## Bitcoin and output search not indexed

Using Bitcoin RPC and `txindex=0` Is it possible to tell the difference between an existing issue that has already been issued and a non-existent transaction issue (or transaction ID)? Look at `gettxout` This is not enough because empty data is returned in both scenarios.

## Will not the URL of the Flash game pages be indexed anymore?

Hi

They say that Google will stop indexing Flash. My question is:

The pages containing Flash games stop indexing the URL containing such games in .swf format?

Does anyone know something about it?

Many thanks

## Fiber category vs indexed category

In Benabou's essay Fibered categories and the basics of naive class theory it says (end page 31):An indexed category is just a representation of a fibrous category.& # 39;

1. It seems that Benabou argues that fiber optic categories formalize the same idea as indexed categories, but are better to manage. I have also found very little literature on indexed categories. Is the concept of the "indexed category" a bit outdated compared to the "fibrous category"? (Personally, I'm not an expert and am temporarily comfortable with indexed categories, but now I was wondering if I should continue to study the fibrous categories for a better understanding.)

2. Expressly, from nlab I know that of course you can get from one $$mathcal S$$-indexed category an over-fibered category $$mathcal S$$using the Grothendieck construction. It is also claimed that two of them are equivalent. So, conversely, how can I restore that? $$mathcal S$$indexed category from this fiber category over $$mathcal S$$?

## Website is not crawled or indexed in Bing or Yahoo Search Engine

Hello everybody,
I have a customer website <>, The site ranks well in the Google search engine. But not in yahho or bi … | Read the rest of https://www.webhostingtalk.com/showthread.php?t=1788149&goto=newpost

## When does SER check if a page has been indexed?

Do I have to put the project in Review or Review mode? Or only Active works?
Thanks a lot!

## postgresql – Postgres with seq scan with filter for indexed column + EXISTS for associated table

I have the following query, which takes about 25-35 seconds to execute:

``````EXPLAIN (analyze, buffers, format text) SELECT booking.*
FROM booking
WHERE booking.reference_number = '9999999999' OR booking.booking_id = '9999999999' OR
(
EXISTS (
SELECT * FROM booking_customer
WHERE booking_customer.booking_id = booking.booking_id AND
(booking_customer.email = '9999999999' OR booking_customer.phone = '9999999999') AND
booking_customer.deleted = false
)
);
``````

The EXPLAIN issue can be found here: https://explain.depesz.com/s/RPNV

As you can see from the chart, the bookings table is searched one after another, even though filtered by indexed columns. `reference_number` and `booking_id`, The `booking_customer` However, the table uses the index scan correctly.

Does it have something to do with it? `EXISTS` or `OR` there clauses?

My table structure is as follows:

``````                              Table "public.booking"
Column         |           Type           | Collation | Nullable | Default
-----------------------+--------------------------+-----------+----------+---------
deleted               | boolean                  |           |          |
booking_id            | character varying        |           | not null |
reference_number      | character varying        |           |          |
booking_owner         | character varying        |           |          |
checkin_date          | timestamp with time zone |           |          |
checkout_date         | timestamp with time zone |           |          |
status                | character varying        |           |          |
hold_till             | timestamp with time zone |           |          |
version               | integer                  |           | not null |
comments              | text                     |           |          |
extra_information     | json                     |           |          |
cancellation_reason   | character varying        |           |          |
cancellation_datetime | timestamp with time zone |           |          |
created_at            | timestamp with time zone |           | not null | now()
modified_at           | timestamp with time zone |           | not null | now()
Indexes:
"booking_pkey" PRIMARY KEY, btree (booking_id)
"ix_booking_reference_number" UNIQUE, btree (reference_number)
"idx_booking_checkin_date" btree (checkin_date)
"idx_booking_checkout_date" btree (checkout_date)
"ix_booking_status" btree (status)
"trgm_booking_ref_num" gist (reference_number gist_trgm_ops)
``````

And customer table:

``````                          Table "public.booking_customer"
Column         |           Type           | Collation | Nullable | Default
-----------------------+--------------------------+-----------+----------+---------
deleted               | boolean                  |           |          |
customer_id           | character varying        |           | not null |
booking_id            | character varying        |           | not null |
first_name            | character varying        |           |          |
last_name             | character varying        |           |          |
gender                | character varying        |           |          |
age                   | integer                  |           |          |
nationality           | character varying        |           |          |
phone                 | character varying        |           |          |
email                 | character varying        |           |          |
gst_addr_field1       | character varying        |           |          |
gst_addr_field2       | character varying        |           |          |
gst_addr_city         | character varying        |           |          |
gst_addr_state        | character varying        |           |          |
gst_addr_country      | character varying        |           |          |
gst_pincode           | character varying        |           |          |
legal_name            | character varying        |           |          |
created_at            | timestamp with time zone |           | not null | now()
modified_at           | timestamp with time zone |           | not null | now()
Indexes:
"booking_customer_pkey" PRIMARY KEY, btree (customer_id, booking_id)
"book_cust_idx" btree (booking_id, customer_id)
"ix_booking_customer_email" btree (email)
"ix_booking_customer_phone" btree (phone)
"trgm_cust_last_name" gist (last_name gist_trgm_ops)
``````

Details about the total records in the table are as follows:

``````db=> SELECT COUNT(*) FROM booking;
count
--------
958092
(1 row)

db=> SELECT COUNT(*) FROM booking_customer;
count
---------
2471445
(1 row)

db=> SELECT COUNT(*) FROM booking WHERE reference_number = '9999999999' OR booking_id = '9999999999';
count
-------
1
(1 row)

db=> SELECT COUNT(*) FROM booking_customer WHERE (email = '9999999999' OR phone = '9999999999') AND deleted = false;
count
--------
156377
(1 row)

db=> SELECT COUNT(DISTINCT(booking_id)) FROM booking_customer WHERE (email = '9999999999' OR phone = '9999999999') AND deleted = false;
count
-------
65196
(1 row)
``````

So ideally I should have gotten `65196` Rows as a result, which may be a good reason to use sequence scan. However, the planner returns only 14 lines as an estimate. That's funny, considering that yesterday at midnight, I did vacuum analysis on both tables.

Even if I try with a different value for phone or email, giving about 1300 lines, the seq scan is still used for the booking table.

Is there a way to optimize this query?

Postgres details:

``````db=> SELECT version();
version
-------------------------------------------------------------------------------
PostgreSQL 9.6.12 on x86_64-pc-linux-gnu, compiled by gcc (GCC) 4.9.3, 64-bit
(1 row)
``````

## Matrix – How do I solve a large system of differential equations with indexed functions?

I firmly believe that matrix methods are the right answer here, but I can not imagine how to set them up. Imagine a large number of coupled functions:

``````AB(m,n)(t)
``````

Where m and n are integer indices that can be up to hundreds of thousands or thousands of thousands, and t is a continuous time variable. Imagine AB (m, n) as the concentration of AB of type (m, n), and these concentrations of different types can evolve over time. In addition, we have a single additional feature:

``````B(t)
``````

it is also a concentration that evolves over time, but for which there is only one type. Initial conditions are:

``````AB(a,0)(0) = A0
AB(anythingelse)(0) = 0
B(0) = B0
``````

Here a is a constant integer in the hundreds to thousands.

AB (m, n) can be converted into other types by two processes:

``````AB(m,n) + B --> AB(m-1,n+b)
AB(m,n) --> AB(m-1,n-1)
``````

Here b is a constant integer that is significantly smaller than a. That is, the differential equations that determine the evolution of the system are:

``````D(AB(m, n)(t), t) == -k1(m, n) AB(m, n)(t) B(t)
+k1(m + 1, n - b) AB(m + 1, n - b)(t) B(t)
-k2(m, n) AB(m, n)(t)
+k2(m + 1, n + 1) AB(m + 1, n + 1)(t)
D(B(t), t) == -k1(m, n) AB(m, n)(t) B(t)
``````

Good assumptions for the forms for k1 and k2 that we can use for testing are:

``````k1(m_) = (m/a) k3
k2(m_, n_) = k4 n/(n + k5/m) + n k6 k1(m)
``````

Here k3, k4, k5 and k6 are positive real numbers.

How on earth do I organize this system to solve it numerically? `NDSolve` (or `ParametricNDSolve`) or similar? The ultimate goal will be to have a measurable function that looks something like this:

``````Sum(m AB(m,n),{m,0,a},{n,0,infinity})
``````

This function would then be suitable for experimental data that varies k3-k6 and possibly a and b. Later generalizations may be to have a broader distribution of starting concentrations, rather than all being identical, a range of different possible bs, etc.

## Google Search Console error: Indexed but blocked by robots.txt

I have used shared hosting in the past and everything was fine. But when I switched to a VPS (Digital Ocean) Google search panel, the following error appears: "I … | Read the rest of https://www.webhostingtalk.com/showthread.php?t=1786978&goto=newpost