"aici", "al", "ăla", "ale", "alea", "ălea", "altceva", "altcineva", "am", "ar", "are", "aş", "aşadar", "asemenea", "asta", "ăsta", "astăzi", "astea", "ăstea", "ăştia", "asupra", "aţi", "au", "avea", "avem", "aveţi", "azi", "bine", "bucur", "bună", "ca", "că", "căci", "când", "care", "cărei", "căror", "cărui", "cât", "câte", "câţi", "către", "câtva", "ce", "cel", "ceva", "chiar", "cînd", "cine", "cineva", "cît", "cîte", "cîţi", "cîtva", "contra", "cu", "cum", "cumva", "curând", "curînd", "da", "dă", "dacă",...

"aici", "al", "ăla", "ale", "alea", "ălea", "altceva", "altcineva", "am", "ar", "are", "aş", "aşadar", "asemenea", "asta", "ăsta", "astăzi", "astea", "ăstea", "ăştia", "asupra", "aţi", "au", "avea", "avem", "aveţi", "azi", "bine", "bucur", "bună", "ca", "că", "căci", "când", "care", "cărei", "căror", "cărui", "cât", "câte", "câţi", "către", "câtva", "ce", "cel", "ceva", "chiar", "cînd", "cine", "cineva", "cît", "cîte", "cîţi", "cîtva", "contra", "cu", "cum", "cumva", "curând", "curînd", "da", "dă", "dacă",...

    Closer closer = Closer.create();
    try {
      InputStream in = closer.register(openStream());
      return countBySkipping(in);
    } catch (IOException e) {
      // skip may not be supported... at any rate, try reading
    } finally {
      closer.close();
    }

    closer = Closer.create();
    try {
      InputStream in = closer.register(openStream());
      return ByteStreams.exhaust(in);

- Improved the error message shown when a Pod using user namespaces was created on a runtime that did not support user namespaces. ([#131623](https://github.com/kubernetes/kubernetes/pull/131623), [@rata](https://github.com/rata))

   *
   * <p>See http://en.wikipedia.org/wiki/Bloom_filter#Probability_of_false_positives for the
   * formula.
   *
   * @param n expected insertions (must be positive)
   * @param p false positive rate (must be 0 < p < 1)
   */
  @VisibleForTesting
  static long optimalNumOfBits(long n, double p) {
    if (p == 0) {
      p = Double.MIN_VALUE;
    }
    return (long) (-n * Math.log(p) / SQUARED_LOG_TWO);

* Moved pod affinity and anti-affinity from annotations to api fields [#25319](https://github.com/kubernetes/kubernetes/pull/25319) ([#39478](https://github.com/kubernetes/kubernetes/pull/39478), [@rrati](https://github.com/rrati))

# Minimum width for HTML images in thumbnails.
thumbnail.html.image.min.width=100
# Minimum height for HTML images in thumbnails.
thumbnail.html.image.min.height=100
# Maximum aspect ratio for HTML images in thumbnails.
thumbnail.html.image.max.aspect.ratio=3.0
# Width of generated thumbnail images.
thumbnail.html.image.thumbnail.width=100
# Height of generated thumbnail images.
thumbnail.html.image.thumbnail.height=100

labels.group_gidNumber=gidNumber
labels.gidNumber=gidNumber
labels.user_homeDirectory=Directory home
labels.homeDirectory=Directory home
labels.upgrade_title_configuration=Aggiornamento
labels.upgrade_data_migration=Migrazione dati
labels.upgrade_reindex=Reindicizzazione
labels.upgrade_start_button=Avvia
labels.replace_aliases=Aggiorna alias
labels.reset_dictionaries=Ripristina dizionari
labels.reindex_start_button=Avvia

    if (uniques < contents.length / 2) {
      // Deduplication eliminated many of the elements.  We don't want to retain an arbitrarily
      // large array relative to the number of elements, so we cap the ratio.
      contents = Arrays.copyOf(contents, uniques);
    }
    return new RegularImmutableSortedSet<E>(
        ImmutableList.<E>asImmutableList(contents, uniques), comparator);
  }

  /**

   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit
   * rate, and ability to be implemented with O(1) time complexity. The initial LRU implementation
   * operates per-segment rather than globally for increased implementation simplicity. We expect
   * the cache hit rate to be similar to that of a global LRU algorithm.
   */

  // Constants

  /**