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Bianca Hopes "The B" Group

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Andrew Martin
Andrew Martin


This paper describes some of the statistical considerations in the intent-to-treat design and analysis of clinical trials. The pivotal property of a clinical trial is the assignment of treatments to patients at random. Randomization alone, however, is not sufficient to provide an unbiased comparison of therapies. An additional requirement is that the set of patients contributing to an analysis provides an unbiased assessment of treatment effects, or that any missing data are ignorable. A sufficient condition to provide an unbiased comparison is to obtain complete data on all randomized subjects. This can be achieved by an intent-to-treat design wherein all patients are followed until death or the end of the trial, or until the outcome event is reached in a time-to-event trial, irrespective of whether the patient is still receiving or complying with the assigned treatment. The properties of this strategy are contrasted with those of an efficacy subset analysis in which patients and observable patient data are excluded from the analysis on the basis of information obtained postrandomization. I describe the potential bias that can be introduced by such postrandomization exclusions and the pursuant effects on type I error probabilities. Especially in a large study, the inflation in type I error probability can be severe, 0.50 or higher, even when the null hypothesis is true. Standard statistical methods for the analysis of censored or incomplete observations all require the assumption of missing at random to some degree, and none of these methods adjust for the potential bias introduced by post hoc subset selection. Nor is such adjustment possible unless one posits a model that relates the missing observations to other observed information for each subject-models that are inherently untestable. Further, the subset selection bias is confounded with the subset-specific treatment effect, and the two components are not identifiable without additional untestable assumptions. Methods for sensitivity analysis to assess the impact of bias in the efficacy subset analysis are described. It is generally believed that the efficacy subset analysis has greater power than the intent-to-treat analysis. However, even when the efficacy subset analysis is assumed to be unbiased, or have a true type I error probability equal to the desired level alpha, situations are described where the intent-to-treat analysis in fact has greater power than the efficacy subset analysis. The intent-to-treat design, wherein all possible patients continue to be followed, is especially powerful when an effective treatment arrests progression of disease during its administration. Thus, a patient benefits long after the patient becomes noncompliant or the treatment is terminated. In such cases, a landmark analysis using the observations from the last patient evaluation is likely to prove more powerful than life-table or longitudinal analyses. Examples are described.

The Intent

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The intent is the most difficult element to determine. To constitute genocide, there must be a proven intent on the part of perpetrators to physically destroy a national, ethnical, racial or religious group. Cultural destruction does not suffice, nor does an intention to simply disperse a group. It is this special intent, or dolus specialis, that makes the crime of genocide so unique. In addition, case law has associated intent with the existence of a State or organizational plan or policy, even if the definition of genocide in international law does not include that element.

The Intent History page of the developer console displays aggregated, anonymized frequent utterances and the resolved intents. You can use this to learn how users interact with your skill to identify improvements you may want to make to your interaction model. You can also map utterances to your intents and slots from this page.

The confidence that the utterance resolved to the correct intent. This can be HIGH. MEDIUM, or LOW. Note that LOW confidence requests are not sent to your skill as an intent request, but trigger a reprompt instead.

For example, suppose you see a particular utterance that was sent to AMAZON.FallbackIntent, but it is actually a reasonable phrase that should trigger one of your custom intents. You can map that utterance directly to that intent and update your interaction model right from the Intent History page.

After you map an utterance to a different intent or slot, the original utterance is moved to the Resolved Utterances tab. When the revised utterance is used frequently enough in the future to be included in the intent history, it is shown as a new utterance on the Unresolved Utterances tab.

Once an utterance is resolved in this way, it remains on the Resolved Utterances tab. If the same utterance meets the criteria to be included in the intent history in the future, it is still considered resolved and is displayed on the Resolved Utterances tab.

The AMAZON.FallbackIntent built-in intent is triggered when the user's utterance does not match any of your skill's intents. This intent displays just like the others on the Intent History page, so you can see frequent utterances that did not match your interaction model.

Under federal law, the possession of a controlled substance with the intent to sell or distribute it is a serious offense. To fully understand this crime, it helps to break it into two parts: (1) the possession of the drugs, and (2) the intent to distribute them. Both elements must be satisfied to commit the offense of "possession with the intent to distribute."

Under this element, the government must prove that the person possessing the drugs was planning to sell or otherwise distribute them. In the absence of incriminating statements from the defendant, intent is often proven by the surrounding circumstances. Typically, the intent to distribute controlled substances is assumed when the accused is holding an amount too large to be for only personal use. Some other indications that the possessor intended to sell the drugs include the presence of packaging materials, large amounts of money, and communications from customers.

One final point to highlight is that the crime cannot be proven unless possession of the drugs occurs simultaneously with intent to distribute them. For example, if someone has plans to sell ten kilograms of heroin next week, but they have not yet received the shipment of the drugs, prosecutors could not proceed with charges for possession with the intent to distribute -- because, after all, there was no possession. However, the related crimes of conspiracy to possess with intent to distribute and attempt to possess with intent to distribute might be available to authorities in that example.

Under federal law, the penalty for possession with the intent to distribute depends on the Federal Sentencing Guidelines. Judges must refer to the guidelines in imposing sentences. The length of imprisonment and the amount of monetary fines depends upon which controlled substances were involved and whether the defendant has a prior criminal history.

If you have been charged with possession with intent to distribute, you will need a strong advocate on your side. An experienced attorney can help develop a defense for your case. Find a qualified criminal defense lawyer near you today.

Can you provide me with some additional information regarding your setup? Is this deployment on all physical hardware, and does this hardware support RDMA? If this is a virtual environment for testing, it would be expected that some of the intent deployments will fail. If everything is physical, can you also confirm all of the pre-reqs have been installed that Network ATC needs (specifically Data Center Bridging)? It would appear from the output above the failure is coming from an attempt to create QoS policies, and the DCB feature is required for this to happen.

Per your screenshot, it does appear the pre-reqs have been added. Though one thing that sticks out to me is that in the output from Get-NetAdapterRdma, it shows that your NICs do not support PFC and ETS. I don't think this would prevent the intent to fail, it does concern me that the QoS policies would not adhered to correctly.

With just this output, I can't tell specifically why the intent failed, but you could attempt to collect a trace to determine the cause. You can do this by running Set-NetIntentTracing (no parameters), applying the intent again and letting it fail then stopping the trace using Set-NetIntentTracing -StopTracing. Convert the ETL trace directly on the HCI node using the steps provided in the output of the command (netsh trace convert) then open the resulting text file and look through the trace to see if you can find any clues to the issue.

I did some additional digging and found that this error can be caused when you already have a conflicting DCB configuration in place. Can you double-check and confirm if all prior configurations have been removed? You can use the steps documented here to ensure all previous configs are removed - -us/azure-stack/hci/manage/manage-network-atc#remove-an-intent.

Looking back at my original OP & subsequent replies, I realise now that I have not mentioned something important - We are getting the same ErrorActionPreference error message when creating an intent for Management using this command:

Thank you for also noting you are getting the same error when attempting to deploy the management intent. One thing I did notice from the command above is the variable you are using - %ClusterName%. Because you are using this within PowerShell, you have to use the $ to specify a variable. This could be the cause of the error as PowerShell would not be able to parse the %ClusterName%.

TheGoogle Maps app for Android exposes several intents that you can use to launch Google Maps in display,search, navigation, or Street View modes. If you want toembed a map in your app, please refer to the Google Maps Android APIGetting Started Guide. 041b061a72


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