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no How to cook a cake “Bear”
cake ingredients
Cooking Tips
Ingredients
What will you need
To make bear cake you will need:
How to make bear pie:
How to make bear cake
Video how to make a teddy bear
How to cook a cake “Bear” Cake “Bear” turns out to be very tasty and tender.
It reminds us of childhood and those goodies that mom prepared for us for the holidays.
To date, bear pie is one of the most commonly baked dishes.
To make the cake delicious, you need to choose the right oil.
In stores, it is sold in two types: sweet cream or margarine.
If you want a more delicate and creamy cake, then choose the first type of butter.
As a cream, take sour cream or cream.
Choose thick sour cream. Use coconut flakes, marzipan, berries as a decoration.
You can also use mastic or marzipan.
Cake “Bears”
Cake “Bear” is very tasty and tender.
In stores, it is sold in two types: sweet cream or margarine. If you want a more delicate and creamy cake, then choose the first type of butter.
As a cream, take sour cream or cream. Choose thick sour cream.
Use coconut flakes, marzipan, berries as a decoration.
Dough Ingredients:
Flour – 2 cups
Butter – 200 g
Baking powder – 1 tsp
orange peel
Vanilla sugar – 1 sachet
Sour cream – 1 cup
Cream Ingredients:
Eggs – 2 pcs.
Sugar – 1 cup
Butter – 200 g
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the production of epidemiological evidence, when possible, is useful for estimating of the parameters. Our fitting process is based on the Levenberg-Marquardt algorithm [@pone.0062199-Levenberg1], [@pone.0062199-Marquardt1]. The advantage of using an algorithm is that it can handle extreme parameter values.
A drawback of our approach is that some data, such as those that occur during early outbreaks, are rarely available for parameter estimation, unless the outbreak is large. We also tested the stability of the algorithm by estimating the transmission dynamics for the 2001 cholera outbreak in Calcutta [@pone.0062199-Brown2] in which only the day-wise cholera cases were reported. The estimated time-dependent transmission dynamics for the 2001 cholera outbreak in Calcutta were compared with the findings of conventional transmission dynamics (2-week lag) for the same outbreak [@pone.0062199-Parekh1]. Our parameter estimations were almost identical to the conventional 2-week lag estimations ([Table 4](#pone-0062199-t004){ref-type=”table”}). However, our parameter estimations were almost identical to the conventional transmission dynamics estimation (2-week lag) ([Table 3](#pone-0062199-t003){ref-type=”table”}). Our results are very promising, and we believe that if the same algorithm can be applied to the data on early outbreaks, it can be very useful in estimating the parameters.
In conclusion, we suggest that the framework presented here can be used for estimating transmission dynamics of the bacterial pathogens, and epidemiological investigations in general. We also demonstrate that our approach has more robustness against noise in the data than conventional method. The proposed method can not only be used in conjunction with traditional data analyses techniques, such as time-series regression [@pone.0062199-Waller1] and linear regression [@pone.0062199-Dobson1], but also with other unconventional approaches such as Bayesian methods.
We would like to thank Prof. James Barry for his fruitful comments and suggestions.
[^1]: **Competing Interests:**The authors have declared that no competing interests exist.
[^2]: Conceived and designed the experiments: BPG. Performed the experiments: BPG. Analyzed the data
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