Hair Transplant for Eyebrow Restoration

Eyebrow restoration can be best done with individual single hair follicles grafts harvested by FUE. Understanding the male and female eyebrow allows us to plan an aesthetic reconstruction, requiring 70 to 120 grafts. Selection of donor hair, angle of placement, alignment and direction within the rows influences the results, as does scarring and perfusion of the skin. Details of planning, technique, anesthesia and postoperative care, as well as drawbacks of older methods, are discussed in the article.

In Lieu of GILTI

Prior to the 2017 tax reform (TCJA), with a few exceptions, the United States only taxed the foreign income of its domestic corporations when profits were distributed to its U.S. shareholders as dividends. Through this policy, the United States supported its domestic corporations’ active overseas business operations by allowing equal economic competition with foreign entities without the additional burden of paying the U.S. income tax. However, corporations were able to use this ability to electively defer U.S. tax on foreign income as a tax planning technique, which, in part, contributed to the accumulation of large amounts of untaxed “offshore” earnings by U.S. multinational corporations. The U.S. Congress essentially terminated deferral and this tax planning technique when it enacted the current tax on global intangible low-taxed income (GILTI) as part of the TCJA. But GILTI is a formulaic calculation that taxes income regardless of the taxpayer’s intent, use of profits, or the income’s potential for aggressive tax planning. Although GILTI protects against the use of aggressive tax planning techniques, it compromises the tax policy goal of allowing U.S. corporations to compete in foreign jurisdictions unhindered by the U.S. income tax. In lieu of GILTI and the section 245A deduction, this Article proposes a new Subpart F inclusion for excessive unrepatriated earnings based on the concept of distributable net income. This proposal would be superior to the current GILTI regime because it would allow multinational corporations to use deferral for the beneficial goal of supporting foreign active business operations, but would prevent the use of deferral for tax planning purposes.

Multirobot Formation with Sensor Fusion-Based Localization in Unknown Environment

Multirobot cooperation enhancing the efficiency of numerous applications such as maintenance, rescue, inspection in cluttered unknown environments is the interesting topic recently. However, designing a formation strategy for multiple robots which enables the agents to follow the predefined master robot during navigation actions without a prebuilt map is challenging due to the uncertainties of self-localization and motion control. In this paper, we present a multirobot system to form the symmetrical patterns effectively within the unknown environment deployed randomly. To enable self-localization during group formatting, we propose the sensor fusion system leveraging sensor fusion from the ultrawideband-based positioning system, Inertial Measurement Unit orientation system, and wheel encoder to estimate robot locations precisely. Moreover, we propose a global path planning algorithm considering the kinematic of the robot’s action inside the workspace as a metric space. Experiments are conducted on a set of robots called Falcon with a conventional four-wheel skid steering schematic as a case study to validate our proposed path planning technique. The outcome of our trials shows that the proposed approach produces exact robot locations after sensor fusion with the feasible formation tracking of multiple robots system on the simulated and real-world experiments.

SACBP: Belief space planning for continuous-time dynamical systems via stochastic sequential action control

We propose a novel belief space planning technique for continuous dynamics by viewing the belief system as a hybrid dynamical system with time-driven switching. Our approach is based on the perturbation theory of differential equations and extends sequential action control to stochastic dynamics. The resulting algorithm, which we name SACBP, does not require discretization of spaces or time and synthesizes control signals in near real-time. SACBP is an anytime algorithm that can handle general parametric Bayesian filters under certain assumptions. We demonstrate the effectiveness of our approach in an active sensing scenario and a model-based Bayesian reinforcement learning problem. In these challenging problems, we show that the algorithm significantly outperforms other existing solution techniques including approximate dynamic programming and local trajectory optimization.