.add("publicobject.com",   "sha1/T5x9IXmcrQ7YuQxXnxoCmeeQ84c=")
         .add("*.publicobject.com", "sha1/T5x9IXmcrQ7YuQxXnxoCmeeQ84c=")
         .build());
    ```

 *  **Interceptors lists are now deep-copied by `OkHttpClient.clone()`.**
    Previously clones shared interceptors, which made it difficult to customize
    the interceptors on a request-by-request basis.

 *  New: `Headers.toMultimap()`.

        handler -->> client: HTTP error response
        dep -->> dep: Raise other exception
    end
    dep ->> operation: Run dependency, e.g. DB session
    opt raise
        operation -->> dep: Raise HTTPException
        dep -->> handler: Auto forward exception
        handler -->> client: HTTP error response
        operation -->> dep: Raise other exception
        dep -->> handler: Auto forward exception
    end

 * href="https://www.javadoc.io/doc/com.github.ben-manes.caffeine/caffeine/latest/com.github.benmanes.caffeine/com/github/benmanes/caffeine/cache/AsyncLoadingCache.html">their
 * deep support for asynchronous operations</a>. But if you want to migrate to Caffeine with minimal
 * code changes, you can use <a

        String field = settings.array().get(SuggestSettings.DefaultKeys.SUPPORTED_FIELDS)[0];

        Map<String, Object> document = new HashMap<>();
        document.put(field, "Schöner Klang der Gitarre");
        document.put("lang", "de");
        suggester.indexer().indexFromDocument(new Map[] { document });
        suggester.refresh();

            and newer CPUs.)
            *   [Example performance speedups.](https://medium.com/intel-analytics-software/leverage-intel-deep-learning-optimizations-in-tensorflow-129faa80ee07)
        *   For older CPUs, oneDNN optimizations are disabled by default.
    *   **Windows x86 package:** oneDNN optimizations are disabled by default.

  TF_Operation* feed4 =
      TF_GraphOperationByName(graph, "imported4/imported2/feed");

  // Check that imported `imported3/scalar` has remapped control dep from
  // original graph and imported control dep
  num_control_inputs = TF_OperationGetControlInputs(
      scalar4, control_inputs, TF_OperationNumControlInputs(scalar4));
  ASSERT_EQ(2, num_control_inputs);
  EXPECT_EQ(feed, control_inputs[0]);

     * is the only one in use, but if we encounter nested concatenations, we start a deque of
     * meta-iterators rather than letting the nesting get arbitrarily deep.  This keeps each
     * operation O(1).
     */

    @CheckForNull private Iterator<? extends Iterator<? extends T>> topMetaIterator;

    // Only becomes nonnull if we encounter nested concatenations.

 * href="https://www.javadoc.io/doc/com.github.ben-manes.caffeine/caffeine/latest/com.github.benmanes.caffeine/com/github/benmanes/caffeine/cache/AsyncLoadingCache.html">their
 * deep support for asynchronous operations</a>. But if you want to migrate to Caffeine with minimal
 * code changes, you can use <a

      <match value="-----BEGIN CERTIFICATE-----" type="string" offset="0"/>
    </magic>
  </mime-type>
  <mime-type type="application/x-x509-cert;format=der">
    <sub-class-of type="application/x-x509-cert"/>
    <glob pattern="*.der"/>
    <magic priority="50">
      <match value="0x3080" type="string"
              mask="0xFFF8" offset="0">
         <!-- SHA with RSA Encryption -->

scrollParents: [],\n    };\n\n    // get reference and popper elements (allow jQuery wrappers)\n    this.reference = reference && reference.jquery ? reference[0] : reference;\n    this.popper = popper && popper.jquery ? popper[0] : popper;\n\n    // Deep merge modifiers options\n    this.options.modifiers = {};\n    Object.keys({\n      ...Popper.Defaults.modifiers,\n      ...options.modifiers,\n    }).forEach(name => {\n      this.options.modifiers[name] = {\n        // If it's a built-in modifier,...