msv | Sun Multi-Schema XML Validator

I have a query that is running really slow for production (900ms and sometimes even 3-4 seconds) The query is pretty simple and slow due to a big table but not for a slow server. I am running over Aurora RDS serverless. I am asking is there a better way to go. I only want to join between two tables with his most recent values. I use Rank ordering by created_at

@DCTLib, do you recall this discussion below? You suggested a recursive equation, which was the right approach.

Cudd_PrintMinterm, accessing the individual minterms in the sum of products

Now, I am considering multistate reliability, where we can have either not fail or fail to n-1 different states, with n >= 2. Tulip-dd implements MDDs as described in:

https://github.com/tulip-control/dd/blob/master/doc.md#multi-valued-decision-diagrams-mdd

https://github.com/tulip-control/dd/issues/71

https://github.com/tulip-control/dd/issues/66

In the diagrams in the drawings below, we have defined an MDD declared by:

aut.declare_variable(x=(0,3)) u = aut.add_expr(‘x=i’)

Each value/state of the multi-value variable (MSV) x, x=0, x=1, x=2, or x=3 leads to a specific BDD as shown in the diagrams at the bottom, taking a four-state variable x as example here. The notation is that state 0 represents the normal state and x can fail to different states 1, 2, and 3. The failure probabilities are assigned in table below. In the BDDs below, we (and tulip as well) use the binary coding with two bits x_1 and x_0 to represent each state/value of the MSV. The least significant bit (LSB), i.e., x_0, is always the ancestor. Each of the BDD diagrams below is a representation of a specific value, or state.

To quantify the BDD of a specific state, i.e., the top node, we must know probabilities of binary variables x_0 and x_1 taking different branches (then or else) in the BDD. These branch probabilities are not given directly but need to be calculated according to the BDD structure.

The key here is that the child node probabilities and the branch probabilities of the parent node must be known prior to the calculation of the parent node probability. In the previous BDD quantification, we knew the probabilities of branches from node x_1 to leaf nodes when calculating node x_1 probability. We did not need to know how node x_1 was connected to node x_0. Now, for this four-state variable x, we need to know how node x_1 is connected to node x_0, the binary variable representing the least significant bit, to determine the probabilities of branches from node x_1 to leaf nodes. The question is how to implement this?

I'm using prince for a principal component analysis:

So I created a table name locations:

create table locations (

I am developing a sample code for my customer and haven't done programming in python before. I am reading a text file from google cloud bucket

First I did a script to filter files from a specific folder and copy and paste the selected files to another folder, this was working well.

Now I having problem to implement the UI Tkinter, I can't find a way to make works when the origin folder path and type of files choice came from the interface.

I will be grateful if somebody shows me how to do this.