Anomalous Lattice Vibrations of Single and Few-Layer MoS2

Molybdenum disulfide (MoS2) of single and few-layer thickness was exfoliated on SiO2/Si substrate and characterized by Raman spectroscopy. The number of S-Mo-S layers of the samples was independently determined by contact-mode atomic-force microscopy. Two Raman modes, E12g and A1g, exhibited sensitive thickness dependence, with the frequency of the former decreasing and that of the latter increasing with thickness. The results provide a convenient and reliable means for determining layer thickness with atomic-level precision. The opposite direction of the frequency shifts, which cannot be explained solely by van der Waals interlayer coupling, is attributed to Coulombic interactions and possible stacking-induced changes of the intralayer bonding. This work exemplifies the evolution of structural parameters in layered materials in changing from the 3-dimensional to the 2-dimensional regime.Comment: 14 pages, 4 figure

An Examination of Inclusive Practices for Students with Learning Disabilities in Botswana: A Literature Review

The country of Botswana has passed laws to support the human rights of their citizens, including people with learning disabilities. In accordance with the United Nations’ guidelines, Botswana’s human rights initiatives, and the international movement toward inclusive education, inclusive educational reform is taking place. We have conducted a comprehensive literature review, the purpose of which was to establish the progress Botswana has made in special education policy, implementation of policy into schools, and the strides made toward inclusion. However, there are still many struggles comparable to many school systems in African nations. Key findings include a nation with significant developments in human rights which includes a developing inclusive education system with both policy and implementation, yet, still coping with the growing pains of a young special education program

Finding anomalies in high-density LiDAR point clouds

Modern three-dimensional (3D) terrestrial scanning systems such as the TITAN system make it possible to acquire precise, geo-referenced datasets over areas spanning many square kilometers. These systems consist of several vehicle-mounted lasers for acquiring point data, a high-precision GPS unit for providing geo-reference data, and an inertial measurement unit (IMU) for tracking vehicle motion. Two liabilities of this type of approach are that the navigational accuracy degrades when the GPS signal is lost, and moving objects can cause data artifacts. These induce particular anomalies in the acquired data that must be eventually corrected, often by hand, during the post-processing stage. The goal of this paper is to show that by exploiting the configuration of the LiDAR sensors, such anomalies can often be detected automatically from the dataset. In particular, we demonstrate that under an appropriate tessellation, iterative closest point (ICP) algorithms can be used to reliably localize anomalies and provide an estimate of their magnitude