We investigate the effect of Rashba spin-orbit coupling (SOC) on the optoelectronic properties of n- and p-type monolayer MoS2. The optical conductivity is calculated within the Kubo formalism. We find that the spin-flip transitions enabled by the Ra
shba SOC result in a wide absorption window in the optical spectrum. Furthermore, we evaluate the effects of the polarization direction of the radiation, temperature, carrier density, and the strength of the Rashba spin-orbit parameter on the optical conductivity. We find that the position, width, and shape of the absorption peak or absorption window can be tuned by varying these parameters. This study shows that monolayer MoS2 can be a promising tunable optical and optoelectronic material that is active in the infrared to terahertz spectral range.
The discovery of the hydrodynamic electron liquid (HEL) in graphene [D. Bandurin emph{et al.}, Science {bf 351}, 1055 (2016) and J. Crossno emph{et al.}, Science {bf 351}, 1058 (2016)] has marked the birth of the solid-state HEL which can be probed n
ear room temperature in a table-top setup. Here we examine the terahertz (THz) magneto-optical (MO) properties of a graphene HEL. Considering the case where the magnetic length $l_B=sqrt{hbar/eB}$ is comparable to the mean-free path $l_{ee}$ for electron-electron interaction in graphene, the MO conductivities are obtained by taking a momentum balance equation approach on the basis of the Boltzmann equation. We find that when $l_Bsim l_{ee}$, the viscous effect in a HEL can weaken significantly the THz MO effects such as cyclotron resonance and Faraday rotation. The upper hybrid and cyclotron resonance magnetoplasmon modes $omega_pm$ are also obtained through the RPA dielectric function. The magnetoplasmons of graphene HEL at large wave-vector regime are affected by the viscous effect, and results in red-shifts of the magnetoplasmon frequencies. We predict that the viscosity in graphene HEL can affect strongly the magneto-optical and magnetoplasmonic properties, which can be verified experimentally.
Deep brain stimulation (DBS) is an effective therapy as an alternative to pharmaceutical treatments for Parkinsons disease (PD). Aside from factors such as instrumentation, treatment plans, and surgical protocols, the success of the procedure depends
heavily on the accurate placement of the electrode within the optimal therapeutic targets while avoiding vital structures that can cause surgical complications and adverse neurologic effects. While specific surgical techniques for DBS can vary, interventional guidance with medical imaging has greatly contributed to the development, outcomes, and safety of the procedure. With rapid development in novel imaging techniques, computational methods, and surgical navigation software, as well as growing insights into the disease and mechanism of action of DBS, modern image guidance is expected to further enhance the capacity and efficacy of the procedure in treating PD. This article surveys the state-of-the-art techniques in image-guided DBS surgery to treat PD, and discuss their benefits and drawbacks, as well as future directions on the topic.
In brain tumor surgery, the quality and safety of the procedure can be impacted by intra-operative tissue deformation, called brain shift. Brain shift can move the surgical targets and other vital structures such as blood vessels, thus invalidating t
he pre-surgical plan. Intra-operative ultrasound (iUS) is a convenient and cost-effective imaging tool to track brain shift and tumor resection. Accurate image registration techniques that update pre-surgical MRI based on iUS are crucial but challenging. The MICCAI Challenge 2018 for Correction of Brain shift with Intra-Operative UltraSound (CuRIOUS2018) provided a public platform to benchmark MRI-iUS registration algorithms on newly released clinical datasets. In this work, we present the data, setup, evaluation, and results of CuRIOUS 2018, which received 6 fully automated algorithms from leading academic and industrial research groups. All algorithms were first trained with the public RESECT database, and then ranked based on test dataset of 10 additional cases with identical data curation and annotation protocols as the RESECT database. The article compares the results of all participating teams and discusses the insights gained from the challenge, as well as future work.
