Quick Jump + Powerful Leap

Quick Jump makes High Jump and Long Jump single actions.
Powerful Leap adds 5 feet to your Leap distance horizontally.

Do these work together? One of them talks about Leaps, the other Long Jumps, are these the same thing?
So if I have both with a Speed of 25, can I use a single action to Leap 15 feet without a check, and with an Athletics check DC (Distance-5)?

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How can I best set up a quick project in GSA?

Hello, GSA peepz. Hope you are all having a great Summer! :pirate:
My question is: How can I quickly make a project?
In the past, it required writing descriptions (250,450) and all other fields. For some, also articles.
And then spinning them all.
I used the White Hat Box Spinner Chief spinning program, but it required a lot of checking by hand afterwards. This is all very time consuming.
How can I quickly set up a project?
I’d like to be able to set up Tier 2 or 3 that are not as important projects faster.


Hi guys!
I have a couple local small businesses websites. I need to boost them with links.
I want to add one or two tier 1 links per month, and tier 2-3-4.  One niche is local beauty salon, other niche is local spa salon. It is small town, it has 50k of people.
My question is, how I quickly get/buy the correct tier 1 link? So I can then use GSA Search Ranker?
P.S. I don’t want to make reach out contating magazines, journals etc. to get tier 1 link.

Sedgewick Quick Union Analysis

I am currently studying Algorithms, Fourth Edition by Sedgewick et al. On page 226, there is an analysis of the quick union algorithm’s find() method’s worst case. This is the algorithm:

  private int p   {    while (p != id[p]) p = id[p];   return p;   } 

Now I count N comparisons in total (inside the while) plus N-1 accesses (last comparison is false) to rewrite the value of p. This would give me 2N – 1 accesses to the array. The textbook however says there are 2N+1 accesses. What am I doing wrong? Thanks for your time.

Radix sort slower than Quick sort?

I would like to demonstrate that sometime radix-sort is better than quick-sort. In this example I am using the program below:

#include <stdio.h> #include <stdlib.h> #include <assert.h> #include <string.h> #include <time.h> #include <math.h>  int cmpfunc (const void * a, const void * b) {    return ( *(int*)a - *(int*)b ); }  void bin_radix_sort(int *a, const long long size, int digits) {     assert(digits % 2 == 0);      long long count[2];     int *b = malloc(size * sizeof(int));     int exp = 0;      while(digits--) {         // Count elements         count[0] = count[1] = 0;         for (int i = 0; i < size; i++)             count[(a[i] >> exp) & 0x01]++;          // Cumulative sum         count[1] += count[0];          // Build output array         for (int i = size - 1; i >= 0; i--)             b[--count[(a[i] >> exp) & 0x01]] = a[i];          exp++;         int *p = a; a = b; b = p;     };      free(b); }  struct timespec start;  void tic() {     timespec_get(&start, TIME_UTC); }  double toc() {     struct timespec stop;     timespec_get(&stop, TIME_UTC);     return stop.tv_sec - start.tv_sec + (         stop.tv_nsec - start.tv_nsec     ) * 1e-9; }  int main(void) {     const long long n = 1024 * 1024 * 50;     printf("Init memory (%lld MB)...\n", n / 1024 / 1024 * sizeof(int));      int *data = calloc(n, sizeof(int));      printf("Sorting n = %lld data elements...\n", n);      long long O;     tic();     O = n * log(n);     qsort(data, n, sizeof(data[0]), cmpfunc);     printf("%lld %lf s\n", O, toc());      int d = 6;     tic();     O = d * (n + 2);     bin_radix_sort(data, n, d);     printf("%lld %lf s\n", O, toc()); } 

It performs as follow:

$   gcc bench.c -lm $   ./a.out  Init memory (200 MB)... Sorting n = 52428800 data elements... 931920169 1.858300 s 314572812 1.541998 s 

I know that Quick Sort will perform in O(n log n) while Radix Sort will be in O(d (n + r)) ~= O(6 * n). For n = 52428800, log(n) = 17. I am then expecting Radix Sort to be 3 times faster than Quick Sort…

This is not what I observe.

What am I missing?

Quick Sort vs Radix Sort

In an coding exam, I was once asked this question:

Assuming that you are only sorting Integers in ascending order, which algorithm do you use when you want to prioritize speed the most, but you also want to save space?

The options were:

  • LSD Radix Sort
  • Merge Sort
  • Quick Sort

I think an argument can be made between LSD Radix Sort and Quicksort.

Radix sort would function in $ $ O(kn)$ $ and Quicksort would function in $ $ O(nlogn)$ $ and worst case, $ $ O(n^2)$ $

I chose Radix Sort as the answer, but I’m curious as to what others had to say.

What’s a quick test to see if an $n \times n$ matrix is diagonal and/or proporitional to the identity matrix?

As the title indicates, I want to test whether an $ n \times n$ matrix (numeric, symbolic,..) is diagonal and/or proportional to the $ n \times n$ identity matrix. I, of course, can test whether the $ n^2-n$ individual off-diagonal entries are zero–but that’s, it would seem, is inefficient.