisions in global markets. {\it Operations Research} {\bf 55}(3) 470--489.

\item Dornier, P.  1998. {\it Global Operations and Logistics: Text and Cases.} New York: John Wiley $\&$ Sons.

\item Huchzermeier, A., M. Cohen. 1996. Valuing operational flexibility under exchange rate risk. , {\it Operations Research} {\bf 44}(1) 100-113.

\item Kazaz, B., M. Dada, and H. Moskowitz. 2005. Global production planning under exchange-rate uncertainty. {\it Management Science} {\bf 51}(7) 1101--1119.

\item Kogut, B., N. Kulatilaka. 1994. Operating flexibility, global manufacturing, and option value of a multinational Network.  {\it Management Science} {\bf 51}(7), 123--139.

\item Wen, L., H. Yang, H., D. Bu, L. Diers,  and H. Wang.  2018. Public accounting vs private accounting, career choice of accounting students in China. {\it Journal of Accounting in Emerging Economies}  Vol. 8 Issue: 1, pp.124-140.

\item Kouvelis, P., M. J. Rosenblatt. 2001. A Mathematical Programming Model to Global Supply Cain Management: Conceptual Approach and Managerial Insights. Working paper, Washington University and Technion

\item Kouvelis, P., K. Axarloglou, and V. Sinha. 2001. Exchange rates and the choice of ownership structure of production facilities. {\it Management Science} {\bf 47}(8) 1063--1080.

\item Li, X., Liao, X.,  Wang, H., \& Wei, L. 2018. Coordinating data pricing in closed-loop data supply chain with data value uncertainty (February 8, 2018).  Available at SSRN:  http://dx.doi.org/10.2139/ssrn.3120590

\item Singh, S.,  H. Wang, and M. Zhu. 2017.  Perceptions of Social Loafing in Groups: Role of Conflict and Emotions. Available at SSRN: http://dx.doi.org/10.2139/ssrn.3132871

\item Singh, S.,  H. Wang, and M. Zhu. 2017.  Perceptions of Social Loafing during the Process of Group Development". Midwest Academy of Management Conference Proceedings Chicago, Illinois. Working paper.

\item Lowe, T., R. E. Wendell, and G. Hu. 2002. Screening Location Strategies to Reduce Exchange Rate Risk. {\it European Journal of Operational Research} {\bf 136}(3) 573--590.

\item Mello, A., J. Parsons, and A. Triantis. 1995. An Integrated model of multinational flexibility and financial hedging. {\it Journal of International Economics} {\bf 39}(1-2) 27--51.

\item O'Brien, T. J. 1996. Global Financial Management. New York: Wiley.

\item Van Mieghem, J.A.,  M. Dada. 1999. Price versus production postponement: Capacity and competition. {\it Management Science} {\bf 45}(12) 1631--1649.

\item Wang, H. 2014. Essays on price competition and strategies: market entry with capacity allocation, channel design and information provision. Open Access Dissertations. 1339.

https://scholarlyrepository.miami.edu/oa\_dissertations/1339

\item Wang, H., H. Gurnani, and  M. Erkoc. 2016. Entry deterrence of capacitated competition using price and non-price strategies. {\it Production and Operations Management}  {\bf 24}(4) 719 --735.

\end{hangref}

\newpage
\setcounter{page}{1}
\pagenumbering{arabic}

redpajama_set_name: RedPajamaArXiv


Trainers and Instructors for its Academic Dept.
Hello Sinan, I just sent my application for the position. Looking forward to hearing from you.
I am also very interested! Please let me know.
International CAST needed: furniture brand advert.
I am also looking for an English & Turkish speaking housemaid for my family in Kartal area. Live-In/Live-out both options possible. Please contact me for details.
A friend of mine is looking for a job.
If you're looking for a job as an ELT instructor..
Dear Cankat, Would you mind to check my Resume for your consideration.
Omg how old is this post? I hope you're still here?
Turkey's first and sole classifieds site ( (…) ) in the English language is now live. Register for FREE and post ads completely FREE! Reach MORE PEOPLE!


text:
Seasons After's Jimmy Beattie Unleashes "Without Warning" Track
Written by Jason Price on August 10, 2015
Jimmy Beattie, lead guitarist for the band SEASONS AFTER, has offered up a video for a guitar inspired track of his own called "Without Warning". Check out the video below.
Seasons After has several Top 40 singles in Active Rock World and are currently pushing a new album entitled "Calamity Scars & Memoirs". The band also did a killer cover of "Cry Little Sister" from 'Lost Boys.' The latest single off the album is called "Weathered & Worn" and is currently in the Top 50 songs at Active Rock Radio.
Check out the band Seasons After here:
Official Website: www.seasonsafter.com
Facebook: https://www.facebook.com/seasonsafternation
Twitter: @SeasonsAfter

redpajama_set_name: RedPajamaCommonCrawl


WEST BEND, Wis. (CBS 58) — A teen is missing from West Bend and police are asking for help to find her.
Annabelle Plaskey, 17, was last seen by her legal guardian on February 18, 2019. Investigators believe she may be in the Fond du Lac or Madison areas.


Baby Signing Research - Baby Hands Productions, Inc.
Childhood development researchers have been studying the results of teaching hearing babies to sign for more than twenty years. Research in this field is expanding each year as the benefits of using sign language with preverbal babies becomes more compelling to researchers as well as parents.
In 1982, two researchers, Drs. Linda Acredolo and Susan Goodwyn noticed that young babies were spontaneously using simple hand movements to represent words they weren't yet able to say. This discovery prompted Acredolo and Goodwyn to conduct research, which spanned two decades, to study the effects of teaching hearing babies to sign. Much of this research was funded by the National Institutes of Health.
Acredolo and Goodwyn conducted a longitudinal study that involved 103 eleven month old babies. What these researchers found was amazing, babies that communicated with sign language before they could speak actually learned to talk sooner and scored higher on intelligence tests when compared to their non-signing peers. These babies developed larger vocabularies, displayed more self-confidence and engaged in more sophisticated play than their non-signing peers. Even at age eight, children who had learned to sign as infants scored significantly higher on IQ tests than those who had not! In addition, the parents of these babies reported a decrease in frustration and a strengthening of the bond between themselves and their babies.
Goodwyn, S.W., Acredolo, L. P. & Brown, C. (2000). Impact of Symbolic Gesturing on Early Language Development. Journal of Nonverbal Behavior, 24, 81-103.
Acredolo, L. P., & Goodwyn, S.W. (July 2000). The long-term impact of symbolic gesturing during infancy on IQ at age 8. Paper presented at the meetings of the International Society for Infant Studies, Brighton, UK.
Brie Moore, Linda Acredolo, & Susan Goodwyn (April 2001). Symbolic gesturing and joint attention: Partners in facilitating verbal development. Paper presented at the Biennial Meetings of the Society for Research in Child Development.
A pilot study was conducted by Dr. Kimberlee Whaley in 1999 at the A. Sophie Rogers Infant-Toddler Laboratory School at Ohio State University. Dr. Whaley found that babies as young as nine months of age were able to communicate with their teachers by using sign language.
Allott, R. (1994) Gestural Equivalents of Language.
Marilyn Daniels found that preschoolers who were taught sign language scored significantly higher on the Peabody Vocabulary Test when compared to preschoolers who did not learn sign language. Daniels concluded that a preschooler's vocabulary can be improved if words are presented visually and kinesthetically as well as verbally.
Daniels, M. (1994). The Effects of Sign Language on Hearing Children's Language Development. Communication Education, October, v43 n4, p291 (8).
Daniels, M. (1996). Seeing Language: The Effect Over Time of Sign Language on Vocabulary Development in Early Childhood Education. Child Study Journal, 26, 193-208.
Daniels, Marilyn, Dancing with Words: Signing for Hearing Children's Literacy. Bergin & Garvey, October 2000. ISBN: 0897897927.
Copyright © 2019 Baby Hands Productions, Inc.


text:
using System;
using Microsoft.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore.Infrastructure;
using Microsoft.EntityFrameworkCore.Metadata;
using Microsoft.EntityFrameworkCore.Migrations;
using WebApi.Migration.Demo;

namespace WebApi.Migration.Demo.Migrations
{
    [DbContext(typeof(AppContext))]
    [Migration("20170513064436_addFk3")]
    partial class addFk3
    {
        protected override void BuildTargetModel(ModelBuilder modelBuilder)
        {
            modelBuilder
                .HasAnnotation("ProductVersion", "1.1.1")
                .HasAnnotation("SqlServer:ValueGenerationStrategy", SqlServerValueGenerationStrategy.IdentityColumn);

            modelBuilder.Entity("WebApi.Migration.Demo.Model.Course", b =>
                {
                    b.Property<int>("CoId")
                        .ValueGeneratedOnAdd();

                    b.Property<string>("CourseName");

                    b.Property<int?>("StudentStuId");

                    b.HasKey("CoId");

                    b.HasIndex("StudentStuId");

                    b.ToTable("Course");
                });

            modelBuilder.Entity("WebApi.Migration.Demo.Model.Destination", b =>
                {
                    b.Property<int>("DestinationId")
                        .ValueGeneratedOnAdd();

                    b.Property<string>("Country");

                    b.Property<string>("Description");

                    b.Property<string>("Name");

                    b.Property<byte[]>("Photo");

                    b.HasKey("DestinationId");

                    b.ToTable("Destination");
                });

            modelBuilder.Entity("WebApi.Migration.Demo.Model.Lodging", b =>
                {
                    b.Property<int>("LodgingId")
                        .ValueGeneratedOnAdd();

                    b.Property<int>("DestinationDestinationId");

                    b.Property<bool>("IsResort");

                    b.Property<decimal>("MilesFromNearestAirport");

                    b.Property<string>("Name");

                    b.Property<string>("Owner");

                    b.HasKey("LodgingId");

                    b.HasIndex("DestinationDestinationId");

                    b.ToTable("Lodging");
                });

            modelBuilder.Entity("WebApi.Migration.Demo.Model.Student", b =>
                {
                    b.Property<int>("StuId")
                        .ValueGeneratedOnAdd();

                    b.Property<int?>("Age");

                    b.Property<DateTime>("BirthDate");

                    b.Property<string>("StuName");

                    b.HasKey("StuId");

                    b.ToTable("Student");
                });

            modelBuilder.Entity("WebApi.Migration.Demo.Model.Course", b =>
                {
                    b.HasOne("WebApi.Migration.Demo.Model.Student")
                        .WithMany("Course")
                        .HasForeignKey("StudentStuId");
                });

            modelBuilder.Entity("WebApi.Migration.Demo.Model.Lodging", b =>
                {
                    b.HasOne("WebApi.Migration.Demo.Model.Destination", "Target")
                        .WithMany("Lodgings")
                        .HasForeignKey("DestinationDestinationId")
                        .OnDelete(DeleteBehavior.Cascade);
                });
        }
    }
}


LIXOURI. Lixouri is the second largest town of Kefalonia (after Argostoli) and the main town of the peninsula Paliki, the western part of the island of Kefalonia. The inhabitants of the peninsula often called the peninsula itself just Lixouri. Lixouri town lies west of Argostoli (35 km) and south of Fiskardo, Assos and Myrtos. When coming from the direction of Argostoli, you should take the ferry and then within half an hour you arrive in Lixouri. You can also drive around Argostoli Bay and then you will lose approximately one hour. Lixouri is a lovely town with a nice center and a large square where there are many shops and cafes and the shopping street is pedestrianised . There are dozens of well-groomed restaurants, tavernas and bars. Around Lixouri and within 10 kilometres you will find beautiful beaches such as Xi-beach (also known as Red Beach) Petani Beach, Platia Ammos and Atheras. What certainly is worth doing is taking the ferry to Argostoli, you will sail across the bay of Argostoli and from the boat you will have a beautiful view of the coastal towns but also Katavothres and the lighthouse of Agioi Theodoroi. Lixouri, was completely destroyed in 1953 after an earthquake, has since been rebuilt and is actually a modern city. The Carnival is visited by many Greeks from the mainland and is an important tradition here.
Kefalonia: Where on the map is Lixouri located?


17-year-old Pixie is a tough-talking, wild and beautiful hedonist. In a dead end seaside town on the British coast, she and her friends have spent their summer being drawn deeper and deeper into a strange new world of experimentation.
In this timeless, dark place, somewhere between the sea and the land, values of love and intimacy grow increasingly distant, and cold, casual sexual exchanges have become the norm.
As the end of the summer nears, the unexpected arrival of an unfamiliar young boy, Blondie, signals a change in the group's cyclical routine. His innocence and peculiar strength cause Pixie to question her own motivations as she begins to struggle with feelings she's never experienced before. This is a coming of age story at once unique and entirely familiar; a haunting love story of a disaffected youth.
The short film, directed by Sara Dunlop and co-written by Sara and James Chappell, is a co-production between Rattling Stick and Dunlop Films. It was the only UK entry nominated for the short film Palme d'Or at the 2016 Cannes Film Festival, selected from over 5000 global submissions. It went on to win Best Narrative Short at the Brooklyn Film Festival and continues to be showcased at festivals worldwide. A feature film based on the same characters and world is currently in development.


If an event is cancelled with no postponement and will no longer take place you will receive a full refund for your purchase as soon as the event is confirmed cancelled by the venue. If an event is postponed your tickets will still be valid at the rescheduled date.
Will I receive my tickets in time for the event? Even if it is taking place in the next 24-48 hours?


Researchers from MIT have discovered a link between the size of a language-processing area of the brain and poor pre-reading skills in kindergartners. This finding, coupled with an MRI technique, could lead the way for an earlier dyslexia diagnosis.
Diagnosis of dyslexia may soon be done with a brain scan before children begin to read.
The study, published in the Journal of Neuroscience, relies on previous research showing that adults with poor reading skills have a smaller, less organized arcuate fasciculus.
According to researchers, this structure of the brain connects two areas integral to communicating: Broca's area, involved in speech production, and Wernicke's area, involved in understanding both written and spoken language.
Until this recent study, it was unknown whether the differences in the arcuate fasciculus were the cause of reading difficulties or the result of little reading experience.
Part of a larger effort that analyzes 1,000 children at schools in Massachusetts and Rhode Island, the study from Massachusetts Institute of Technology (MIT) involved researchers assessing children at the start of kindergarten for pre-reading sounds. This gave them an idea of where each child's pre-reading skills lay.
Following this assessment, the researchers then invited some of the children to MIT for brain scans that use a technique called diffusion-weighted imaging, a MRI (magnetic resonance imaging).
The study published in the Journal of Neuroscience utilizes brain scans from 40 children.
Upon comparing the brain scans with results of pre-reading tests, the researchers noticed a link between the size and organization of the arcuate fasciculus and performance on phonological awareness tests.
Phonological awareness refers to the ability to identify and employ the varying sounds of language. This ability, the researchers note, can be measured by observing how children segment, identify and rearrange sounds to make them into new words.
Elizabeth Norton, one of the lead authors of the study, says: "The first step in reading is to match the printed letters with the sounds of letters that you know exist in the world."
The researchers add that since the arcuate fasciculus connects Broca's area and Wernicke's area in the brain, a larger and more organized one could help the two regions communicate better. It could link both speech production and the ability to understand written or spoken language in a more efficient way.
"We don't know yet how it plays out over time, and that's the big question: can we, through a combination of behavioral and brain measures, get a lot more accurate at seeing who will become a dyslexic child, with the hope that that would motivate aggressive interventions that would help these children right from the start, instead of waiting for them to fail?"
The researchers conclude that for some dyslexic children, offering early training with phonological skills can help with their reading skills later on.
This latest study builds on a 2011 study, also from MIT, which revealed that phonological impairment could cause dyslexia.
Ellis, Marie. "Dyslexia could be diagnosed by MRI brain scan." Medical News Today. MediLexicon, Intl., 14 Aug. 2013. Web.


The value of this package includes 2 driving sessions of 5 and 6 laps. Review your driving in between the sessions and analyze with your instructor where you can improve your speed and skills.
Finally, the moment you've been waiting for: get behind the wheel of the racing Lamborghini, strap in and start your engine! You're in control, it's time to hit the track for your first driving session. 5 laps around the Las Vegas Motor Speedway infield road course.
It's time to buckle up again for your second 6 lap driving session. Let's put in to practice all the tips you get from your instructor.


This quote is especially poignant today with the news of the tragedies at Sandy Hook Elementary. We are sorrowful and disheartened at such unspeakable events and our hearts and prayers go out to each family effected. Since there are no words to lessen this tragedy, we will wait, and opportunities arise to give aid, we will be the first in line and will be sure to alert you of them as well. We are so grateful for the health and safety of our own families, and hope you squeeze your loved ones a little tighter today.
sorry, that previous comment was for the giveaway. it's hard to see what i'm clicking when using a phone!
Fave family gift – A Zoo membership!
A paid weekend at a Beautiful lake cabin = fabulous family gift!


I am still here and writing this blog. No posts for nearly a month! I apologise! There's been quite a lot going on including a wedding party here at home for my daughter Sophie who got married in the US last year without our being able to be there.
Just returned from a welcome week away in Salcombe which is a beautiful place totally unknown to me up til now, but I feel like going back! Wonderful views along the coastal inlet of the Kingsbridge estuary and Salcombe itself is an unspoilt little town with lots of original buildings, small shops….great retail therapy opportunities!…and interesting features.
While there I saw a book by artist Sue Lewington which was on the shelves of the holiday flat we were staying in. It was a book in the form of a sketchbook with the title Salcombe and had some really characterful and inspirational pen and wash drawings telling the story of the town. Made me want to immediately get my sketchbook out.
As it was, I confined my artistic activities to visiting an orchid nursery in Newton Abbott and looking for wild orchids on Orley Common, sadly none to be found. Why orchids?…there may be another book in the offing…more news later. Took loads of photos.
Back home here, the garden is a riot of colour and overgrown with flowers being visited by the bees. On that subject I read an article by Joe Swift in today's Times about flowers to grow to encourage bees..something we should all try and do to save our rapidly declining bee population. Bees like simple open flowers like daisies or bell shaped flowers that they can easily crawl into.
In this garden, the ones most visited are the lavender, scabious, cosmos, the cranesbill geraniums, nepeta, annual cornflowers, marigolds and nasturtiums, which I'm growing among the vegetables and of course the hollyhocks. Even the runner beans and potato flowers attract the bees…we had our first potatoes from the veg plot yesterday for tea and they were delish!
I'm rambling, a bit like the garden is after being neglected for a week!
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Terry Crews is on the promotion circuit for the fifth season of his television show 'Brooklyn Nine-Nine'.
Sean Evans' ability to conduct an intriguing interview over eating spicy wings gives a breath of fresh air to stock standard interview tropes. His extremely popular YouTube show 'Hot Ones' on the 'First We Feast' YouTube channel sees him and the interviewee both eat 10 increasingly hot chicken wings while Evans' asks a range of questions.
Staging an interview over food or beverages isn't anything new, but the added challenge of completing the 'Hot Ones wing challenge' brings a sense of intrigue and a lot of character to the interview.
Evans' interviewing technique is on full display in an interview with actor and comedian, Terry Crews, with Evans' bouncing off an already extremely charismatic man.
Terry Crews is on the show promoting the fifth season of Brooklyn Nine-Nine.
Evans clearly does plenty of research before interviewing his guest, combining questions about their career and their personal life – the latter can be an extremely touchy subject but Evans manages to not step on any toes and in turn keeps a positive vibe between him and his guest.
Evans brings up the topic of Crews' son and how he has bonded with him through building a custom computer to help understand his son's hobbies.
Evans stages it as an open-ended question by asking "can you talk to me about not knowing a damn thing about computers to all of a sudden building a state-of-the-art gaming PC with your son?".
He then lets Crews gush about "connecting with his [son's] world" and how he, 49-years-old at the time, is adapting to a modern world.
Evans forms a bond with Crews as they are keeping conversation with the heat of the chicken wings trounced in extremely hot sauce. Evans, a seasoned veteran at this point (four seasons in) can deal with the heat and continues to helm the interview.
Crews admits he's a competitive guy but even he has to commend Evans, exclaiming "You're pretty good!" after they both eat a 135,600 Scoville chicken wing. Evans barely breaks a sweat.
With every spicy wing, Evans changes to a completely new topic, keeping the interview feeling fresh.
Hot Ones, where Evans is a co-creator, producer and obviously the host, shows how popular the food-based interview format can be when it is entertaining.
The perfect mix between a quick on his feet, affable host in Evans, an interesting and charismatic guest, in this case, Terry Crews, and the challenge of defeating "the wings of death" is a recipe for success.
Heath Sheahan is studying the Diploma of Media and Communication at LaTrobe College. You can follow him on twitter @HeathSheahan.