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03-01-2019 08:29 PM - edited 03-02-2019 10:10 AM
I really enjoy Katie McGee as a host, nice voice, pleasant personality, and knows the products. I like Gabrielle too...
@maximillian wrote:
Katie and Gabrielle should get more on-air time, IMO. Less time is in order for Jane T., Shawn and Amy.
And please add KL to your list of MUST NOT WATCH TV....she now seems to be doing her best imitation of SK lately with an extra bit of silliness thrown in..........
More Katie and Gabrielle PLEASE!!!!
I really miss Katie and Gabrielle together on the early morning fashion shows!
Graver is most annoying the way she prances around and flaunts her figure
@MrSour wrote:
Graver is most annoying the way she prances around and flaunts her figure
"Irrational exuberance" is how l would describe it. That was an expression made famous in the 1990s by then-Federal Reserve chairman Alan Greenspan, describing the dot-com bubble. Lol.
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Ever try something and have super high hopes? Me too. I've always wanted one of these concealer style palettes that would let me mix up my makeup game and conceal and highlight my face. I picked up this one from Makeup Revolution as I'm generally always impressed with their products and they're very affordable too.
The palette actually has a great selection of shades and when you swatch them they feel very creamy and easy to blend. The trouble comes when I actually apply this to my face. Maybe its just my face, and you can let me know if you've tried this palette, but I just find the concealers very dry and they refuse to blend into the skin. Its very annoying and I've tried a million different ways to try and apply them to the skin but every time my face just looks scaley.. even when I use them on the most oily parts of my skin. Its really strange and I've really tried hard to love this palette but for me it just doesn't work what so ever. The most success I've had is from using a brush but even then it doesn't look presentable enough to go out in public with. I wore this concealer around the house to see if it would look better after being on for a little while but much to my disappointment it was a horrible creasy mess and the concealers had virtually vanished within a few hours. This palette is super affordable and if you've already got some pretty flawless skin they might work out for you, but for me its a palette I won't be using. I think I'll stick to eyeshadows when I use Makeup Revolution!
Makeup Revolution Ultra Cover and Conceal Palette – Available here

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San Francisco
Chabaa Thai Cuisine 420 Geary St./Mason St., downtown, (415) 346-3121. L-D daily.
Diners enter a narrow walkway past the tiny kitchen when entering the very small dining room tucked in the back here. I was amazed by the deliciousness that came out of that small cooking space. We chose #16 tom ka soup with coconut milk and mushrooms to start. It was followed quickly by #22 pad ma kuer, a stir-fry of eggplant, sweet basil, and choice of meat (I like the chicken) plus sides of sticky rice and cucumber salad. There are extensive vegan-vegetarian options, but you need to ask for that menu. If you like heat, be sure to request the condiment tray with its wonderful hot green pepper rounds, spicy red sauce, and minced peanuts. Service is fast and pleasant.
More things to do in San Francisco
Way more things to do in San Francisco.
More ideas for exploring Northern California.
images ©2016 Carole Terwilliger Meyers


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Dateline TV Producer Tested for Chemicals - BPA, Triclosan and Phthalates. The Products We Use, Matter.
I post this not to entice you into the fear, doubt and confusion of big media but to help you learn about some of the reasons to avoid plastics and chemicals in your daily lifestyle and how much this could assist you and your family toward better health. ~Amandha Vollmer
By Mae Wu
Did you catch the Dateline episode yesterday? It was a great report. The producer Andrea Canning wanted to see how her daily behavior could affect the levels of bisphenol A (BPA), phthalates and triclosan in her urine.
First, she found her baseline numbers, which were around the national average. Then she tried to eliminate these chemicals from her daily use—ate fresh fruits and veggies, used unscented cosmetics, avoided antibacterial soap and avoided plastic with the #7 recycling symbol. When she was tested again, her levels fell to almost zero. The next day, she tried to boost her numbers again by doing normal everyday things—microwaved her oatmeal in a plastic cup, had canned soup and vegetables for lunch and dinner, put on make-up with fragrance, drank a V-8 and a diet Coke in a can, washed her hands with Dial soap and brushed her teeth with Colgate Total. The result? Her numbers spiked.
She also tested levels in her kids. Her six month old baby had levels of triclosan that were 10 times higher than the national average; her toddler had levels of triclosan that were 100 times higher than the national average. Presumably her baby isn't washing her hands with antibacterial soap or brushing her teeth with Colgate Total. When I asked Andrea Canning (via twitter) where she thought the high levels of triclosan came from, she didn't know.
Triclosan is a stupid use of a toxic chemical. As my colleagues Gina Solomon and I and have blogged before, antibacterial soap containing triclosan is neither safe nor effective. (Read our factsheet and other materials).
But here's a little good news on triclosan. Last week, we got an important win in court on our lawsuit against Food and Drug Administration (FDA) on triclosan. As my colleague Sarah Janssen explained, in 1978, the FDA proposed a rule that would have prohibited triclosan (and other chemicals) from being used in hand soaps because it was not shown to be safe or effective. But companies were allowed to keep selling soap containing triclosan until the rule was finalized.
Fast forward 35 years: FDA still has not finalized the rule, and the antibacterial soap industry has exploded. The Natural Resources Defense Council (NRDC) sued FDA for its failure to protect the public health. The District Court in the Southern District of New York found that NRDC members who were exposed to triclosan soap at work could simply avoid triclosan by carrying soap in their pockets and dismissed the case. Fortunately, this week, the Second Circuit Court of Appeals disagreed with the district court. This means that our case gets to continue and we may just finally get a final rule by the FDA.
The news on BPA isn't as good. Check out the science on BPA. We are all eating it when we eat or drink anything that comes out of a can. People are also likely being exposed from thermal paper receipts which are coated with BPA. The FDA did ban the use of BPA in baby bottles and sippy cups, but that was at the behest of the chemical industry. Tellingly, it only took FDA nine months to agree to industry's request. But public interest groups ask the FDA to take steps to protect public health, the only response is silence.
In the meantime, in response to public's demands, more and more manufacturers are moving away from BPA. Unfortunately, "BPA-free" doesn't necessarily mean safe. One of the most common replacements is BPS—a chemical cousin to BPA which is also estrogenic. This just highlights the fact that the FDA is failing to identify and regulate sources of exposure to chemicals which have been identified as being harmful to human health.
And finally, phthalates: a new study finding phthalates in our food shows that even when you do the "right" thing, it is exceeding difficult to eliminate phthalate exposure.
Hopefully, with last night's coverage on Dateline, more people will be wary of all the chemicals we are being exposed to through our common everyday products. And they will see that the federal agency whose mission is to protect public health has done nothing to step in and help us. Check out our Fix FDA page.
WATCH THE VIDEO HERE: http://ecowatch.com/2013/03/25/dateline-tv-producer-tested-for-chemicals/
Visit EcoWatch's FOOD and BIODIVERSITY page for more related news on this topic.
Yummy Mummy Emporium Blog brings you great articles and information to make healthy decisions for your family.
Amandha D. Vollmer
This creative mompreneur herbalist
May 2020


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Martyn Iles | February 06, 2018
As the incoming Managing Director, it is difficult to put into words the gratitude I feel towards Lyle Shelton for his leadership and courage.
Working in close quarters with him over the last three and a half years, I've admired his determination, energy and boundless optimism in the face of immense opposition.
God brought Lyle to ACL at just the right time, and in the same way, he seeks to follow the Lord's leading by stepping into the world of partisan politics. Watch this space.
We are living in a crucial time for our nation and for the Church.
Changing the definition of marriage represented a watershed moment for Australia. The consequences we forewarned will gradually emerge, and our nation is just a little bit less free than it was a few months ago.
But by the grace of God, we have come through that campaign in our strongest position to date.
We helped to shift over 1.5 million votes in 90 days. That is almost unheard of in Australia's political history.
The 'no' vote was larger than the current primary vote of either major party.
We have a rapidly growing supporter base of 110,000. A huge number of you donate and volunteer.
Simply put, the infrastructure and experience we have acquired in recent times sees us in our strongest position ever.
We have seen just a glimpse of what our movement could look like when we work together. Our challenge now is to build on that momentum to transform a one-off campaign into an enduring force.
And with God's help, I know that we can do it.
Be encouraged - there is a very large, passionate, vocal constituency who, like you, care deeply about issues concerning faith and family.
From where I sit, I don't see the end, but a beginning.
My number one priority will be reaching out to churches, engaging with congregations, and equipping Christians to become advocates and activists for a more righteous and just Australia.
Protecting religious freedom for all Australians is at the top of the agenda.
I can tell you, from my time as Director of ACL's Human Rights Law Alliance (HRLA), that everyday Christians are coming under fire simply for living out their faith.
In the short time since HRLA was founded, we have been involved in over 30 legal cases working to defend the rights of believers facing persecution for their faith.
These are mums and dads, sons and daughters living in Australia who are being singled out and victimised for their faith – at school, university and at work.
These chilling cases include:
The Turnbull Government's review of religious freedoms is an important opportunity to highlight the need for much greater protections for religious freedom – but this will only be the start of a longer, more important and profound campaign.
Together we must continue the fight for the fundamental freedom to believe and live out our faith without fear of harassment or intimidation.
This kind of freedom is at the heart of the scriptural command to pray for our government. The Apostle Paul is clear – we should pray for the ability to live godly lives in peace and for the freedom to spread the gospel (1 Tim 2:1-4).
Paul and Timothy had limited chances to complement their prayers with political action, but in a democracy we can do exactly that. This is a blessing we must not waste.
Freedom of religion must continue to be a key pillar of ACL's work.
Our freedom to live out our beliefs is so crucial because the law is so often getting it wrong on fundamental issues. What the law now says about marriage is just one example:
ACL will continue to be your strong voice for the truth on these crucial questions of justice for our time.
Recently I was reading in Isaiah where God accuses Israel of substituting what is right for what is wrong, and what is wrong for what is right (Isa 5:20). As I consider the New Testament mandate for governments, to reward what is good and punish what is wrong (Rom 13:3), I wonder whether we are now making the same mistake that Israel made so long ago.
Are our laws punishing good? And sanctioning what is wrong?
In crucial times such as these, we must continue to be a strong voice for the values that are consistent with all that is true and good. As I have often said when speaking around the country, we must keep the light on.
This is demonstrated perhaps no more clearly than through some of these very issues.
For example, a few months ago I read a heart-breaking legal case. It concerned a 15-year-old girl who was approved for a double mastectomy because she felt like she was a boy. Her body will be permanently mutilated in the name of gender ideology.
The liberating truth for that young girl is that God made us male and female in His image. But when the truth is stifled; when the light goes out; when right is replaced by wrong … there is darkness and suffering.
You and I must continue to be a voice for values in such crucial times.
Someone must stand up, and if not us, then who?
That's why I ask you again earnestly to pray and continue your faithful support for ACL as we enter a new, incredibly important chapter.
Meanwhile, I commit to serving you in this role to the greatest of my abilities, under God, for His glory.
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Estimation and Accuracy of Origin-Destination Highway Freight Weight and Value Flows
Paul Metaxatos
University of Illinois at Chicago
This paper proposes a spatial interaction modeling framework and implements a maximum likelihood estimation of highway freight weight and value flows using the gravity model. The computation of the standard error of the flow estimates provides the basis for measuring the level of accuracy of the estimates. The results provide evidence of the suitability of gravity models for freight forecasting given the excellent fit and the small variances.
The measurement of freight movements requires tracking freight flows across geographic and political boundaries. This is a particularly challenging task given the current capabilities for state and regional data acquisition. Various mathematical approaches have been implemented (Memmot 1983; USDOT 1996; Cambridge Systematics 1997) to circumvent this problem, but none, to the best of this author's knowledge, proposes a measure to assess the accuracy of the computed flows.
This paper proposes to fill this gap using developments in spatial interaction modeling that have not been demonstrated on a large scale to date. The methodology computes maximum likelihood flow estimates and obtains their covariance matrices that, in turn, may be used to obtain confidence intervals and carry out certain tests of hypotheses. The approach can accommodate the large number of origins and destinations typically encountered in freight (and passenger) travel forecasting.
The methodology was applied to highway freight weight and value flows of international trade traffic between seaports or border ports and destination states (see Metaxatos (2002) for details). The variances of the flow estimates computed were remarkably small. The demand for freight transportation flows can then be estimated within a desired confidence level. Moreover, the empirical analysis undertaken provides evidence that the theoretical framework proposed in this paper is rich enough for freight demand forecasting applications.
Commodity shipments in this paper are thought to be realized patterns of spatial interactions that typically result from many independent decisions by individual firms, each constituting a relevant subsystem within the economy as a whole. Hence, if the travel behavior of each firm is modeled as a very small interaction process, the resultant interaction process can be taken to be the superposition of all these processes. It may be argued that for large collections of small frequency processes, the resulting superimposed process is approximately Poisson and, therefore, completely characterized by its associated mean interaction frequencies (Sen and Smith 1995).
In this light, assuming that the observations Nij of shipment weight and value between origin seaports/border ports of entry i and destination states j can be described by the gravity model, then
In this paper, Tij 's (the stochastic term) are interpreted as the expected international trade traffic flow (in terms of weight and value) carried by highway from external station i to state j. The Ai 's are factors related to the origin zone i and the B j ' s are destination-related factors. The Fij 's are factors that reflect the separation between i and j. A common form that is general enough for most applications is
This form is called an exponential form and are different measures of separation, while θk 's are parameters to be estimated. Potential measures of separation include travel time, distance, generalized costs, etc.
In the gravity model, observable quantities Ni* = Σj Nij,N*j = Σi Nij,Nij and their expected values Ti*, T*j, and Tij are described by means of an underlying structure consisting of unobservable quantities Ai, Bj, and Fij. Similar situations abound in statistics. In moving average models, for example, observations are described by means of unobservable parameters. A like situation exists in analysis of variance models.
Although the origin and destination factors are unobservable, they do have physical interpretations. For example, if for some origin i, there are two destinations j and j ' such that Fij = Fij', then Tij /Tij' = Bj /Bj '. Thus other factors being equal, Tij is proportional to Bj (but, in general, not proportional to T*j), and is called the attractiveness of j. Similarly, the origin factor Ai may also be called the emissiveness of i.
Clearly, BjFij is the effect of the destination factor Bj at i , or the accessibility of j as perceived from i . This is a spatial analogy of the temporal concept of present value in economics, where a dollar earned in n years in the future is worth only (1 + σ)n now, where σ is the interest rate. Similarly, AiFij is the effect of the origin factor Ai at j . The sum αi = ΣjBjFij may be called the total accessibility of all destinations at i , and the sum βj = ΣiAiFij may be called the total accessibility of all origins at j . If, for example, Ti* is kept fixed as αi increases, the push Ai decreases. Thus, as the competition αi from the destinations increases, the push at i decreases. From the point of view of someone at i , αi measures accessibility; from the viewpoint at j , it measures competition. Similar statements can be made about Bj.
Maximum Likelihood Estimation
The model (1) will be estimated using maximum likelihood (ML). Maximum likelihood estimates have desirable asymptotic properties (consistency, efficiency, and asymptotic normality) and are robust to distributional assumptions for realistic departures from the Poisson assumption (note that the multinomial distribution leads to identical estimates with the Poisson distribution). Furthermore, they are essentially unbiased even for a very small sample of flows (Sen and Smith 1995).
Under some mild conditions (Sen and Smith 1995), the ML estimate of ζ = (A (1),...,A (i ), B (1),...,B (J ), θ1 ,...,θ Q )´ exists and that of θ is unique. The estimates of A and B are not unique; however, if one A (i ) or B (j ) is chosen to be an arbitrary positive number, the remaining A (i )'s and B (j )'s are unique under the previous mild conditions. It can be proved that the ML estimate of ζ results in the solution to the following system of equations
where the operator * indicates summation with respect to the subscript it replaces (e.g., Ti* = ΣjTij, T*j = ΣiTij ). A number of standard numerical methods or more specialized procedures can be used to solve equations (3) through (5). The three procedures adapted for the paper are the Deming-Stefan-Furness (DSF) procedure, the linearized DSF procedure, and the Modified Scoring procedure. An account of the development of the three procedures is given in Sen and Smith (1995). For completeness of the presentation, some of the details for each procedure follow.
The DSF Procedure for Parameters Ai and Bj
The DSF procedure gives values of Tij for any choice of (θ' ), and Ni* ,N*j , with ΣiN i* = ΣjN*j . Generally speaking, this procedure adjusts the rows (columns) of a two-dimensional table in each even (odd) iteration. After choosing an initial value for the column balancing coefficient, , say, the DSF procedure iterates as follows (the index r denotes the iteration number):
where Oi = Ti* , Dj = T*j , and Fij is a function of the separation measures . Upon convergence (see Sen and Smith (1995) for a proof of convergence), the values of Tij are given by
In this paper, we chose a fairly stringent criterion for convergence as follows
where δ = 1012 . The algorithm attained this criterion in less than 100 iterations.
The DSF procedure essentially expresses Tij as a function of θ. These values of Tij could then be used in equation (5) to solve for an updated value of θ. In general, however, as θ changes, equations (3) and (4) could be violated, unless these changes are very small. This is achieved by using a linearized version of the DSF procedure, called the LDSF procedure (Weber and Sen 1985), which is computationally very attractive.
The LDSF Procedure for Tij
Let us assume that we have run the DSF procedure and obtained a good set of Tij that solves equations (3) and (4) for any given θ. This means that Oi = Ti* = Ni* and Dj = T*j = N*j . Define by ΔΟ = (ΔΟ1,...,ΔΟI)' and ΔD = (ΔD1,...,ΔDJ)' to be small changes in the values of Ο = (Ο1,...,ΟJ)' and D = (D1,...,DJ)' , respectively. Also, let ΔFij , be a small change in Fij = exp[ θ'Cij] . It can be proved (Sen and Smith 1995) that the corresponding small change, ΔTij , in each Tij , so that ΔTi* = ΔΟi , and ΔT*j = ΔDj can be obtained by the LDSF procedure, which iterates as follows
for , and r = 0, 1, 2,..., with initial Tij values given by (11)
A proof for the convergence of the procedure is given in Weber and Sen (1985).
Changes in Tij as a Function of a Change in θ
For a small change Δθ in θ and a small change 0 so that ΔΟ = ΔD = 0, it can be proved (Yun and Sen 1994) that an approximation for the corresponding small change ΔTij for each Tij for all and is given by equation 12.
The 's are constants, and Oi = Ti* , Dj = T*j . Therefore, if Tij 's are known, the only unknown in equation (12) is the Δθ . The solution for the Δθ will be the topic of the next section.
Estimation of θ Using the Modified Scoring (MS) Procedure
So far, for an initial value for θ, we obtained Tij (θ) by using the DSF procedure to solve equations (3) and (4). We then changed θ to θ + Δθ and computed, using the LDSF procedure, with Δ0 = ΔD = 0, the corresponding change, ΔTij(θ, Δθ) in Tij (θ) as a function of Δθ.
We are ready now to insert the [Tij(θ) + ΔTij(θ, Δθ)]'s into the left side of equation (5) and solve the resultant equation for Δθ. Inserting Tij + ΔTij in place of Tij in (5) and using (12), equations (3) and (4) would remain approximately satisfied, while obtaining the following system of Q linear equations with Q unknowns (the Δθq's):
This system of equations can be solved by any standard solution method such as Gaussian elimination.
The current solution for θ at iteration r is updated next using the formula
θr = θr-1 + Δθr-1 (14)
If the corrections Δθr-1 have become negligible, the values of θ have been stabilized and the MS procedure terminates. Otherwise, new Tij 's are obtained from the DSF procedure and the MS procedure continues. There is no guarantee that the MS procedure always converges (Sen and Smith 1995), although our computational experience is positive.
Goodness of Fit
Under the previous assumption that observations Nij are independently Poisson distributed, the (Pearson) X2 statistic,
where is an estimate of Tij , is an appropriate measure of the overall fit of a model. Moreover, when is obtained using maximum likelihood, equation (15) has a X2 distribution with df = ij i J K + 1 degrees of freedom (Bishop et al. 1975; Rao 1973).
If , then X2 = Z2 , where
Since E (Nij ) = Tij and because Nij have the Poisson distribution,
var(Nij) = E(Nij Tij)2 = Tij (17)
Therefore, E (Z2) = IJ , where I is the number of origin zones i, and J the number of destinations j . Equivalently, E (Z2 /IJ ) = 1. Thus, the so-called "X2 -ratio," X2 /df , has an expectation that is asymptotically 1. It can be shown (Sen and Smith 1995) that the variance of the X2 -ratio is
Hence, if Tij 's are bounded away from zero (which is the case in exponential gravity models with finite parameters θ), the variance of Z2/IJ→0, as IJ→∞. It follows that when and Tij 's are bounded away from zero, the variance of X2/df→0.
In practical applications, since the Poisson assumption seldom holds perfectly (as is the case here, where every pound or dollar value of shipment does not travel independently of each other pound or dollar value), an X2 ratio less than 2 is a good indication that the gravity model fits the data well (Sen and Smith 1995).
Covariance of Maximum Likelihood Estimates
Covariance of `s
Let small case letters stand for the logarithms of corresponding capital letters (e.g., tij = log [Tij ], a (i ) = log [A (i )], b (j ) = log [B (j )]. The model (1) may be written as
Let M denote the coefficient matrix of the right side of the system of equations (19). The matrix M is not of full rank (Sen and Smith 1995). However, the matrix M(2) obtained by deleting one of the first I + J columns of M is of full rank and has dimension IJ × (I + J + Q 1). Let diag( · ) stand for a diagonal matrix, the diagonal elements of which are given within the parentheses. Then compute the matrix M'(2) · diag(T) · M(2) from the equation
U3 = ((upq )) with , with , with , V1 = diag(T1*,...,TI*) , V2 = ((Tij)) and V3 = diag(T*1,...,T*j 1). Notice that the subscript j in each of the matrices above goes only up to J 1.
Matrix M'(2) · diag(T) · M(2) , a square matrix of dimension (I + J + Q 1), is the covariance matrix of M'(2) · diag(N). This is because the Nij's have independent Poisson distributions and the covariance matrix Cov(N ) of N is diag(T ). It can be shown (Sen and Smith 1995) that the covariance matrix of is
Φ-1· M'(2) · diag(T) · M(2)· (Φ-1)' (23)
Φ = M'(2) · diag(T) · M(2)· diag(1/A(1),...,1/A(I), 1/B(1),...,1/B(J 1), 1,...,1) (24)
Φ-1 = diag(1/A(1),...,1/A(I), 1/B(1),..., 1/B(J 1), 1,...,1) · (M'(2) · diag(T) · M(2))-1 (25)
Notice that using equations (23) through (25), another expression for the covariance matrix of can be written by as follows
diag(1/A(1),...,1/A(I), 1/B(1),..., 1/B(J1),1,...1) ·
(M'(2) · diagT · M(2))-1 · diag(1/A(1),...,1/A(I), 1/B(1),..., 1/B(J1), 1,...,1) (26)
The bottom right Q × Q submatrix of matrix (26) is the estimated covariance matrix of . The bottom right Q × Q submatrix of the inverse of (20) is (Rao 1973)
From equation (26), it follows that equation (27) is the covariance matrix of .
Covariance of ij 's
Having obtained Cov(A ,B ,θ) from equation (23) or using equation (26), and since B (J ) is set equal to a constant, and its variance and covariances involving it are zeros, it can readily be seen that the covariance matrix of , denoted by the symbol Cov() , is
Cov() = Ψ1 · Cov(A,B,θ) · Ψ'1 (28)
Ψ1 = diagT · M(2)(1/A(1),...,1/A(I), 1/B(1),..., 1/B(J), 1,...,1) (29)
and M the coefficient matrix of the right side of the system of equations (19).
Short-Term Forecasting
The shipment of goods is affected by a multitude of factors (USDOT 1996, table 2.1). The weight and value of commodities shipped, characteristics of immediate concern in this study in particular, may be affected by the economy as a whole, globalization of business, international trade agreements, just-in-time inventory practices (weight only), packaging materials (weight only), economic regulation/deregulation, publicly provided infrastructure (weight only), user charges and other taxes, changes in truck size and weight limits (weight only), and technological advances. The discussion below is based on the assumption that, in the short term (e.g., three to five years) the compound effect of these factors on the size of the weight and value characteristics of commodity shipments is consistent with Poisson randomness.
Let the random variable be a future observation1 of the flow from i to j . In the short run, under the assumption that the separation configuration will not change during the forecast period, we may conjecture that and Nij will be highly (serially) correlated. Thus, we may then argue that the variance of the difference of future and present observations will be smaller than the variance of future observations alone. Hence,
var( − Nij) = var() + var(Nij) − 2Cov(Nij) (30)
where var(·) stands for the "variance of" and Cov(·) for the "covariance of," will be small. In such cases, especially if Nij 's are known, Sen and Smith (1995, chapter 5) suggest that it would be preferable to predict ( − Nij)'s and add the predictions to the Nij 's. A possible set of predictions for ( − Nij)'s are ()'s. Thus, if the future is not too far off,
Nij + () (31)
may yield a better prediction than . The computation of can be made easily using the LDSF procedure described earlier.
Other Forecasts
Four separate cases are discussed here. The first case assumes that would be available exogenously, θƒ would be the estimate from the base period assumed to remain unchanged into the forecast period, and the estimates Af (i ) and Bf (j ) could be base period estimates assumed to remain unchanged into the forecast period, or one or both of them could be exogenous. Then, Tij for the forecast period may be estimated by
The calculation of Cov( ) requires the computation of the covariance matrices of the Af (i )'s, Bf (j )'s, and θƒ. For those estimates that remain unchanged from the base period, the appropriate covariance matrix is the one for the base period. For estimates obtained exogenously, the covariance matrix needs to be supplied exogenously. Covariances of estimates obtained from different independent data are usually assumed to be zeros.
The second case assumes that and θƒ would be available as before and the estimates Bf (j ) and could be base period estimates assumed to remain unchanged into the forecast period or could be obtained exogenously. Then, Tij for the forecast period may be estimated by
The second case assumes that and θƒ would be available as before and the estimates Af (i ) and could be base period estimates assumed to remain unchanged into the forecast period or could be obtained exogenously. Then, Tij for the forecast period may be estimated by
The computation of the covariance matrices for the second and third cases is similar to the first case once the appropriate Jacobians with respect to Af (i )'s, Bf (j )'s and θƒ have been obtained. Recall that equation (29) is the respective Jacobian for the first case.
A fourth case, arising when , θƒ, , and are available, requires the use of the DSF procedure to generate the Aƒ (i ) and Bƒ (j ). Then, Tij for the forecast period may be estimated by equation (32). The computation of the covariance matrices for this case is treated in detail by Sen and Smith (1995, p. 440).
It is interesting to observe at this point that origin-destination travel times and/or costs (which depend on routes chosen and traffic congestion on the routes) usually become available only after the gravity model has been applied to forecast flows. This difficulty affects only the forecasting phase (not the estimation phase, when we use base period data for which travel times can be observed or computed using available information) and can be alleviated by combining the distribution and assignment stages of the process into a single stage.
Data Issues
Freight Shipments
Oak Ridge National Laboratory (ORNL) provided two sets of origin-destination flow data for freight shipment weight and value between origin seaports/border ports of entry i and destination states j from the following sources:
- The Transborder Surface Freight Database. This database (http://www.bts.gov/transborder/prod.html) is distributed by the Bureau of Transportation Statistics and contains freight flow data by commodity type and surface mode of transportation (rail, truck, pipeline, or mail) for U.S. exports to and imports from Canada and Mexico.
- The Port Import Export Reporting Service (PIERS) Database. This commercial database (http://www.piers.com/about/default.asp), offered by the Journal of Commerce , offers statistics on global cargo movements transiting seaports in the United States, Mexico, and South America to companies around the globe.
Two matrices, Nij , were developed: one for shipment weight and one for shipment value for each of the two databases with dimensions 128 × 50 and 144 × 50 for the Transborder and PIERS databases, respectively.
The limitations of these two data sources are well documented (Meyburg and Mbwana 2002). A caveat for the Transborder Database is that it is a customs, not a transportation, dataset, resulting in inconsistencies between U.S. and Canadian data and issues related to the accuracy of transshipment data.2 One caveat for using PIERS is that reported origins and destinations may be billing addresses rather than shipment points.
Separation Measures
In identifying specific types of spatial separation that tend to impede or enhance the likelihood of interactions between points of entry and destination sites, the most obvious type involves physical space, as exemplified by travel distance and travel time, which are quantifiable in terms of meaningful units of measurement. ORNL provided two sets with separate impedance matrices, , k = 1, 2 from origin point i to destination county c .
The first dataset included impedances between origin seaports and destination counties, the second set between origin border ports and destination counties. Both measures were computed from ORNL's National Highway Network (NHN). The first of the two measures is the route (network) distance in miles; the second computes a function of travel time for different functional classifications of highway segments and adds these time penalties together while tracing the previous network routes. The previous impedance matrices presented two problems: 1) more than 50% of the cells were empty because not all seaports/border ports of entry are connected to each county through the NHN; and 2) occasionally, freight shipments moved between origin-destination pairs with a missing connection (separation measure).
In order to deal with both problems, we devised and implemented the following stepwise procedure for the distance matrix (the first separation measure, ).
1. Centroid coordinates were computed for all counties nationwide.
2. Spherical distances in miles from each county to every other county.
3. For every destination county with a missing connection to an origin point (seaport/border port of entry), the closest county with an existing connection to an origin point was estimated based on the previous county-to-county distances.
4. The missing connection from an origin point to a destination county was finally computed to be the distance between the same point of origin and the closest destination county augmented by 130% the (airline) distance between the two destination counties (as a proxy to the actual road distance). This simplification was made under the assumption that a missing connection would imply that the destination county is off the NHN and thus would require additional time to be accessed from its closest county on the NHN.
The above procedure resulted in the construction of a synthesized separation measure comprising both route distance (the ORNL estimate) and multiples of airline distance (our estimate). It is important to take a closer look at those two components of the (re-estimated) first separation measure .
The airline distance between origin point i and destination county c , even augmented by 30%, is only an approximation of the actual miles traveled and represents a surrogate for the complex set of factors that express the difficulty of overcoming separation. On the other hand, the route distance for the same origin-destination pair is the total over-the-road distance on a realistic route. As a measure of separation, the route distance provides better accuracy for the eastern half of the limited access highway system of the United States, which has a higher level of complexity resulting in less circuitous routes than in the western half.
Whereas the distance measure developed above is a measure that depends more or less on the physical characteristics of the road link, the impedance measure, a function of link travel time as estimated by ORNL, depends on the special roadway type or certain conditions encountered on the link. ORNL's estimating procedure could not be replicated in this paper for the missing impedances. A surrogate value was computed based on the average speed obtained by ORNL's distance and time estimates, and the synthesized distances.
The procedure classified ORNL's distance and time estimates into 10 deciles. The stratum average speed was computed by the ratio of the average distance and time for that stratum (table 1). Each missing time impedance was then estimated by the ratio of its corresponding distance estimate and the average speed of the stratum to which the distance estimate belongs.
Clearly, this procedure imposes some inconsistency in the imputation of travel times, because the average speed estimate is based on decile groupings of the initial estimates. The consistency of the procedure could be improved if in a second iteration the decile groupings are based on all distances (initial and imputed), but I did not attempt this for this paper.
The previous steps resulted in two re-estimated sets of separation measures: 1) a distance matrix and a travel time matrix between origin seaports and destination counties; and 2) a distance matrix and a travel time matrix between origin points of entry and destination counties. The final step in preparing the separation measures for model estimation was to estimate these measures between origin points and destination states rather than counties. This was made possible simply by computing for each origin point i and all destination counties in state j the average distance and travel time. That is,
, ,
where n is the cardinality of Cj . Note that had we avoided the intermediate step of origin-to-destination county distance estimation, say, by computing distances to state geographical centers, origin-destination pairs with both ends in the same state would have been indistinguishable in terms of their separation.
Other Relevant Variables
As mentioned earlier, the weight and value of commodities shipped may be affected by a nexus of factors that are either origin-specific, destination-specific, or solely dependent on separation between an origin and a destination. Although study resources did not permit the collection of pertinent data on these factors, it could be interesting to observe how such factors can be accommodated in the proposed theoretical framework for future reference.
For origin-specific and destination-specific factors, Sen and Smith (1995) propose the following exploratory analysis: estimate Ai 's and Bj 's first using the maximum likelihood procedure described earlier, and then use these estimates as the dependent variable values in a model fitting procedure. Thus, the estimates of the Ai 's can be associated with the origin-specific factors, while the estimates of the Bj 's can be associated with the destination-specific factors.
Factors that can be solely attributed to the separation between an origin and destination can be accommodated in a deterrence function, an example of which is indeed the most general exponential function in equation (2). Openshaw and Connolly (1977) have compiled a list of possible functions and empirically compared several of them.
The only decision necessary to apply the procedures described above (i.e., DSF, LDSF, and MS) is the choice of the flow unit. In the case of passenger transportation, a flow unit of 1 (consistent with a Poisson or multinomial distribution assumption) would be reasonable. In the case of freight shipments of goods, a basic unit of flow would appear to be a trainload (for shipments by rail) or a truckload (for shipments by truck). In the absence of mode-specific information as well as information related to the variation in modal size, we experimented with different values and determined an "optimal" (with regard to providing the best model fit) basic unit of flow of 100,000 pounds or dollars. This is not surprising given that the bulk of flows are long-distance shipments usually performed by large3 trucks or rail (on a limited scale for the particular data) with an average shipment value of $2.03 per pound for the Transborder data and $1.39 per pound for the PIERS data. Interestingly, our results appeared to be quite insensitive to the choice of the flow unit, primarily because the flows were inordinately large. This is in agreement with previous work (Sen and Pruthi 1983).
The procedures described above were run to a tight convergence. For each iteration of the MS procedure, the DSF procedure attained a 10E 12 convergence as defined by equation (8) in less than 100 iterations. The MS procedure itself attained a 10E 06 convergence as defined by the right-hand side of equation (13) in less than 20 iterations.
Parameter Estimates and Model Fit for PIERS Data
Separate gravity models were estimated for both seaport-to-state (seaport data) and border port-to-state (transborder) weight and value flows. In particular, for the seaport data, several model specifications were tested based on transformations of the distance and time separation measures, and , respectively, after a careful examination of residuals that showed the presence of outliers.
In the analysis of residuals, two difficulties were addressed. The first difficulty is the unequal variances of residuals, a consequence of the Poisson distribution. This problem was handled by considering, as Cochran suggests (Rao 1973, p. 393), instead of the plain residuals , the components
The second difficulty stems from the very large number of residuals (the number is I × J , the number of all origin-destination pairs). To tackle this concern, we followed a procedure described in Sen and Smith (1995, p. 456) consisting of drawing normal (rankit) plots of residuals. If the residuals are normal, such a plot would lie approximately on a straight line. Points that deviate sharply near the ends were tagged as outliers. Unusual jumps in the plots or other strongly nonlinear shapes could signal the need for transformations of the 's or for additional 's. There are clearly other ways of examining residuals. It is important to note here that the effort to conduct residual analysis in the gravity model case should not be seen as less than that for linear models where residual analysis is routinely carried out.
Indeed, the examination of residuals signaled the need for transformation of the 's. We found the square root transformation provided adequate fit for both weight flow and value flow estimates (table 2). The model provides an excellent fit for the data, because the Chi-square statistic hovers around its expected value of 1. In addition, the cell-to-cell weight flow estimates correlate very well with the data (Pearson correlation coefficient, r = 0.89, p < 0.01. The cell-to-cell value flow estimates also correlate very well with the data (r = 0.98, p < 0.01). Moreover, the weight and value length distributions in figure 1 (1% corresponds to 2,292,872,822 pounds) and figure 2 (1% corresponds to $3,198,123,011), respectively, seem to corroborate the previous results.
Of interest in table 2 is the appearance of with a positive value. This is due to collinearity between the used impedances, distance and travel time, a phenomenon that is known to adversely affect the sign of parameter estimates. Dropping one of the impedances would bias the parameter estimates left in the model. Given the robustness of the maximum likelihood procedure above in collinearity situations, all available impedance measures were retained (Sen and Smith 1995, chapter 5). After all, the sign of would have changed to a negative value had we reparameterized the model and considered instead of travel time as the first impedance measure, the difference between distance and travel time (in appropriate units).
In the end, the model specifications for the weight and value flows, respectively, are
Parameter Estimates and Model Fit for Transborder Data
In the case of Transborder data, we conducted a similar investigation of residuals (as above with the PIERS data) and observed the presence of a few remaining outliers, despite using transformed 's. These outliers were mainly states receiving an unusually large share of shipments compared with other states. The discovery was made after squaring the residuals in equation (35) and adding them together for all origin points of entry for each destination state. Destination states with a large share of shipments had a much larger sum of squares of residuals than other destinations. This was understandable, because these large destination states attract more shipments from longer distances and suggest the use of an additional impedance variable
for the weight flows, and
for the value flows, where δ is 1 for destinations with more than a 10% share in weight (4% in value) and 0 otherwise. In effect, we sought a different parameter estimate for the square root/log of distance for destination states with large shares.
The previous use of the indicator (dummy) variable δ is typical in spatial analysis for the treatment of residuals (Sen and Smith 1995) and introduces the effects of spatial structure on flow patterns (Gensler and Meade 1988; Fotheringham and O'Kelly 1989; Lo 1991), which is not the primary intent of this paper. More complex measures of relative location have been developed and tested empirically (Boots and Kanaroglou 1988; Lowe and Sen 1996). In the end, the model specifications for the weight and value flows, respectively, are
The previous steps removed all remaining outliers. Parameter estimates and goodness-of-fit statistics are shown in table 3. The previous observation regarding the sign of applies. The model fits the data very well, as the Chi-square ratios for both weight and value remain under 2. In addition, the cell-to-cell weight flow estimates correlate very well with the data (Pearson correlation coefficient, r = 0.91, p < 0.01). The cell-to-cell value flow estimates also correlate very well with the data (r = 0.94, p < 0.01). Moreover, the weight and value length distributions in figure 3 (1% corresponds to 767,519,815 pounds) and figure 4 (1% corresponds to $1,565,313,371), respectively, seem to corroborate the previous results.
Computation of Covariance of Estimates for PIERS Data
The previous point estimates of the parameters and the flows were used in the methodology described earlier to obtain the covariance of these estimates. The procedure can accommodate any reasonable number of separation measures, , and the large number of origins and destinations typically encountered in practice.
The computational requirements of the procedure are no longer prohibitive. We were able to obtain the covariance matrix of a 144 × 50 flow matrix, a 7200 × 7200 matrix, in a little more than an hour on a Pentium III, 800 MHz, 512MB RAM laptop computer running a FORTRAN 77 compiler. Replacing Tij 's by their estimates in equation (27), the covariance matrix of for the weight flows from the PIERS dataset was found to be
The correlation between (the parameter estimate for the distance measure) and (the parameter estimate for the travel time measure) is readily apparent from equation (38). The negative sign of the covariances should not be disconcerting. It shows that, if for some small shift in the observations, were to increase, would decrease to "compensate."
Similarly, the covariance matrix of for the value flows from the PIERS dataset was found to be
The correlation between and is similarly apparent from equation (39).
Computation of Covariance of Estimates for Transborder Data
The covariance matrices of from the Transborder dataset for the weight and value flows, respectively, were found to be
These last two covariance matrices in equations (40) and (41) show relatively high correlation between (the parameter estimate for the distance measure) and (the parameter estimate for the travel time measure) and relatively low correlation between (the parameter estimate for the transformed travel time measure) and or . The interpretation of the negative signs is the same as above.
For illustration purposes, an example of the usefulness of the computed covariance matrices for 's in computing confidence intervals is shown in table 4. The table shows a few Nij 's, 's, percentage difference between Nij and , and 90% confidence intervals constructed by adding and subtracting 1.65 times the standard error available from the variances.
The most characteristic and indeed more restrictive feature of the Poisson distribution is the equality between its mean and variance. Many types of spatial interaction phenomena exhibit restricted (variance less than their means) or extra variation (variance greater than their means). Yet, the framework described above is very robust. Its robustness stems from the many types of asymptotic results that establish the Poisson distribution as the unique limiting form for a wide range of interaction processes when the population size increases and the overall influence of each individual interaction decreases.
More specifically, this research demonstrates that, to the extent the behavior of each shipping firm can be thought of as a very small interaction process, the resultant interaction process (i.e., the realized pattern of origin-destination commodity shipments) can be thought of as the superposition of all these processes and thus characterized by gravity models. The limited empirical analysis in this paper confirmed this conjecture and thus establishes an extremely rich framework for future experimentation.
Future applications of the proposed framework could conduct additional exploratory analyses to determine which factors affecting the demand for freight shipments are origin-based, destination-based, or separation-based. Another important issue needing more attention in the future is the requirement that, when the proposed modeling framework is used for forecasting, the travel times and costs used as impedance measures should be consistent with those obtained during the traffic assignment.
In summary, this paper has provided evidence that the movement of freight shipments can now be estimated within a desired confidence level as a result of maximum likelihood estimation of Poisson gravity models. The freight transportation modeler has two procedures available for computing reliable information within a predetermined accuracy: one for computing freight flow estimates and one for computing covariance matrices. These procedures can accommodate any reasonable number of separation measures,, and the large number of origins and destinations typically encountered in practice.
This paper reports on research conducted by the author for the Bureau of Transportation Statistics, U.S. Department of Transportation.
Bishop, Y.M.M., S.E. Fienberg, and P.W. Holland. 1975. Discreet Multivariate Analysis: Theory and Practice. Cambridge, MA: MIT Press.
Boots, B. and P. Kanaroglou. 1988. Incorporating the Effects of Spatial Structure in Discrete Choice Models of Migration. Journal of Regional Science 28:495507.
Cambridge Systematics. 1997. A Guidebook for Forecasting Freight Transportation Demand, NCHRP Report 388. Transportation Research Board, National Research Council.
Fotheringham, A. and M. O'Kelly. 1989. Spatial Interaction Models: Formulations and Application. Studies in Operational Regional Science. Boston, MA: Kluwer Academic Publishers.
Gensler, W. and M. Meade. 1988. Locational and Population Factors in Health Care-Seeking Behavior in Savannah, Georgia. Health Services Research 22:443462.
Lo, L. 1991. Spatial Structure and Spatial Interaction: A Simulation Approach. Environment and Planning A 23:12791300.
Lowe, J. and A. Sen. 1996. Gravity Model Applications in Health Planning Analysis of an Urban Hospital Market. Journal of Regional Science 36:(3)437462.
Memmot, F.W. 1983. Application of Statewide Freight Demand Forecasting Techniques, NCHRP Report 260. Transportation Research Board, National Research Council.
Metaxatos, P. 2002. International Trade Traffic Study (Section 5115): Measuring the Ton-Miles and Value-Miles of International Trade Traffic Carried by Highway for Each State: Estimation of Origin-Destination Flows and Confidence Intervals, Final Report, prepared for the U.S. Department of Transportation, Bureau of Transportation Statistics. March.
Meyburg, A.H. and J.R. Mbwana, eds. 2002. Conference Synthesis: Data Needs in the Changing World of Logistics and Freight Transportation. New York Department of Transportation, Albany, NY. Available at http://www.dot.state.ny.us/ttss/conference/synthesis.pdf.
Openshaw, S. and C.J. Connolly. 1977. Empirical Derived Deterrence Functions for Maximum Performance Spatial Interaction Models. Environment and Planning A 9:10671079.
Rao, C.R. 1973. Linear Statistical Inference and Its Application. New York, NY: Wiley.
Sen, A. and T.E. Smith. 1995. Gravity Models of Spatial Interaction Behavior. New York, NY: Springer-Verlag
Sen, A. and R.K. Pruthi. 1983. Least Squares Calibration of the Gravity Model When Intrazonal Flows are Unknown. Environment and Planning A 15:15451550.
U.S. Department of Transportation (USDOT). 1996. Quick Response Freight Manual, DOT-T-97-10. Washington, DC. September 1996.
Weber, J.S. and A. Sen. 1985. On the Sensitivity of Gravity Model Forecasts. Journal of Regional Science 25:317336.
Yun S. and A. Sen. 1994. Computation of Maximum Likelihood Estimates of Gravity Model Parameters. Journal of Regional Science 34:199216.
Author address: Paul Metaxatos, University of Illinois at Chicago, 412 South Peoria Street, Suite 340, Chicago, IL 60607. Email: email@example.com.
KEYWORDS: freight origin-destination flow estimation, covariance of estimates, gravity model.
1. The superscript f denotes that the quantity is an estimate for the forecast period.
2. See http://www.bts.gov/ntda/tbscd/desc.html, as of January 2004, for more information.
3. Currently, the gross weight limit for a 6-axle combination truck is 80,000 pounds.


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We would like to thank Boo Golding who has developed this wonderful mouth-watering recipe using our British white quinoa (Twitter, Instagram @veganboo_ Facebook: Vegan Boo). With additional thanks to Daniel Alford for the photographs (www.danielalford.co.uk Instagram, Twitter @danielalford_ ).
These Fritters are great eaten hot with a big dollop of the cooling raita or can be eaten cold as a perfect addition to any summer picnic.
Cauliflower makes these fritters low in carbohydrates and the combination of it here with turmeric has been shown in studies to have incredible health benefits.
The quinoa gives them a wonderful nutty taste and a helpful protein boost.
(makes around 20)
First cook the quinoa - as per instructions on the pack
Next make the flax eggs - in a bowl whisk 3 tbs of ground flax seed and 1/2 cup of cold water together, then leave in fridge to set.
Using a regular box grater, grate a medium sized potato in to a bowl with the juice of 1 lemon, cover and place in the fridge to marinate.
Remove florets of cauliflower from the stalk and place in to a food processor, pulse until it resembles rice then transfer to a large bowl.
Next add the spring onions, garlic and chilli, blend until everything is very fine, stopping to scrape the sides as needed.
Sprinkle your spices and salt into the cauliflower and stir well, so everything is a bright yellow and smells delicious.
Mix the remaining ingredients into the bowl with the cauliflower - the quinoa, lemony potato, flax eggs, spring onion mix, and chickpea flour, stir well so that everything is combined.
Dust some chickpea flour onto a clean work surface and using a standard cookie cutter as a guide (approx. 3 inches) spoon around 2 tbsp of the fritter mix into the rounds and lightly pat down into the round using the back of a teaspoon or your fingers. Once flattened sprinkle over some more chickpea flour and whilst pushing the mixture down slowly lift the cookie cutter up and away from your fritter.
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Add the cucumber mix to the bowl, stir well and season with salt.
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Hello, Friends welcome to the worldmirchi.com blog and I am Vinay Patel. Today I want to share something special with you, and it is Phillauri film Dey1 Box Office Collection and review, Cast. Phillauri Film Dey1 Box Office Collection: For the past few weeks, Bollywood has not been good. The only hit is the bride of Badrinath. But many have become disappointed. Anushka Sharma and Diljeet Dosanjh are playing the role. There is no value other than a star. Apart from this, Diljeet Dosanjh is also included. This is a big star in Punjab.
Although the discussion around the film is quite small, some business experts believe it. Anushka Sharma's movie is generally good. Because Anushka Sharma is on the winning streak, Exhibition Officer Akshay Rathi said, "It would be selective, massive multiplex which will see a wide release in 1200 screens in India and should be. Considering the appeal of the film, Full di earns Rs 3 crore on the first day. On the other hand, Amod Mehra, Had a different idea. If it's like 3 crores, so it would be a miracle. There is absolutely no point. It should be only in the media. I am a Good start is not very visible.
Anushka Sharma and Diljit Dosanjh starter Phillauri is staying steady at the box office. Trade analyst Taran Adarsh, who keeps us updated about the latest collection of the films, shared Phillauri's day six box office collections too.
Phillauri All Day box office collection
1 Day 3.00 cr
2 Day 5.20 cr
3 Day 6.03 cr
4 Day 2.94 cr
5 Day 2.05 cr
6 Day 1.81 cr
Total Box office collection: 21.03 cr
It would be better at the beginning because I should start day 1 like Rs 3 crore. It all depends on the content and if it is good then it is good. So the film can do well in the weekend too, But by the evening. If the word of mouth is positive, so it can improve. We do not know how a movie is boring or interesting.
Phillauri Film Diljit Dosanjh Review
Phillauri is a loose film that failed to swallow audiences. Most of the first half bits in bits only Anushka smiles and cries, or when Paulo di and Shashi set fire to screen with their heart-warming chemistry. Nothing is scary than falling in love and the ghost of your memories keeps getting together. But Kanan is experiencing a more specific type of ghostly. She is not disturbed by the memories of a former lover, but in love by the real ghost of another ghost. As a result of this marriage, Shashi is bound to Kanan, who is required to find a way to take care of the unfinished business, which makes him the reason to roam around him
Movie of Phillauri is a winner and it was very clear from the trailer. The idea is spectacularly original, culturally, and has great potential in it. The problem is that, in the trailer, you see only a few more hilarious. Exciting one line plot develops in a two and a half hour film that is full of romantic film tropes. The invisibility of the ghosts can only be laughing. The story between Sasha's past and the presence of Kanan suddenly appears. Spiritual songs are easy on the ears, but emphasising their eyes by adding runtime.
Phillauri Film Review
Love and love in Metering Prasad's helplessness and despair is dear. Diljeet Dosanjh brought his trademark goodness into a defamed role. It is a bit slow and allows the scenes to last as much as they need. I found impatient in many places, and although Suraj Sharma and Mehrin Pirzada keep an eye on the eyes and are very easy for them, surrounded by large Punjabi families. And a horrified female ghost that brings festivals only after the commencement. These three characters have kept the first act of Phillauri. This is seen in the middle of being lightly entertaining and entertaining. A filler is a rural outpost in Punjab.
First, we should clean the air on the basis of our trailers of Phillauri. The discussion about this matter has been discussed in depth in the discussion of how many Anshai Lal's flowers are borrowed from Tim Burton's bride's corpse. And seeing the feelings of their perplexity for their flowers, this film grows towards life.
Phillauri Film Cast
- Anushka Sharma
- Diljit Dosanjh
- Suraj Sharma
- Mehreen Pirzada


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Directions to St. Johann-Alpendorf
Coming from Salzburg, Munich and Vienna, Alpendorf in Pongau's district capital of St. Johann is your quickest entry point to the Snow Space Salzburg ski resort.
At only a 50-minute drive from the City of Salzburg and only 15 minutes from the Austrian motorways, St. Johann-Alpendorf offers perfect conditions for a relaxed journey, no matter if you have planned a hiking holiday in summer or a ski trip in winter.
Arriving by car
With its proximity to the City of Salzburg, it's easy and comfortable to reach St. Johann-Alpendorf by car.
Coming from Vienna: Motorway A1 – exit A10/E47 interchange Pongau – Pinzgauer Bundesstraße B311 via Bischofshofen to St. Johann im Pongau and Alpendorf
Coming from Munich: Motorway A8 towards Salzburg – at interchange Salzburg A1/A10 continue towards Villach/Salzburg Süd – exit A10/E47 interchange Pongau – B311 to St. Johann im Pongau and Alpendorf
Coming from Carinthia, Italy and Slovenia: Tauern motorway A10 – exit A10/E47 interchange Pongau – B311 to St. Johann im Pongau and Alpendorf
Coming from Graz: Motorway A9 – exit 69 Selzthal – Ennstal Bundesstraße B320 towards Radstadt, Schladming, Liezen – Altenmarkt B320 – towards Wagrain on B163
Coming from Zell am See: Bundesstraße 311 to St. Johann im Pongau – B163 to Wagrain
Tips for a safe and comfortable trip:
- Toll sticker: If you plan to use the Austrian motorways, you need a toll sticker, available at all border crossings as well as at service stations and tobacconists. New for 2018: the digital toll sticker.
- Emergency corridor: In case of congestion, drivers on Austrian motorways are obliged to form an emergency corridor in order to make space for emergency vehicles. If you drive on the left lane move as far to the left-hand side as possible. If you drive on another lane (middle or right lane), move as far to the right-hand side as possible (hard shoulder included).
- Winter tyres: From November to April, drivers in Austria are obliged to use winter tyres. We recommend checking the condition of your winter tyres before your journey.
Snow Space Salzburg
Arriving by train
"Next stop: St. Johann im Pongau!"
If you arrive by train, get off at Intercity station St. Johann im Pongau. Tip: The ÖBB Railjet takes you directly to St. Johann. From there, St. Johann-Alpendorf and your hotel are best reached by taxi, bus or hotel shuttle service.
For time tables for your train or bus journey to St. Johann-Alpendorf, please consult the Austrian (www.oebb.at) or German Railways (www.bahn.de).
Attractive train offers:
- ÖBB "winter sports" combination ticket
- With your ÖBB train ticket, you benefit from great discounts at Ghost Mountain and many other attractions …
Arriving by plane
If you arrive by plane, we recommend booking a flight to Salzburg (app. 50 minutes away) or Munich (about two hours away).
From both W. A. Mozart airport in Salzburg and Franz-Josef-Strauß Airport in Munich, St. Johann-Alpendorf is best reached with a shuttle bus or taxi.
Taxi companies in St. Johann-Alpendorf
- Taxi Edi: +43 664 3940235
- Taxi Hippolt: +43 6412 8686; email@example.com
- City Taxi St. Johann: +43 6412 8588; email@example.com
- Taxi Rainer: +43 664 2415725; firstname.lastname@example.com
- Stadt Taxi: +43 664 6311913
- Taxi V.I.P.: +43 660 5600112
- Taxi Wimmer: +43 6412 6245; firstname.lastname@example.com
No matter if you arrive by car, train or plane: St. Johann-Alpendorf is your door to pure pleasure – with us, your next ski trip is just around the corner!


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THE TORONTO TRADITIONAL MASS SOCIETY - UNA VOCE TORONTO - since 2004 has been a Chapter of the VTMS in Vancouver -- a Member of Foederatio Internationalis Una Voce--FIUV. We are a lay movement of Catholics dedicated to the development of the Extraordinary Form of the Roman Rite in the Archdiocese of Toronto and its suffragan dioceses for the restoration of Catholic piety and culture.
Saturday, 13 February 2016
Solemn Traditional Latin Triduum for Toronto
This year, we will be in Toronto at St. John's Chapel at Blessed John Henry Newman High School on the grounds of St. Augustine's Seminary. We thank the Rector of St. Augustine's Seminary, the Principal and Caretakers of Blessed Cardinal Newman High School and the Permit Staff of the Toronto Catholic District School Board for their support and cooperation. The large chapel is located on the west side of the school with entry from 100 Brimley Road South off Kingston Road in Scarborough on the grounds of St. Augustine's Seminary.
All services will be in the solemn form with priest, deacon and subdeacon. If you wish to assist as a server or in the Schola, please contact firstname.lastname@example.com.
Your financial support for this project is welcomed and necessary as there is a significant cost to the Toronto Traditional Mass Society for the permit, caretaking staff, insurance and liturgical items. Would you consider a tax-deductible donation today which you can do so online here at CanadaHelps?
2 comments:
Is there any place in Toronto where the faithful can attend a real Tenebrae service, as it would have been done prior to Vatican II? What the Toronto Oratory describes as "Lamentations" does not sound like the ritual of Tenebrae which involved extinguishing of candles ...ReplyDelete
Since 1956 it is not to be anticipated but celebrated at its proper hours. The Oratory will have some kind of service tonight. The SSPX chapel will have Matins and Lauds, which is what Tenebrae is, on Thursday morning only at 8:00AM.ReplyDelete


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Javanese Oxtail Soup (Sop Buntut) is a comforting soup with oxtails being cooked to the point of almost falling off the bones in aromatic spices and chunky vegetables. If that doesn't spell warmth and comfort, I don't know what is!
Buntut in Indonesian language means Tail, hence the name just like in English…Sop Buntut. This was a popular street food that has made its way to restaurant menu. I love the tenderness of the oxtail after being cooked for such long hours and the spice-rich tasting soup. The chunky vegetables in a soup is also something that I really like for some reasons. Rustic!
I've made these soup several times and perfected the recipe 🙂 Perfect for the freezing temperature now
Please weigh ingredients with a digital kitchen scale instead of using measuring cups as they are not very accurate especially when it comes to recipe that requires precision.
- 2 lbs (900 g) oxtail (cut into round pieces, normally this is already done for you in grocery store)
- 3 Tbsp of butter
- 1 Tbsp sugar
- 1 medium cinnamon stick
- 5 cloves
- 3 cloves garlic - (finely minced)
- 1 tsp whole white peppercorns
- 1 tsp nutmeg powder
- 2 bay leaves
- 6 cups water
- 2 stalks of celery - (cut into half)
- 4 carrots - (peeled and cut into big chunks)
- 2 Roma tomatoes - (quartered)
- 3 large potatoes - (peeled and quartered)
- Salt to taste
Chili sauce:
- 3-4 red or green bird's eye chili - (chopped)
- 2 Tbsp of Indonesian sweet soy sauce / kecap manis
- Fried shallot crisp - (bawang goreng)
- Fresh cilantro leaves
- Bring a large pot of water to a boil. Put it all the oxtail and blanch for about 1 minute. Discard the water and set the oxtail aside. Wash and clean the pot or use another clean large pot
- Melt about 3 Tbsp of butter in the pot. Add in the garlic, stir-fry for about 10 seconds, add in the cloves, peppercorns, bay leaves and nutmeg powder and stir-fry until really fragrant. Add in the oxtails, beef broth and celery, and water enough to cover the oxtails. Put in the cinnamon stick and bring the water to a boil and then lower the heat and let it simmer for the next 3-4 hours (or until the oxtails are really tender)
- About 15 minutes before the end of boiling the oxtails, add in the carrots, tomatoes and potatoes and let them cook until veggies are soft but not mushy. Remove the celery and discard. Have a taste and season with more salt to your liking. Skim off some of the fat before serving if you prefer. Sprinkle some fried shallot crisps and cilantro leaves on top of the soup and serve with the chili sauce on the side
*This post contains affiliate links. You don't pay extra as a consumer if you choose to click on the link and purchase from there. What To Cook Today just receives a small commission from this. That's all. It helps to pay for the cost to have this blog up and running. Thank you so much for your support !


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Monday, September 30, 2013
Homemade Pizza #2 - Salami and Smoked Ham Pizza
As promised, this was the 2nd pizza which I made yesterday (Sunday), the salami and smoked ham pizza. I learnt from making my 1st pizza that I had to roll out the dough as thin as possible, at least 30 cm in diameter. So this time round, the crust was thinner than the haiwaiian pizza but it was still quite thick!
Nevertheless, it was yummy with very simple ingredients, 4 round pieces salami and 3 strips of german black forest smoked ham (zwarte woud ham) and some shredded cheese.
You can find the dough recipe in my previous post. As for the fillings, here it is:
some olive oil
some grated cheese
1 can (70g) of concentrated tomato puree (Benito brand from Colruyt)
4 pieces of salami
4 strips of smoked ham
1. Preheat the oven to 230C or 450F.
2. Place the dough on a cornmeal-dusted pizza stone, pizza pan or cookie sheet. Roll out the dough using a rolling pin to a diameter of at least 30 cm. Roll up the edge slightly to create a ridge around the pizza. (I don't have a pizza stone nor a pizza pan, so I placed the dough on a piece of greased baking paper which I later shoved it onto the metal grill which was then placed into the oven. )
3. Now add the desired fillings. First coat a baking brush with olive oil and brush a thin layer of olive oil on the rollout dough.
4. Then using the back of a spoon, coat it with a 2nd layer of tomato puree.
5. Place the slices of salami and smoked ham on top, then sprinkle a layer of graed cheese on top.
6. Bake in the oven at 230C or 450 F for 15 to 18 min until the crust turns brown. (I baked mine for 15 min.)
I am submitting this post to Aspiring Bakers #35 - A Palate for Pizza (Sept 2013) hosted by Joey of Little Accidents in the Kitchen.
3 comments:
Been a while since I had a pizza... What about offering a slice to me :)ReplyDelete
Simple and yummy. Cheers :)ReplyDelete
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Join us for CADD's Third Thursday Happy Hour on Jan 19 at Ro2 Art
CADD Presents 3rd THURSDAYS
Held at a CADD Member Gallery Each Month
Join us on the 3rd Thursday of each month at a different CADD member gallery for a Happy Hour!
This month's event will take place at Ro2 Art on Jan 19 from 5:30-7:00 pm
Ro2 ART
1501 S. Ervay Street, Dallas TX 75215 USA
Familiarize yourself with the Contemporary Art Dealers of Dallas! Learn about our mission, scholarships, annual events, and other educational programs.
Learn about each gallery's current and upcoming exhibitions, meet the gallery owners and their staff, meet the gallery artists, and other like-minded, art lovers in the DFW area.
CADD's 3rd Thursdays are FREE and proudly sponsored by:
Brooklyn Brewery and Arts+Culture Texas
Permanent link to this article: http://artgroupsdfw.com/exhibits-events/join-us-for-cadds-third-thursday-happy-hour-on-jan-19-at-ro2-art/


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- Betty Audish and Audish is a trademark registered in the US. Our brand has gained recognition and protection from Amazon. We will not allow any forms of infringement.


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Insulin action on the internalization of the GLUT4 glucose transporter in isolated rat adipocytes
UMMS Affiliation
Program in Molecular Medicine
Publication Date
Document Type
Adipose Tissue; Animals; Cell Fractionation; Cell Membrane; Cells, Cultured; Electrophoresis, Polyacrylamide Gel; Insulin; Kinetics; Male; Membrane Proteins; Microsomes; Monosaccharide Transport Proteins; Potassium Cyanide; Rats; Rats, Sprague-Dawley; Trypsin; Ultracentrifugation
Life Sciences | Medicine and Health Sciences
A novel method was developed to measure relative amounts of the GLUT4 glucose transporter on the surface of intact fat cells and to monitor the action of insulin on cell surface glucose transporters as they internalize into intracellular membranes. The method takes advantage of two predicted trypsin cleavage sites in the major exofacial loop of this transporter protein. Treatment of cyanide-poisoned rat adipocytes with 1 mg/ml trypsin at 37 degrees C for 30 min produced an immunoreactive GLUT4 protein species in subsequently isolated plasma membranes that migrated with higher mobility (apparent M(r) = 35,000) than native GLUT4 (apparent M(r) = 46,000) on SDS-polyacrylamide gel electrophoresis. This proteolyzed GLUT4 protein was absent in the intracellular low density microsomes. Insulin treatment of adipocytes for 20 min prior to sequential additions of cyanide and trypsin caused a 16-fold increase in the proteolytically cleaved GLUT4 species. Incubation of fresh fat cells with trypsin caused a rapid and progressive appearance of the proteolyzed GLUT4 species in the intracellular low density membranes as well as plasma membranes. After 5 min of trypsinization, 66% of the total cleaved GLUT4 in these cells had moved into the low density membranes. Insulin treatment markedly decreased the internalized cleaved GLUT4 to 20% of the total. These data indicate the following: 1) trypsinization of the GLUT4 transporter protein on intact fat cells is a convenient means to monitor the extent of transporter recruitment to the plasma membrane by insulin, as well as to estimate GLUT4 internalization rates; and 2) the action of insulin on glucose transporter redistribution to the cell surface is associated with a marked inhibition of the fraction of cell surface GLUT4 transporters internalized per unit time.
J Biol Chem. 1993 May 5;268(13):9187-90.
Journal/Book/Conference Title
The Journal of biological chemistry
Related Resources
PubMed ID
Repository Citation
Czech MP, Buxton JM. (1993). Insulin action on the internalization of the GLUT4 glucose transporter in isolated rat adipocytes. Open Access Articles. Retrieved from https://escholarship.umassmed.edu/oapubs/833


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In his role as "Deep Throat," former FBI agent Mark Felt passed information to the Washington Post and helped reveal the Watergate scandal — when men connected to the Nixon White House burgled and wiretapped the headquarters of the Democratic National Committee in 1972 — as well as other episodes of corruption in the Nixon era. However, the concept of Deep Throat has often overshadowed the real man. Here's more about who he truly was: before, during and after his time as Deep Throat.
When Felt met Woodward
Mark Felt and Bob Woodward met years before the younger man was a reporter at the Washington Post. In his 2005 book about Felt, The Secret Man, Woodward recounted that in 1970, when he was still in the Navy, he encountered Felt while bringing documents to the White House. The two conversed, and Felt gave Woodward his contact information. The FBI agent would provide the younger man with career advice and tips on other stories before the Watergate scandal erupted and Felt's inside information helped transform Woodward into one of the world's most famous reporters.
The FBI directorship
In 1972, Felt was a loyal lieutenant to J. Edgar Hoover at the FBI; after Hoover passed away in May, Felt hoped to be appointed FBI director. Instead, Richard Nixon selected L. Patrick Gray III — who had little relevant experience but was considered loyal to the president — to be acting director. Felt was dismayed, and went on to chafe under Gray's leadership (such as disapproving of his new boss's decision to recruit female agents to the Bureau). It's possible that this disappointment — and a hope of ousting Gray so he could step into the directorship himself — spurred Felt to leak information and become Deep Throat.
Suspected by the White House
While passing information post-Watergate, Felt not only demanded clandestine meetings, he tried to cover his tracks by overseeing an investigation into leaks. But some at the White House still came to believe Felt was the leaker: On October 19, 1972, H.R. "Bob" Haldeman, Nixon's chief of staff, told the President that Felt could be the source because he'd wanted to become head of the FBI. However, Haldeman also cautioned, "If we move on him he'll go out and unload everything. He knows everything that's to be known in the FBI. He has access to absolutely everything." For the time, Felt would stay in place.
Felt resigns
It was an accusation of leaking that prompted Felt to resign from the Bureau in May 1973 — but this time he wasn't actually the leaker. As recounted in Max Holland's 2012 book, Leak: Why Mark Felt Became Deep Throat, William Ruckelshaus (the FBI's new acting director, who'd stepped into the role after Gray) received a call that purportedly came from New York Times reporter John Crewdson. "Crewdson" informed Ruckelshaus that Felt was his source for a recent story; Ruckelshaus confronted Felt, who proclaimed his innocence and ended up indignantly submitting his resignation. Crewdson admitted to Holland that his source had actually died in 1977, and stated he'd never phoned Ruckelshaus — meaning Felt was brought down by a leak he hadn't been responsible for.
Felt on trial
Being Deep Throat was risky, but Felt never faced any charges for his role. However, other actions he'd taken at the FBI ended up placing him in judicial jeopardy. Felt had pursued the Weather Underground, a radical group believed responsible for planting bombs. In July 1972 he'd received instructions from Gray that read: "Hunt to exhaustion. No holds barred." Felt went on to authorize agents to break into the homes of people connected to members of the organization. These break-ins resulted in Felt being indicted in 1978; he went on trial in 1980.
Support from Nixon
During his trial, Felt had an unexpected supporter: former President Nixon. Felt's defense claimed that the break-ins had been in the interests of national security, and Nixon backed this in his testimony (at the time, Nixon likely no longer suspected Felt of being Deep Throat, as new leaks had come out even after Felt's resignation from the FBI). Though Felt was convicted in the fall of 1980, President Ronald Reagan pardoned him after taking office in 1981; Nixon subsequently sent Felt champagne to celebrate.
The Deep Throat reveal
Over the years, people continued to speculate about Deep Throat's true identity. As someone who'd had access to FBI files and the Nixon White House, Felt was a natural suspect — but he always denied his involvement when asked (he also didn't appreciate the fact that the nickname came from a hit porn film). Yet in 2005, Felt and his family decided to reveal his identity. Felt, who was then in his 90s, got to tell his side of the story before it was too late — and was able to provide his family with any income that resulted from the public announcement.
What motivated Felt
With Felt outed as Deep Throat, his motives were analyzed once more. Was he simply resentful about being passed over for a promotion? How could he judge the Nixon White House when his own actions had crossed lines? In the end, Felt's love for the FBI is the most likely explanation. Felt's son once stated, "He believed in the F.B.I. more than anything else he believed in in his life." However complex Felt's motivations — as Woodward himself noted, "There is no such thing as a perfect source" — he helped protect the independence of the FBI and the American system of justice.