‘In Contact With Four MLAs’: After Maharashtra, Sanjay Raut Claims Shiv Sena Will Create New Political Front In Goa
by IANSShiv Sena MP Sanjay Raut on Friday (29 November) predicted that after Maharashtra, there could "be a miracle" and a potential political earthquake in the Bharatiya Janata Party-ruled Goa soon.
"At least four MLAs, including those with Goa Forward Party President Vijay Sardesai are in contact with Shiv Sena.
"We plan to form a separate front in that state with various parties, including Congress… We are hopeful that there could be a ‘miracle' in Goa also soon," Raut told the media.
The Sena leader's comments on the political situation in the neigbouring state came a day after the Shiv Sena-Nationalist Congress Party-Congress's Maha Vikas Aghadi-led by Chief Minister Uddhav Thackeray took office.
(This story has been published from a wire agency feed without modifications to the text. Only the headline has been changed.)


Click in this frame to redirect keyboard input to it, then hit the spacebar
View the source code in Python and in JavaScript. This example has sourcemap support for Google Chrome. Press F12, click the source tab and then click somewhere in pong.js to try. N.B. The source of fabric.js has not been included yet.


The CSS font properties define the font family, boldness, size, and the style of a text.
In CSS, there are two types of font family names:
The font family of a text is set with the font-family property.
The font-family property should hold several font names as a "fallback" system. If the browser does not support the first font, it tries the next font, and so on.
Start with the font you want, and end with a generic family, to let the browser pick a similar font in the generic family, if no other fonts are available.
The font-style property is mostly used to specify italic text.
This property has three values:
The font-weight property specifies the weight of a font
The font-variant property specifies whether or not a text should be displayed in a small-caps font.
In a small-caps font, all lowercase letters are converted to uppercase letters. However, the converted uppercase letters appears in a smaller font size than the original uppercase letters in the text.
The font-size property sets the size of the text.
Being able to manage the text size is important in web design. However, you should not use font size adjustments to make paragraphs look like headings, or headings look like paragraphs.
Always use the proper HTML tags, like <h1> - <h6> for headings and <p> for paragraphs.
The font-size value can be an absolute, or relative size.
Absolute size:
Relative size:
To allow users to resize the text (in the browser menu), many developers use em instead of pixels.
The em size unit is recommended by the W3C.
1em is equal to the current font size. The default text size in browsers is 16px. So, the default size of 1em is 16px.
The size can be calculated from pixels to em using this formula: pixels/16=em
To shorten the code, it is also possible to specify all the individual font properties in one property.
The font property is a shorthand property for:
CSS Font Families
In CSS, there are two types of font family names:
- generic family - a group of font families with a similar look (like "Serif" or "Monospace")
- font family - a specific font family (like "Times New Roman" or "Arial")
Font Family
The font family of a text is set with the font-family property.
The font-family property should hold several font names as a "fallback" system. If the browser does not support the first font, it tries the next font, and so on.
Start with the font you want, and end with a generic family, to let the browser pick a similar font in the generic family, if no other fonts are available.
.serif {
font-family: "Times New Roman", Times, serif;
}
.sansserif {
font-family: Arial, Helvetica, sans-serif;
}
.monospace {
font-family: "Lucida Console", Courier, monospace;
}
p.impact {
font-family: Impact, Charcoal, sans-serif;
}
Font Style
The font-style property is mostly used to specify italic text.
This property has three values:
- normal - The text is shown normally
- italic - The text is shown in italics
- oblique - The text is "leaning" (oblique is very similar to italic, but less supported)
p.normal {
font-style: normal;
}
p.italic {
font-style: italic;
}
p.oblique {
font-style: oblique;
}
Font Weight
The font-weight property specifies the weight of a font
Font Variant
The font-variant property specifies whether or not a text should be displayed in a small-caps font.
In a small-caps font, all lowercase letters are converted to uppercase letters. However, the converted uppercase letters appears in a smaller font size than the original uppercase letters in the text.
Font Size
The font-size property sets the size of the text.
Being able to manage the text size is important in web design. However, you should not use font size adjustments to make paragraphs look like headings, or headings look like paragraphs.
Always use the proper HTML tags, like <h1> - <h6> for headings and <p> for paragraphs.
The font-size value can be an absolute, or relative size.
Absolute size:
- Sets the text to a specified size
- Does not allow a user to change the text size in all browsers (bad for accessibility reasons)
- Absolute size is useful when the physical size of the output is known
Relative size:
- Sets the size relative to surrounding elements
- Allows a user to change the text size in browsers
Set Font Size With Pixels & EM
To allow users to resize the text (in the browser menu), many developers use em instead of pixels.
The em size unit is recommended by the W3C.
1em is equal to the current font size. The default text size in browsers is 16px. So, the default size of 1em is 16px.
The size can be calculated from pixels to em using this formula: pixels/16=em
h1 {
font-size: 40px;
}
h2 {
font-size: 30px;
}
p {
font-size: 14px;
}
h1 {
font-size: 2.5em; /* 40px/16=2.5em */
}
h2 {
font-size: 1.875em; /* 30px/16=1.875em */
}
p {
font-size: 0.875em; /* 14px/16=0.875em */
}
Font Property
To shorten the code, it is also possible to specify all the individual font properties in one property.
The font property is a shorthand property for:
- font-style
- font-variant
- font-weight
- font-size/line-height
- font-family


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Apache Shiro Authorization Features
Authorization, also called access control, is the process of determining access rights to resources in an application. In other words, determining “who has access to what.” Authorization is used to answer security questions like, “is the user allowed to edit accounts”, “is this user allowed to view this web page”, “does this user have access to this button?” These are all decisions determining what a user has access to and therefore all represent authorization checks.
Authorization is a critical element of any application but it can quickly become very complex. Shiro’s goal is to eliminate much of the complexity around authorization so that you can more easily build secure software. Below is a highlight of the Shiro authorization features.
Features
Related ContentJava Authorization GuideLearn how Shiro handles access control in Java. Read More >> Authorization DocsFull documentation on Apache Shiro's Authorization functionality. Read More >> Getting StartedResources, guides and tutorials for new Shiro users. Read More >> Web App TutorialStep-by-step tutorial for securing a web application with Shiro. Read More >> |
Subject-based - Almost everything you do in Shiro is based on the currently executing user, called a Subject. And you can easily access the subject retrieve the Subject and checks its roles, permissions, or other relevant attributes anywhere in your code. This makes it easier for you to understand and work with Shiro in your applications.
Checks based on roles or permissions - Since the complexity of authorization differs greatly between applications, Shiro is designed to be flexible, supporting both role-based security and permission-based security based on your projects needs.
Powerful and intuitive permission syntax - As an option, Shiro provides an out-of-the-box permission syntax, called Wildcard Permissions, that help you model the fine grained access policies your application may have. By using Shiro’s Wildcard Permissions you get an easy-to-process and human readable syntax. Moreoever, you don’t have to go through the time-consuming effort and complexity of creating your own method for representing your access policies.
Multiple enforcement options – Authorization checks in Shiro can be done through in-code checks, JDK 1.5 annotations, AOP, and JSP/GSP Taglibs. Shiro’s goal is to give you the choice to use the option you think are best based on your preferences and project needs.
Strong caching support - Any of the modern open-source and/or enterprise caching products can be plugged in to Shiro to provide a fast and efficient user-experience. For authorization, caching is crucial for performance in larger environments or with more complex policies using back-end security data sources.
Pluggable data sources - Shiro uses pluggable data access objects, referred to as Realms, to connect to security data sources where you keep your access control information, like a LDAP or a relational database. To help you avoid building and maintaining integrations yourself, Shiro provides out-of-the-box realms for popular data sources like LDAP, Active Directory, Kerboros, and JDBC. If needed, you can also create your own realms to support specific functionality not included in the basic realms.
Supports any data model - Shiro can support any data model for access control– it doesn’t force a model on you. Your realm implementation ultimately decides how your permissions and roles are grouped together and whether to return a “yes” or a “no” answer to Shiro. This feature allows you to architect your application in the manner you chose and Shiro will bend to support you.


The Slide effect default behavior will be to Slide Out the target element from the initial size until the element disappear in 1 second. The Slide effect require the content of the animated element to be wrapped into a single block element.
Think of it as a picture sliding out of a frame.
The picture is the animated element and picture frame is the wrapper DIV.
This effect requires the animating element is within a single container tag, such as a DIV.
Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
Toggle
The slide effect after instantiation can be called in different situations by different elements in the page at different times. In this example we animate the same element when you click either a button or a link. The animation can be also started when the mouse is over an element, the page is loaded or on any other page events.
In this example each time the effect is started will toggle the direction because we added "toggle:true" to the constructor.

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
Slide Horizontal
The Slide was designed to animate the element vertically or horizontally. By enabling the horizontal option the element will dissapear to its left.

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.
Duration and Sizing
The duration and the initial/final size of the region to be animated can be controlled with specific options passed to the Slide Effect constructor. The "from" and "to" options represent the percentage size of the initial element size or the absolute value in pixels.
Duration is set in milliseconds.

Initially hidden element
The target animated element can initially be hidden. To hide an element ou can use one of two CSS properties: display and visibility. The difference between these two properties is the way the element while hidden will alter the flow of the page. While using the display: none; the element is completelly removed from page and the other elements will take its place the visibility: hidden will leave the element in the page flow with all the sizes and other behaviours unaltered but the element is simply not seen.
In the following sample we will use the visibility: none; to initially hide the element and using the Slide effect the element will appear in page.
 ... <form method="get" action="slide_sample.html"> <input type="button" onclick="slide_hidden.start();" value="Slide Example" /> </form>

 ...

 ...
Setup and Finish functions
Sometimes, when using the effects, you need to run some other JavaScript functions before or after the animation. In the constructor you have the possibility to pass two options: "setup" and "finish" with the callback functions which Slide will call automatically.
This example will disable the button while the animation run. The background color of the button will be white during this time.

Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet.


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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
@Beta public interface TransformOutputProvider
The output of a transform.
There is no direct access to a location to write. Instead, Transforms can ask to get the location for given scopes, content-types and a format. This API is non final and is subject to change. We are looking for feedback, and will attempt to stabilize it in the 1.6 time frame.
| Method Summary | |
|---|---|
void |
deleteAll()
Delete all content. |
java.io.File |
getContentLocation(java.lang.String name,
java.util.Set<QualifiedContent.ContentType> types,
java.util.Set<QualifiedContent.Scope> scopes,
Format format)
Returns the location of content for a given set of Scopes, Content Types, and Format. |
| Method Detail |
|---|
void deleteAll() throws java.io.IOException
java.io.IOException
@NonNull java.io.File getContentLocation(@NonNull java.lang.String name, @NonNull java.util.Set<QualifiedContent.ContentType> types, @NonNull java.util.Set<QualifiedContent.Scope> scopes, @NonNull Format format)
Format.DIRECTORY
then the result is the file location of the
directory.Format.JAR
then the result is a file representing the jar to create.
Non of the directories or files are created by querying this method, and there is
no checks regarding the existence of content in this location.
In case of incremental processing of removed files, it is safe to query the method to get
the location of the files to removed.
name
- a unique name for the content. For a given set of scopes/types/format it must
be unique.types
- the content types associated with this content.scopes
- the scopes associated with this content.format
- the format of the content.
|
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Luckin Coffee Surges On Improving Operating Metrics
by Investing HoboSummary
- Large institutional positions were taken in Luckin Coffee pre and post IPO.
- Luckin Coffee has three distinct methods of achieving profitability without sacrificing long term growth.
- Luckin Coffee is already profitable at the store level despite a number of key operating metrics still far from potential normalization.
(Image from Luckin Coffee. The company's aggressive branding campaign is unparalleled to most US listed Chinese companies in the past two decades.)
Luckin Coffee (LK) must have been serving more than coffee during its pre-IPO roadshow months earlier. Despite recording net losses greater than total revenues in the quarter prior to its May IPO, the company was able to attract large institutional positions after shares traded publicly. After posting third quarter 2019 results, Luckin shares soared by over 42% proving recent large institutional bets correct. Unlike a number of recent unicorn companies, Luckin Coffee has a very precise business plan that should lead to substantial earnings growth in the coming quarters.
Since Luckin Coffee currently only operates in China and derives all of its revenues in RMB, this article will refer mostly to the company's reported RMB figures. The current USD/RMB exchange rate is 7.01 RMB to 1 USD.
Institutional Investors
The number of large institutional positions taken in Luckin shares just days after its May 17th IPO should have been a clear sign for individual investors the company had positive long term potential. According to SEC filings, there have been a total of seven beneficiary shareholder filings after Luckin went public and included increased positions by two pre-IPO equity holders.
| Filing Date | Equity Stake | Pre-IPO Investor | |
| Darsana Capital Partners | 05/17/19 | 11.12% | Yes |
| GIC Private | 05/17/19 | 13.63% | No |
| Qatar Investment Authority | 05/17/19 | 8.81% | No |
| Louis Dreyfus Company | 05/21/19 | 8.00% | Yes |
| Melvin Capital Management | 05/29/19 | 7.86% | No |
| Capital Research Global Investors | 05/31/19 | 15.60% | No |
| Point72 Asset Management | 08/05/19 | 5.00% | No |
(Data from LK SEC filings.)
The cumulative percentages of these holdings suggests some may have divested a portion of their positions since May. While LK shares sold off after second quarter earnings, the company showed a lot of operational improvements that led me to believe Luckin Coffee could become profitable before most Wall Street estimates.
Third Quarter Earnings
I've read a lot of opinions regarding Luckin Coffee in recent months. The most common misconception was based on a simplistic argument Luckin was a bad investment because it loses a lot of money. As a conservative investor, I tend to agree that money losing companies are bad investments. This is especially true for companies with broken models without reasonable route towards profitability. It is also true for companies with valuations so high that even extremely optimistic profitability models several years in the future still could not justify the current market capitalization.
The problem with bearish arguments I've read regarding Luckin Coffee has been a headline loss generalization without deeper insight on the company's operational metrics. Some arguments I've read do not even seem to fully understand why Luckin Coffee has been posting operational losses. The company actually provides a lot of information regarding its operations but I have yet to read an earnings recap that actually dove into these metrics. The goal of this article is to highlight which operational metrics investors should track to fully understand when and how Luckin Coffee could be profitable in the future.
Luckin Coffee is still a fairly new company with limited operations last year. As a result referring to annual revenue growth of 540% would not be very useful. At least for the next couple of quarters, investors should concentrate on sequential operational improvements which have been nonetheless extremely impressive.
| Q1 2019 | Q2 2019 | Q1/Q2 Sequential Growth | Q3 2019 | Q2/Q3 Sequential Growth | |
| Store Count | 2370 | 2963 | 25.02% | 3680 | 24.20% |
| Revenues | 478510 | 909115 | 89.99% | 1541591 | 69.57% |
| New Cumulative Customers | 16872 | 22777 | 35.00% | 30724 | 34.89% |
| Average Monthly Items Sold | 16276 | 27593 | 69.53% | 44245 | 60.35% |
| Average Monthly Customers | 4402 | 6166 | 40.07% | 9340 | 51.48% |
(Data taken from Luckin Coffee's Q3 2019 earnings report. Revenues in thousands of RMB. New cumulative customers, average monthly items sold, and average monthly customers in thousands.)
Despite posting 90% sequential revenue growth in the previous quarter, Luckin still managed a very impressive 70% sequential revenue growth in the third quarter. What is more important than the magnitude of sequential revenue growth is the relationship with its sequential store count growth. As the table above shows, revenues grew at almost 2.9 times greater than the company's quarterly store count increase. The company's growth has been well beyond store count additions.
Three Key Paths To Profitability
Product Average Selling Prices
One of the key metrics for investors to keep an eye on are average selling prices [ASP] for its products. This metrics reflects the current realized revenues which are heavily discounted compared to listed menu prices. The table below shows third quarter ASPs which improved slightly over the previous quarter.
| Q1 2019 | Q2 2019 | Q1/Q2 Sequential Growth | Q3 2019 | Q2/Q3 Sequential Growth | |
| Drinks | 39231.6 | 63167.1 | 61.01% | 103966.2 | 64.59% |
| Others | 9595.8 | 19611.9 | 104.38% | 28767.6 | 46.68% |
| Drink ASP | 9.20 | 10.44 | 13.37% | 11.02 | 5.57% |
| Others ASP | 8.75 | 10.75 | 22.84% | 12.09 | 12.48% |
| Blended Average | 9.12 | 10.51 | 15.30% | 11.25 | 7.04% |
(Data taken from Luckin Coffee's Q3 2019 earnings report. Drinks and non-drinks unit sales in thousands. ASP figures in RMB.)
These ASPs compared to an average listed menu drink price of about 25 RMB. Due to continual promotions such as 'buy 10 get 10 free' and free first drink for new customers, Luckin's average realized ASPs are over 50% discounted compared to listed menu prices. This metric has led to some premature bearish arguments the company has a broken business model.
Using third quarter's operating loss and quarterly items sold, Luckin Coffee could have reached corporate operational break even by posting 3.93 RMB higher blended ASPs. Just by reaching blended ASPs of 15.18 RMB though less discounting in this example, Luckin Coffee would have posted a net profit. 15.18 RMB blended ASPs would still represent over 39% discounts from average menu prices. This ASP level for brewed drinks would still be less than half the average 35 RMB menu prices at Starbucks (SBUX) in China.
Unit Sales Volume
Despite continued promotional discounting to attract and retain new customers, Luckin Coffee reported that its stores posted an average of 12.5% operational profit margin. This should not be much of a surprise for those who kept an eye on the company's operating metrics but apparently it was enough of a surprise to spur the massive post earnings rally. Just through sheer increased unit volume, Luckin Coffee has been able to decrease unit costs and improve product gross margin beyond store operating expenses.
The following table shows some cost metrics for the third quarter relative to prior quarters.
| Q1 2019 | Q2 2019 | Q1/Q2 Sequential Growth | Q3 2019 | Q2/Q3 Sequential Growth | |
| Materials | 5.65 | 5.63 | -0.38% | 5.43 | -3.45% |
| Store Operating / Store | 119.14 | 125.37 | 5.22% | 129.70 | 3.46% |
| Depreciation / Store | 35.43 | 29.86 | -15.72% | 29.49 | -1.26% |
| G&A / Store | 72.98 | 65.92 | -9.67% | 66.87 | 1.44% |
| Store Opening / Store | 75.33 | 28.96 | -61.56% | 30.37 | 4.87% |
(Data taken from Luckin Coffee's Q3 2019 earnings report. All figures except materials per item in thousands. All costs in RMB.)
Unlike in the previous second quarter, metrics in the third quarter showed some per store costs leveling out despite increased volume. However the G&A and store opening costs are on the corporate level and did not affect store margins despite increasing marginally on a sequential basis. While store operating costs did increase sequentially, it is more important to note that the increase was due to higher items sold per day. As the chart below shows, items sold per day per store increased by almost 29% sequentially over the second quarter.
(Data taken from Luckin Coffee's Q3 2019 earnings presentation. Q1 2019 sequential seasonal drop reflects the Lunar New Year holiday.)
As a result of higher sales volume, store operating costs per cup declined from 3.99 RMB in Q2 2019 to 3.18 RMB in Q3 2019. This cost reduction alone accounted for a 7.2% product gross margin improvement in the quarter at the blended product ASP of 11.25 RMB. While cost reductions in material and depreciation may have limited further downside, per cup operating costs could still potentially get cut in half.
Management noted in their Q2 2019 earnings conference call that its first store averaged a thousand items sold per day. The gradual increase in items sold per store per day may reflect older stores slowly raising the company average. After all, 1,000 items sold per day just represents either 1,000 customers buying a drink, or 500 customers buying a drink and food, or some combination of the two. It may take a year for a store to reach this sales level but in the most populous country in the world this average target does not seem that unreasonable.
If we assume Q3 2019 items sold per store per day reached 1,000 and store operating costs grew at the same sequential ratio, operating costs per cup would have been reduced to 1.68 RMB. In this theoretical example, the per cup savings at 1,000 daily rate would have yielded an incremental gross profit of 505 million RMB. Compared to the posted 591 RMB operating loss in the third quarter, Luckin Coffee would have narrowed operating loss by 86% just on increased volume of 1,000 items sold per day even at the current large discounted pricing relative to listed menu prices. At about 1,100 items sold per day average, operational break even would be reached on third quarter operational metrics.
Increased Footprint
As noted above, Luckin Coffee already reached operational profitability at the store level. At 3680 stores ending the third quarter with a 12.5% store operating margin, it would not be difficult to extrapolate how many total stores would be required to cover the company's corporate level expenses. Using third quarter operating metrics, Luckin Coffee would need to reach 6.6 billion RMB in quarterly sales to reach operating break even at the corporate level.
Luckin Coffee's midpoint revenue guidance for the fourth quarter calls for 2.21 billion RMB. The company also has a year end store count target of 4500 which puts sequential store growth at about the same level as in the third quarter. For simplicity, this equates to about 480,000 RMB in quarterly revenues per store. Thus at Q3 2019 operating metrics, Luckin Coffee would need to have 13,750 stores to reach operating break even at the corporate level.
This is about three times the company's target store count at the end of 2019. Based solely on this metric, Luckin would still be well over a year away from breaking even at current expansion rates. However even if current operating metrics do not improve, Luckin announced two avenues of expansion that could accelerate its path to profitability.
As primarily a tea drinking country, it would be more difficult to convert the general population to coffee outside of the western influenced corporate side in China's tier 1 cities. To aid this cultural hurdle, the company is launching Luckin Tea which will primarily address China's tier 2 and 3 cities. According to the company's Q3 earnings conference call, tea beverages already account for 20% of total drink volume for Luckin Coffee branded stores. The rapid acceptance of this new beverage line in less than two quarters should bold well for the coming expansion into markets more familiar with tea than coffee.
Luckin also just announced a new retail partnership model which in effect is a revenue sharing franchise model. With initial setup and continuing operational costs shifted to partners, the company could expand its brand presence at a much faster rate and eventually realize revenues once partners exceed predetermined operating targets. Current guidance does not include any potential revenue from this partnership model. Since this is a new initiative, it may take several quarters before actual revenues would be recognized but the upside to this revenue stream is likely to be at very high gross margin.
Fourth Quarter Earnings Estimates
For the fourth quarter, Luckin gave a product revenue range of 2.1-2.2 billion RMB. Total revenues should be slightly higher since the company also collects delivery fees. Based on the midpoint of this guidance and assuming third quarter operating metrics stay level, we can estimate Luckin Coffee's earnings for this coming quarter.
Q4 2019 Earnings Estimate
- Total Stores: 4500
- Revenues: 2208500 RMB ($315.1 million USD at 7.01 exchange rate)
- Cost of materials: 993226 RMB
- Store rental and operating costs: 583661 RMB
- Depreciation expenses: 132695 RMB
- Sales and marketing expenses: 550000 RMB
- G&A expenses: 300929 RMB
- Store opening and other expenses: 22380 RMB
- Total operating expenses: 2582891 RMB
- Operating income: -374391 RMB
- Operating loss in USD: -$53,105.12
- Share count: 240328
- GAAP EPS: -$0.22
- Non-GAAP EPS (excluding share based compensation only): -$0.20
(All RMB figures in thousands.)
This compares to current analysts' average estimates of -$0.17 on $306.4 million in revenues. I believe analysts' estimates call for a slightly lower loss based on the company's statement of marketing expenses peeking in the third quarter and fourth quarter returning to normalized levels. For the sake of conservatism I kept fourth quarter marketing expenses level with the prior quarter, but if the company cut this expense by just 10% sequentially, the estimates above would arrive at current Wall Street expectations of -$0.17 in non-GAAP EPS.
To give a perspective on the accuracy of this estimate, Luckin Coffee beat my Q3 estimate by posting a net loss of $15 million USD lower than expected with marketing expenses factored out. Even despite marketing expenses coming in much higher than my estimates, GAAP net loss of -$74.4 million USD was only slightly larger than my -$70.5 million estimate. In essence the company's improved operational efficiency allowed for much higher levels of marketing without compromising investor expectations.
Final Thoughts
Another way Luckin Coffee could reach profitability sooner is by limiting its marketing expenses. The company spent $78 million USD on sales and marketing and posted a GAAP net loss of $74.4 million in the third quarter. Obviously had the company cut back on marketing entirely, corporate profitability could have already been achieved. As I argued in my Luckin Coffee IPO article, I believe it is critical for the company to spend heavily on branding for its long term success, and in my opinion the company should remain aggressive as long as its cash flow situation permits.
$78 million USD is for sure a lot of money for a new and relatively small Chinese startup to spend on sales and marketing in a single quarter. Despite heavy marketing and rapid physical expansion, operating cash flow as only negative by $17.2 million USD while free cash flow was negative $67.1 million USD. With over $770 million USD in net cash at the end of the third quarter, Luckin Coffee could sustain this level of spending for nearly another three years even if operating metrics did not improve further.
Unlike food chains in the US, Luckin Coffee uses a mobile app to conduct all of its sales. As a result, the company has a record of each customer and their spending habits. This is a huge advantage because it allows the company to offer customer specific incentives to keep them engaged with the brand. Below is a cohort spending pattern provided by the company.
(Chart from LK's Q3 earnings presentation.)
While this chart may look like a complete mess at first glance, it does offer a lot of insight on how the company manages its customers. The most obvious pattern is a zigzag spending patter that tails off after the first month for a new cohort. What this pattern shows is Luckin has been able to manage cohort spending patterns through promotions such that months of lower activity are followed by a spending rebound. By keeping customers engaged with the brand, the company has been able to slowly increase cohort revenues over time.
What this chart also shows is about after a year, cohort spending starts to exceed original spending patterns in the promotional first month. Because this chart is based on listed prices and not what the customer actually spent, recognized revenues in the first month of a new cohort were likely very low since new cohorts were given a free product for signing up. Removing this free trial from the equation, actual recognized revenues for cohorts a year old were likely double that of the initial month.
This is perhaps the most important aspect of Luckin Coffee's metrics because it shows the company has been successful not only in retaining trial customers but also getting them to spend more over time. The following table shows not only the increase in active monthly customers, but the increasing volume of these customers.
| Q4 2018 | Q1 2019 | Q2 2019 | Q3 2019 | |
| Average Monthly Transacting Customers | 4.3259 | 4.402 | 6.166 | 9.3397 |
| Drinks Sold | 13.4188 | 13.0772 | 21.0557 | 34.6554 |
| Drinks Per Customer | 3.10 | 2.97 | 3.41 | 3.71 |
(Data taken from Luckin Coffee's Q3 2019 earnings report. All figures except drinks per customer in millions.)
Since the table above shows current trends, it discounts the eventual trend a year from now when higher levels of new cohorts picked up since the IPO quarter start increasing their recognized spending pattern 3-4 quarters from now. If Lucking Coffee achieves profitability before the middle of 2020 through a combination of avenues described above, this new wave of cohorts will start to incrementally add to profits in as little as three quarters.
Obviously LK has surged a lot in the three days following its third quarter earnings. As a result it would be irresponsible to encourage buying after such a massive rally since the risk of a pullback would naturally be higher. Whatever the trading gods decide for LK in the short term, the company has only increased its value as a long term investment through solid execution.
Disclosure: I am/we are long LK. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Additional disclosure: I am also short SBUX.


| DOSE: T+ 0:00 |
0.5 hits |
oral |
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| T+ 1:00 |
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I first tried acid when I was 17 years old. I've never had much interest in drugs. Having smoked pot on several occasions and having never really enjoyed it, I stuck to alcohol. But my best friend, Mary, had tried acid a few times and liked it, and I started to become curious. After much thought, I decided one Friday to cut school with Mary and trip for the first time. I deliberately brought a few toys to entertain us, some water bottles and lollipops (Mary had said she enjoyed sucking on candy while tripping). I also wore comfortable clothes and sneakers, as Mary had said that if an item of clothing is bothering you at all, its annoyance will be heightened while tripping.
I arrived at Mary's house around 11:45 in the morning and we took the tabs at 12 noon. She, having tripped before, took 2 tabs while I only took a half of one (we had been told by the dealer that each tab was a bit strong so to take them in moderation). We waited around in her house for about an hour, listening to music and going online. Hers started to kick in within the hour, while I still felt nothing. I was disappointed that I wasn't feeling any different, but I was also scared to take another tab because I didn't know what to expect. We left her house and I decided to take another 1/2 a tab (one full tab so far, supposedly at extra strength).
We met up with a few friends of ours (who didn't know we were tripping) and drove around in their car with them. I still didn't feel any different inwardly but I became slightly more giggly and my friends asked if we had been drinking. We said yes so they wouldn't wonder what was up. I seemingly lost my inhibitions a bit: I started dancing and singing in front of everyone, and was having a good time. I still didn't get any visuals and all my surroundings looked the same. As this had gone on for about another hour, I decided something. I didn't plan on ever doing acid again (I just wanted the experience), so I figured I should take another tab to ensure that I got the most out of the experience. At this point my friends who weren't tripping were playing a game and Mary and I each took another whole tab.
The second this tab entered my mouth I felt an inward change. I'm not sure if this was the previous tab kicking in or the one I had just taken was really strong. Either way, Mary had the same reaction and said that my head had just 'spun out of control' and that the 'trees were all fuzzy.' I still didn't have any visuals but I definitely felt strange, so we left my other friends and decided to walk around.
I noticed a number of things as the second tab kicked in. Any food I ate had hardly any taste. I couldnt tell how loud I or Mary were speaking. I wasn't sure if we were acting normal or if we were causing a scene. Everyone around us seemed to be speaking a foreign language. We were walking at what we thought was normal speed, but people were passing by us at a rapid rate so we figured we must be walking very slow. It was as if, all of a sudden, we realized that we were tripping and we weren't sure how we had been acting towards people up until that point. In one sense I was worried about this (and I did not want to see anyone that I knew for fear of acting very bizarre in front of them), but in another, I was glad I realized what I was doing and that anything I saw wasn't real.
As the evening wore on (it had probably been around 2 hours since I took the 2nd tab), everything around me developed a blue tint. Colors were glowing, I noticed lots of patterns and I could spot every light around me for about a mile because they were glowing stronger. My body felt mushy and soft, and my fingers felt fat and bloated. I was afraid to look in the mirror because I had heard that you can see your skin melting off of you and I wasn't sure I was ready to handle that. I started yearning to see my mother.  I also had a male interest at the time, and my desire for him grew stronger during the trip as well. I kept blessing myself with the sign of the cross, but did not realize I was doing it until Mary pointed it out.
Mary and I walked around for about another hour. At this point it was about 6:30 in the evening and it was getting dark out. We decided to go to my friend Martin's house and sit around until we came down completely. We watched Martin and his friends play Super Mario, and every level moved so slowly that I thought each one was a water level. Martin was also playing the guitar, and the sound coming from it seemed to stick to him and travel wherever he went. Another hour of this, and we left. Now it was raining out, and the rain splashing in the puddles looked like pins stabbing at water balloons. The splash caused by the rainddrops seemed to be leaping out of the puddle instead of entering it. My friends were smoking cigarettes and the smoke was flowing and beautiful.
Mary and I returned to her house at about 10:45 at night. We watched television for a few hours, while the walls in her room were still moving and my body still felt soft and mushy. I tried to recite a few prayers in my head but kept losing my train of thought as I went along.
I went home (alone) at about 2 in the morning. I was still sort of tripping but had come down considerably. It took me about 4 hours to fall asleep.
I had figured the whole time that this would be my only time tripping, because I dislike the feeling of not being able to have control over my surroundings. With acid, you don't know exactly what to expect. I was disapointed that I didn't really get any visuals, which is something that may make me want to try it again. Since having done it, I feel like I have a higher perception of sound and I am more sensitive to rapid movement. Also, I do feel a greater sense of faith (perhaps because God got me through the trip safely). I didn't feel a great sense of happiness while on acid, but I also didn't feel sad...it was somewhat neutral with perhaps a few new insights. I wouldn't discourage people from trying it as long as you are not stupid about it: I recommend, for your first time, not combining it with any other drugs and making sure you have a house to be in in case you feel like you need to be indoors.
All in all acid was an enjoyable yet alienating experience.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


NZD/USD on the lower grounds amid fading trade hopes, a lack of major catalyst
by Anil Panchal- NZD/USD stays on the back foot amid trade pessimism.
- FOMC minutes offer no surprises.
- New Zealand Credit Card Spending decorates the domestic economic calendar.
White House Deputy Press Secretary Judd Deere’s trade positive comments fail to ease the present skepticism surrounding the US-China phase one deal as the US President Donald Trump “likes what's happening right now.” The US House is debating the Hong Kong Bill and risks escalation of dispute with China. Among all this, NZD/USD extends its earlier losses while taking rounds to 0.6415 at the start of Thursday’s Asian session.
Following the United States' (US) Senate’s passing of Hong Kong Human Rights And Democracy Act, doubts over any trade accord between the US and China rose as the dragon nation severely condemned the Trump administration’s act of interfering their internal issue. Also supporting the move was Reuters’ story suggesting no phase one deal between the global superpowers during this year. Increasing the voice is the latest CNBC news citing four sources who suggest the deal is in trouble because there is not an agreement between the US and China -- even at the stage -- on which tariffs would go and which tariffs would stay.
Even so, Fox News’ Edward Lawrence quoted White House Deputy Press Secretary, Judd Deere, as saying that negotiations are continuing and progress is being made on the text of the phase-one agreement. The diplomat also conveyed President Trump’s saying in China, “China wants to make a deal. The question is: Do I want to make a deal? Because I like what’s happening right now. We’re taking in billions and billions of dollars.”
Minutes of the Federal Open Market Committee’s (FOMC) latest monetary policy meeting offered no surprise as policymakers continue to be happy on the present path while leaving doors wide open for action in case needed.
While trade/political headlines are likely to keep the driver’s seat, the economic calendar has October month Credit Card Spending (YoY) data from New Zealand. The initial signal to consumer spending indicates an improvement to 5.5% versus 4.8% prior. However, the Reserve Bank of New Zealand (RBNZ) officials have been hinting an action in February meeting and the same could be judged on the flow of incoming statistics. From the US, weekly jobless claims, Existing Home Sales and Philadelphia Fed Manufacturing Survey will keep traders busy during the later part of the day.
Technical Analysis
Given the quote’s another pullback from 100-day Exponential Moving Average (EMA), at 0.6426 now, prices could retest a 21-day EMA level of 0.6384 ahead of resting on five-week-old rising support line at 0.6353.
additional important levels
| Overview | |
|---|---|
| Today last price | 0.6414 |
| Today Daily Change | -14 pips |
| Today Daily Change % | -0.22% |
| Today daily open | 0.6428 |
| Trends | |
|---|---|
| Daily SMA20 | 0.6382 |
| Daily SMA50 | 0.6345 |
| Daily SMA100 | 0.6436 |
| Daily SMA200 | 0.6566 |
| Levels | |
|---|---|
| Previous Daily High | 0.6431 |
| Previous Daily Low | 0.6362 |
| Previous Weekly High | 0.642 |
| Previous Weekly Low | 0.6324 |
| Previous Monthly High | 0.6437 |
| Previous Monthly Low | 0.6204 |
| Daily Fibonacci 38.2% | 0.6404 |
| Daily Fibonacci 61.8% | 0.6388 |
| Daily Pivot Point S1 | 0.6383 |
| Daily Pivot Point S2 | 0.6337 |
| Daily Pivot Point S3 | 0.6313 |
| Daily Pivot Point R1 | 0.6452 |
| Daily Pivot Point R2 | 0.6476 |
| Daily Pivot Point R3 | 0.6522 |


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If you have the greasemonkey or tampermonkey extension for your browser, click here to install the scripts.
You could also use the script from your bookmark by:
Drag the following link to your bookmarks: Kantv-helper
Or copy following code then create a new bookmark:
Once installed, you could simply inject the helper script via the bookmark to active it every time you need it.
This allow you to use this script on the browsers that doesn't support extensions, such as Edge on xbox.
I known it's hard to do so on Xbox. My solution is that using Xbox mobile app as text input to copy and paste the script into a bookmark.
If you are using iPhone or iPad and watch movies on safari browser. You may install this Shortcuts: Kantv Helper. And use it from "Share" sheet, when you are blocking by ads or QRCodes.
Thanks to Alan for providing this idea.
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! DART software - Copyright UCAR. This open source software is provided ! by UCAR, "as is", without charge, subject to all terms of use at ! http://www.image.ucar.edu/DAReS/DART/DART_download ! ! DART $Id$ !----------------------------------------------------------------------- !> seaice_aggre_to_obs_netcdf !> This program creates an observation sequence file that has a synthetic !> observation at every location in the netCDF file. !> 'make_obs_aggre.ncl' was used to add noise to a cice state which is !> then used as input to this program. !> !> An alternative method would be to use this program to create an !> observation sequence file with dummy values at each location and use the !> resulting 'obs_seq.in' as input for running 'perfect_model_obs'. !> This method would not require the use of ncl, but would require running !> 'perfect_model_obs'. !> !> Credits: Yongfei Zhang - University of Washington. !----------------------------------------------------------------------- program seaice_aggre_to_obs_netcdf use types_mod, only : r8 use utilities_mod, only : initialize_utilities, finalize_utilities, & find_namelist_in_file, & check_namelist_read, nmlfileunit, do_nml_file, & do_nml_term use time_manager_mod, only : time_type, set_calendar_type, & set_date, set_time, get_time, GREGORIAN, & operator(>=), operator(-), operator(+) use location_mod, only : VERTISSURFACE use obs_sequence_mod, only : obs_sequence_type, obs_type, read_obs_seq, & static_init_obs_sequence, init_obs, & write_obs_seq, init_obs_sequence, get_num_obs, & set_copy_meta_data, set_qc_meta_data use obs_utilities_mod, only : create_3d_obs, add_obs_to_seq, getdimlen use obs_kind_mod, only : SAT_SEAICE_AGREG_CONCENTR use netcdf_utilities_mod, only : nc_open_file_readonly, nc_close_file, nc_check use netcdf implicit none character(len=*), parameter :: routine = 'seaice_aggre_to_obs_netcdf' integer :: n, i, j, oday, osec, rcio, iunit, otype, io integer :: num_copies, num_qc, max_obs, iacc, ialo, ncid, varid integer :: axdim, aydim integer :: along_base, across_base integer, allocatable :: qc_array(:,:) real(r8), allocatable :: tmask(:,:) ! float tmask:comment = "0 = land, 1 = ocean" ; character(len=128) :: varname logical :: file_exist, first_obs real(r8) :: temp, qc, wdir, wspeed, werr, thiserr real(r8) :: uwnd, uerr, vwnd, verr real(r8) :: dlon, dlat, thislon, thislat real(r8), allocatable :: lat(:,:), lon(:,:) real(r8), allocatable :: seaice_concentr(:,:) type(obs_sequence_type) :: obs_seq type(obs_type) :: obs, prev_obs type(time_type) :: comp_day0, time_obs, prev_time ! namelist with default values integer :: year = 2000 integer :: doy = 1 real(r8) :: terr = 0.15_r8 character(len=256) :: seaice_input_file = 'seaicedata.input' character(len=256) :: obs_out_file = 'obs_seq.out' character(len=256) :: maskfile = 'cice_hist.nc' logical :: debug = .false. ! set to .true. to print info namelist /seaice_aggre_to_obs_nc_nml/ year, doy, terr, & seaice_input_file, obs_out_file, & maskfile, debug ! ------------------------ ! start of executable code ! ------------------------ call initialize_utilities(routine) call find_namelist_in_file('input.nml', 'seaice_aggre_to_obs_nc_nml', iunit) read(iunit, nml = seaice_aggre_to_obs_nc_nml, iostat = io) call check_namelist_read(iunit, io, 'seaice_aggre_to_obs_nc_nml') ! Record the namelist values used for the run if (do_nml_file()) write(nmlfileunit, nml=seaice_aggre_to_obs_nc_nml) if (do_nml_term()) write( * , nml=seaice_aggre_to_obs_nc_nml) ncid = nc_open_file_readonly(seaice_input_file, routine) ! get dims along and across the swath path call getdimlen(ncid, 'ni', axdim) call getdimlen(ncid, 'nj', aydim) ! remember that when you ncdump the netcdf file, the dimensions are ! listed in C order. when you allocate them for fortran, reverse the order. allocate(seaice_concentr(axdim, aydim)) allocate( lat(axdim, aydim)) allocate( lon(axdim, aydim)) allocate( tmask(axdim, aydim)) allocate( qc_array(axdim, aydim)) varname = 'aice' io = nf90_inq_varid(ncid, varname, varid) call nc_check(io, routine, 'nf90_inq_varid "'//trim(varname)//'"') io = nf90_get_var(ncid, varid, seaice_concentr) call nc_check(io, routine, 'nf90_get_var "'//trim(varname)//'"') !! obtain lat and lon varname = 'lat' io = nf90_inq_varid(ncid, varname, varid) call nc_check(io, routine, 'nf90_inq_varid "'//trim(varname)//'"') io = nf90_get_var(ncid, varid, lat) call nc_check(io, routine, 'nf90_get_var "'//trim(varname)//'"') varname = 'lon' io = nf90_inq_varid(ncid, varname, varid) call nc_check(io, routine, 'nf90_inq_varid "'//trim(varname)//'"') io = nf90_get_var(ncid, varid, lon) call nc_check(io, routine, 'nf90_get_var "'//trim(varname)//'"') call nc_close_file(ncid, routine, 'data file') ! read in ocean/land mask from a different file. ncid = nc_open_file_readonly(maskfile, routine) varname = 'tmask' io = nf90_inq_varid(ncid, varname, varid) call nc_check(io, routine, 'nf90_inq_varid "'//trim(varname)//'"') io = nf90_get_var(ncid, varid, tmask) call nc_check(io, routine, 'nf90_get_var "'//trim(varname)//'"') call nc_close_file(ncid, routine, 'mask file') ! convert -180/180 to 0/360 where (lon < 0.0_r8) lon = lon + 360.0_r8 ! time setup call set_calendar_type(GREGORIAN) !! all obs in a single file are the same time. comp_day0 = set_date(year, 1, 1, 0, 0, 0) time_obs = comp_day0 + set_time(0, doy) ! extract time of observation into gregorian day, sec. call get_time(time_obs, osec, oday) ! There's no actual "vertical" layers. But the 3rd dimension in seaice is category. ! ------------------------- ! each observation in this series will have a single observation value ! and a quality control flag. the max possible number of obs needs to ! be specified but it will only write out the actual number created. max_obs = axdim*aydim num_copies = 1 num_qc = 1 ! call the initialization code, and initialize two empty observation types call static_init_obs_sequence() call init_obs(obs, num_copies, num_qc) call init_obs(prev_obs, num_copies, num_qc) first_obs = .true. ! create a new, empty obs_seq file. you must give a max limit ! on number of obs. increase the size if too small. call init_obs_sequence(obs_seq, num_copies, num_qc, max_obs) ! the first one needs to contain the string 'observation' and the ! second needs the string 'QC'. call set_copy_meta_data(obs_seq, 1, 'observation') call set_qc_meta_data(obs_seq, 1, 'Data QC') ! if you want to append to existing files (e.g. you have a lot of ! small text files you want to combine), you can do it this way, ! or you can use the obs_sequence_tool to merge a list of files ! once they are in DART obs_seq format. ! ! existing file found, append to it ! inquire(file=obs_out_file, exist=file_exist) ! if ( file_exist ) then ! call read_obs_seq(obs_out_file, 0, 0, max_obs, obs_seq) ! endif ! we have to pick an error range. since this is a seaice cover fraction ! observation, the valid values should go from 0 to 1.0, so pick 0.1 for now. qc = 0.0_r8 ! we will reject anything with a bad qc qc_array = 0 ! making synthetic observations so assume every observation is good seaice_concentr = seaice_concentr/100.0_r8 alongloop: do j = 1, aydim acrossloop: do i = 1, axdim if (debug) print *, 'start of main loop, ', iacc, ialo !! check the lat/lon values to see if they are ok if ( lat(i,j) > 90.0_r8 .or. lat(i,j) < 40.0_r8 ) cycle acrossloop if ( lon(i,j) < 0.0_r8 .or. lon(i,j) > 360.0_r8 ) cycle acrossloop if ( seaice_concentr(i,j) > 1 ) cycle acrossloop ! the actual data values are denser, so inner loop here if ( qc_array(i,j) /= 0) cycle acrossloop !reserve for future quality control if ( tmask(i,j) < 0.5_r8) cycle acrossloop !do not convert if it's a land grid !>@todo possibly use a higher QC value for suspicious observations ! One strategy would be to assign suspicious observations a higher ! QC value - this would allow the "input_qc_threshold" namelist to control ! whether or not the observation would be assimilated as opposed to having ! to modify source code and create multiple versions of the obs_seq file. ! if (seaice_concentr(i,j) < 0.01_r8 .or. seaice_concentr(i,j) > 1.0_r8) cycle acrossloop thislat = lat(i,j) thislon = lon(i,j) !>@todo maybe thiserr = max(seaice_concentr(i,j)*terr, 0.05_r8) thiserr = seaice_concentr(i,j)*terr if (seaice_concentr(i,j) == 0.0_r8) thiserr = 0.05_r8 ! make an obs derived type, and then add it to the sequence call create_3d_obs(thislat, thislon, 0.0_r8, VERTISSURFACE, seaice_concentr(i,j), & SAT_SEAICE_AGREG_CONCENTR, thiserr, oday, osec, qc, obs) call add_obs_to_seq(obs_seq, obs, time_obs, prev_obs, prev_time, first_obs) if (debug) print *, 'added seaice obs to output seq' end do acrossloop end do alongloop ! if we added any obs to the sequence, write it out to a file now. if ( get_num_obs(obs_seq) > 0 ) then if (debug) print *, 'writing obs_seq, obs_count = ', get_num_obs(obs_seq) call write_obs_seq(obs_seq, obs_out_file) endif deallocate(seaice_concentr, lon, lat, qc_array, tmask) ! end of main program call finalize_utilities() end program seaice_aggre_to_obs_netcdf ! <next few lines under version control, do not edit> ! $URL$ ! $Id$ ! $Revision$ ! $Date$


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This handout will help you understand how paragraphs are formed.
- LIFESTYLE
- September 24, 2017
This handout will help you understand how paragraphs are formed.
- TECHNOLOGY
- September 24, 2017
These sentences are selected from various online news.
September 24, 2017These sentences are selected from various online news.
September 24, 2017These sentences are selected from various online news.
September 24, 2017These sentences are selected from various online news.
September 24, 2017These sentences are selected from various online news.
September 24, 2017These sentences are selected from various online news.
September 24, 2017MORE NEWS
It is usually composed of several sentences that together develop one.
- FAMILY
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- LIFESTYLE
- September 24, 2017
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- September 24, 2017
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It is usually composed of several sentences that together develop one.
- TECHNOLOGY
- September 24, 2017
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Excepturi debitis suscipit nesciunt nihil deleniti dolorum reiciendis aspernatur recusandae in, dolore quod pariatur......
Jamy : These sentences are selected from various online news....


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Crime continues to be a problem in East Timor. There have been a number of attacks on foreigners in Dili, including bag-snatchings, during the hours of daylight as well as at night.
There have been incidents of piracy and armed robbery against ships in neighbouring waters. Mariners should be vigilant.
There has been unrest at various times in the past, but currently all is peaceful there. However, the latest travel advisories should be checked before visiting the country.
April 2016.
Brunei Bay Radio operates a regular voice broadcast sked of METAREA and local coastal forecasts for SE Asia waters, the NW Pacific and eastern Indian Ocean. For details of Brunei Bay Radio broadcast skeds and frequencies, see http://www.bruneibay.net/bbradio/bbrschfvoice.htm and http://www.bruneibay.net/bbradio/bbrscweathMSIbcasts.html
For links to free global weather information, forecast services and extreme weather information see the Noonsite Weather Page
Dili * , Pante Macassar (Oe-cusse)
* indicates port of entry


Roadmaps
Below is the current road map for the Highway Framework. All of these are subject to change, but we want to be as transparent as possible in planning so that we can gather input from the community. Any project not in the list is considered stable and not in need of changes in the next 6 months.
Highway.Data
vNext – Time line – Q4 2013
- By end of the year all features release to have written tutorials, and the API to have updated documentation
- By end of the year EF 6.0 major features that need additional work in the framework will be supported and documented
vNext + 1 – Time line – Q1 2014
- Context and Repository will have factories for creation that control lifetime of the objects
- Projection based Scalars – Scalars will be converted to projection based to allow for SQL output,
- Documentation – Video Tutorials for 80% features
Highway.Insurance
vNext – Time line – Q4 2013
- By end of the year all features release to have written tutorials, and the API to have updated documentation
- Version Support for VS 2013 APIs
vNext + 1 – Time line – Q1 2014
- Video Tutorials for 80% features
Highway.Pavement
vNext – Time line – Q4 2013
- By end of the year all features release to have written tutorials, and the API to have updated documentation
Highway.MVC – New Project
vFirst – Time line – Q4 2013
- Package a set of classes that allow for MVVM Model hydration to Knockout or Angular by default from MVC Model
- All feature documentation and usage video tutorials
Highway.OnRamp.MVC.MVVM – New Project
vFirst – Time line – Q4 2013
- OnRamp to drop MVVM wire up and folder structure into any MVC project – Even Existing
- Video to walk through basic structure
Highway.OnRamp.MVC
vNext – Timeline – Q4 2013
- Documentation of all current features (70%+ complete already)
- Reorganize solution structure to move most inserted classes into an App_Infrastructure folder
- Introduce default conventions for “Post” and “Get” actions to be limited to HttpPost and HttpGet respectively via Filter injection.
Highway.RoadCrew
vFirst
- Implement all currently listed stories/issues to establish a great foundation
- Document all those features on the website, as completed.


The correction lower in DXY appears to have met decent contention in the 97.70/65 band, or fresh 2-week lows, so far.
Any attempt of recovery should initially target the key 100-day SMA in the 98.00 neighbourhood ahead of the 55-day SMA, today at 98.25 and ahead of last week’s tops in the mid-98.00s.
If the selling impetus gathers traction, the next support is located at weekly lows in the 97.70/65 band ahead of the critical 200-day SMA at 97.55. As long as this area holds, the constructive view on the buck is expected to remain unchanged.


Random Number Generation¶
Why not Math.random()
?¶
The JavaScript’s native Math.random()
function is not suited for Discrete Event Simulations, since:
- The
Math.random()
function cannot be seeded. There is no way to guarantee that the same random stream will be produced the next time the script is executed. - There is only one stream of random numbers. Statistics purists frown upon when two independent random distributions are drawn from same seed.
- The javascript library provides only the uniform probability distribution function. In DES, as also in many other scientific applications, there is a need for other kinds of distributions, such as exponential, gaussian, pareto etc.
- The native
Math.random()
does not use (at the time of writing) the arguably better Mersenne Twister algorithm for random number generator (see Mersenne Twister website and Wikipedia article).
The Sim.Random
Library¶
The Sim.Random
library uses the Mersenne Twister algorithm for generating random number stream, and is based on the JavaScript implementation by Makoto Matsumoto and Takuji Nishimura (code).
The original code is wrapped around as a javascript class and there can be multiple objects each representing different random number streams. For example,
/* Demonstrate that random number streams can be seeded,
* and multiple streams can be created in a single script. */
var stream1 = new Sim.Random(1234);
var stream2 = new Sim.Random(6789);
stream1.random(); // returns 0.966453535715118 always
stream2.random(); // returns 0.13574991398490965 always
In addition, the Sim.Random
library supports following probability distribution functions:
API Reference¶
-
class
Sim.
Random
([seed])¶ Arguments: - seed (integer) – An optional seed value. If this argument is not provided, then the seed value is set to
new Date().getTime()
.
- seed (integer) – An optional seed value. If this argument is not provided, then the seed value is set to
-
Sim.Random.
random
()¶ Returns a uniformly generated random floating point number in the range
[0, 1.0)
.
-
Sim.Random.
exponential
(lambda)¶ Exponential distribution.
lambda
is the rate (inverse of mean) for the distribution.lambda
is a required parameters, and must be non-negative and non-zero.
-
Sim.Random.
gamma
(alpha, beta)¶ Gamma distribution.
alpha
is sometimes also known as shape of the distribution, whilebeta
as the scale. Both arguments are required.This function is adapted from Python 2.6 implementation of
random.py
.
-
Sim.Random.
normal
(mu, sigma)¶ Normal (or Gaussian) distribution.
mu
is the mean of the Gaussian probability density function, andsigma
is the standard deviation. Both parameters are required.
-
Sim.Random.
pareto
(alpha)¶ Pareto distribution. The
alpha
parameter is required.
-
Sim.Random.
triangular
(lower, upper, mode)¶ Triangular distribution. The random number are generated between the range (
lower
,upper
) withmode
as the mode value. All three parameters are required.
-
Sim.Random.
uniform
(lower, upper)¶ Uniform distribution. Returns a uniformly generated random number in the range [
lower
,upper
). Both lower and upper arguments are required.
-
Sim.Random.
weibull
(alpha, beta)¶ Weibull distribution. Both
alpha
andbeta
parameters are required.