The IRS Collection Division: Contacts and Settlements

In his study -The IRS Collection Division: Contacts and Settlements - by John M. Tarras, Assistant Professor School of Hotel, Restaurant and Institutional Management, Michigan State University, Tarras initially states: “The collection division of the internal revenue service is often the point of contact for many hospitality businesses. The author describes how the division operates, what the hospitality firm can expect when contacted by it, and what types of strategies firms might find helpful when negotiating a settlement with the IRS.” The author will have you know that even though most chance meetings with the IRS Collection Division are due to unfortunate tax payment circumstances, there are actually more benign reasons for close encounters of the IRS kind. This does not mean, however, that brushes with the IRS Collection Division will end on an ever friendlier note. “…the Tax Reform Act of 1986 with its added complexity will cause some hospitality firms to inadvertently fail to make proper payments on a timely basis,” Tarras affords in illustrating a perhaps less pugnacious side of IRS relations. Should a hospitality business owner represent himself/herself before the IRS? Never, says Tarras. “Too many taxpayers ruin their chances of a fair settlement by making what to them seem innocent remarks, but ones that turn out to be far different,” warns Professor Tarras. Tarras makes the distinction between IRS the Collection Division, and IRS the Audit Division. “While the Audit Division is interested in how the tax liability arose, the Collection Division is generally only interested in collecting the liability,” he informs you. Either sounds firmly in hostile territory. They don’t bluff. Tarras does want you to know that when the IRS threatens to levy on the assets of a hospitality business, they will do so. Those assets may extend to personal and real property as well, he says. The levy action is generally the final resort in an IRS collection effort. Professor Tarras explains the lien process and the due process attached to that IRS collection tactic. “The IRS can also levy a hospitality firm owner's wages. In this case, it is important to realize that you are allowed to exempt from levy $75 per week, along with $25 per week for each of your dependents (unless your spouse works),” Professor Tarras says with the appropriate citation. What are the options available to the hospitality business owner who finds himself on the wrong side of the IRS Collection Division? Negotiate in good faith says Professor Tarras. “In many cases, a visit to the IRS office will greatly reduce the chances that a simple problem will turn into a major one,” Tarras advises. He dedicates the last pages of the discussion to negotiation strategies.

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as “histogram binning” inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. ^ Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. ^ The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. ^ These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. ^ In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation. ^

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as "histogram binning" inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation.