## Windows OS Trials / Evaluations …

I’ve been looking at VPS solutions that offer Windows OS.

I understand most hosting providers offer the trial and the customer has to pu… | Read the rest of https://www.webhostingtalk.com/showthread.php?t=1842654&goto=newpost

## links – Would spamming developer Stack Overflow's story increase SEO evaluations of my websites?

Imagine starting to create hundreds of Stack Overflow accounts. ((I am not and I do not intend to do it in reality). I add a link to my site in the personal site space of the profile. I then make public the developer story (CV). for example. https://stackoverflow.com/story/kamilt

If such pages are searchable on Google and contain links to my website, will this help the SEO of my website? Would that allow me to get a higher ranking in Google because of this?

## recursion – Trace reveals unexpected evaluations and internal calls for a recursive function

I would like help in identifying the problem in my implementation of the recursive function illustrated below. But first, a little context.

There is a well-known solution to the problem of finding the longest common subsequence among two sequences. The algorithm is as follows:

Reverse the sequences S1 and S2, and call the reversed sequences RS1 and RS2

Define a recursive getLCS function, which takes RS1, RS2 and an empty ACC accumulator and does the following:

If RS1 or RS2 is empty, getLCS returns ACC.

Otherwise, if h1, the head of RS1, is equal to h2, the head of RS2, getLCS returns getLCS (tail (RS1), tail (RS2), {h1} union ACC).

Otherwise, getLCS returns the longest of getLCS (queue (RS1), RS2, ACC) and getLCS (RS1, queue (RS2), ACC).

My implementation of Wolfram Language is as follows:

ClearAll(getLCS);
getLCS({}, _, acc_) := acc;
getLCS(_, {}, acc_) := acc;
getLCS({s_, t1___}, {s_, t2___}, acc_) := getLCS({t1}, {t2}, Prepend(acc, s));
getLCS({s1_, t1___}, {s2_, t2___}, acc_) := {
getLCS({t1}, {s2, t2}, acc), getLCS({s1, t1}, {t2}, acc)
} // MaximalBy(Length) // First;
getLCS(lst1_, lst2_) := getLCS(Reverse(lst1), Reverse(lst2), {});

The implementation works, but is extremely slow, even for short sequences. Operation Trace sure:

getLCS({1, 2, 3}, {1, 2, 4}) // Trace

reveals a long list of internal calls whose innocent eyes must be protected.

For reference, here is (essentially) the same implementation in F#:

let getLCS<'A when 'A : equality> (lst1 : list<'A>) (lst2 : list<'A>) : list<'A> =
let rec f (cLst1R : list<'A>) (cLst2R : list<'A>) (acc : list<'A>) : list<'A> =
match cLst1R, cLst2R with
| (), _ | _, () -> acc
| h1 :: t1, h2 :: t2 when (h1 = h2) -> f t1 t2 (h1 :: acc)
| _ :: t1, _ :: t2 ->
((f t1 cLst2R acc); (f cLst1R t2 acc)) |> List.maxBy List.length
f (List.rev lst1) (List.rev lst2) ()

the F# the version runs much faster. I know it Wolfram Language is not as slow in comparison. So my questions are:

1. What are the shortcomings of my Wolfram Language Implementation?
2. Why Trace show a stack of calls so different from what would be considered a normal mental image of the stack of execution implied by the definition?

## nt.number theory – rank 1 evaluations which are not discrete on finite transcendental extensions of rationals

assume $$K = mathbb {Q} (X_1, dots, X_n)$$ is a purely transcendental extension of rationals on an infinitely indeterminate number. Can anyone give an example of rank $$1$$ evaluation on $$K$$ who fails to be discreet?

If not, is there a theorem which shows that such a rank $$1$$ should the assessment be discreet?

## Digital Integration – How to Count the Number of Function Evaluations in NIntegrate

Try the option EvaluationMonitor

Block[{k = 0}, {NIntegrate[f[x], {x, -2, 1}, EvaluationMonitor :> k++], k}]

{0.0901049, 121}

Without using EvaluationMonitor you can do

ClearAll[f, ff]
f[x_] := Tanh[x] Sin[Exp[x]] Exp[-0.55 x^2 Exp[x^2]]

i = 0;
ff[y_?NumberQ] := Block[{x = y}, i++; f[x]]

{NIntegrate[ff[x], {x, -2, 1}], i}

{0.0901049, 121}

## schema.org – How to prove that third party evaluations and evaluations are correct and real?

we are developing an application that of course has a website.
I've added some of our user ratings and ratings given in Google Play, Apple Store and the corresponding JSON-LDs.
Individual Evaluation Example (Review -> Rating).
Example of global comments (UserReview -> AggregateReview)

I could not find the answers on the internet where there was more information about falsification of the data. For example. make your rating 5/5 of 1000000 people. I would not want to pretend then some questions arose:

1. It's the site developer who can add data that can be false or real.
How can I prove the authenticity of a user notice? Link to the third party site where the revision exists? Any other way? In both stores, there is a link "Link to this review". Is it possible to link the individual note to this link?

2. We now have 15 Apple Store ratings and 12 Google Store evaluations. So we got an overall score of 5 on the Apple Store and 4,833 on Google Play => average 4 9165 => ~ 4.9. A page may have an aggregate rating, but what about now when the rating comes from two different sources?

and some questions have arisen.

1. Who is the author of AggregatedRating if the notes are added by me, but that they actually come from Google and Apple? Since this is a mandatory field or the test tool generates at least one error, "a value for the author field is required". because I leave it empty for the moment.

## The evaluations of uploadboy.com: SCAM or LEGIT?

We pay by download (PPD), payment-per-sale program (PPS) and pay to earn referrals.

• 20% of the sales payment and 20% of the invoicing
• 10% of the references won

Payments are processed on a weekly basis and every Monday.
The minimum income to pay is \$ 5 if you select Webmoney and \$ 20 for paypal payments.
Payments …

The evaluations of uploadboy.com: SCAM or LEGIT?

## Website evaluations

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https://vacail.com/

https://weinsteinwin.com/

https://ashcraftandgerel.com/

https://gonzalezlevenson.com/

https://www.burnetti.com/

https://bethunelawfirm.com/

https://mydrted.com/

https://nettleslawfirm.com/

https://www.wintersandyonker.com/