First-principles study of MoS2_2 and MoSe2_2 nanoclusters in the framework of evolutionary algorithm and density functional theory

Evolutionary algorithm is combined with full-potential ab-initio calculations to investigate conformational space of (MoS$_2$)$_n$ and (MoSe$_2$)$_n$ (n=1-10) nanoclusters and to identify the lowest energy structural isomers of these systems. It is argued that within both BLYP and PBE functionals, these nanoclusters favor sandwiched planar configurations, similar to their ideal planar sheets. The second order difference in total energy ($\Delta_2$E) of the lowest energy isomers are computed to estimate the abundance of the clusters at different sizes and to determine the magic sizes of (MoS$_2$)$_n$ and (MoSe$_2$)$_n$ nanoclusters. In order to investigate the electronic properties of nanoclusters, their energy gap is calculated by several methods, including hybrid functionals (B3LYP and PBE0), GW approach, and $\Delta$scf method. At the end, the vibrational modes of the lowest lying isomers are calculated by using the force constants method and the IR active modes of the systems are identified. The vibrational spectra are used to calculate the Helmholtz free energy of the systems and then to investigate abundance of the nanoclusters at finite temperatures.Comment: 6 figures; 3 table

Augmenting Visual SLAM with Wi-Fi Sensing For Indoor Applications

Recent trends have accelerated the development of spatial applications on mobile devices and robots. These include navigation, augmented reality, human-robot interaction, and others. A key enabling technology for such applications is the understanding of the device's location and the map of the surrounding environment. This generic problem, referred to as Simultaneous Localization and Mapping (SLAM), is an extensively researched topic in robotics. However, visual SLAM algorithms face several challenges including perceptual aliasing and high computational cost. These challenges affect the accuracy, efficiency, and viability of visual SLAM algorithms, especially for long-term SLAM, and their use in resource-constrained mobile devices. A parallel trend is the ubiquity of Wi-Fi routers for quick Internet access in most urban environments. Most robots and mobile devices are equipped with a Wi-Fi radio as well. We propose a method to utilize Wi-Fi received signal strength to alleviate the challenges faced by visual SLAM algorithms. To demonstrate the utility of this idea, this work makes the following contributions: (i) We propose a generic way to integrate Wi-Fi sensing into visual SLAM algorithms, (ii) We integrate such sensing into three well-known SLAM algorithms, (iii) Using four distinct datasets, we demonstrate the performance of such augmentation in comparison to the original visual algorithms and (iv) We compare our work to Wi-Fi augmented FABMAP algorithm. Overall, we show that our approach can improve the accuracy of visual SLAM algorithms by 11% on average and reduce computation time on average by 15% to 25%.Comment: 16 pages, 19 figures, Autonomous Robots Journal submission (AuRo

The overlooked role of band-gap parameter in characterization of Landau levels in a gapped phase semi-Dirac system: the monolayer phosphorene case

Two-dimensional gapped semi-Dirac (GSD) materials are systems with a finite band gap that their charge carriers behave relativistically in one direction and Schr\"odinger-like in the other. In the present work, we show that besides the two well-known energy bands features (curvature and chirality), the band-gap parameter also play a crucial role in the index- and magnetic field-dependence of the Landau levels (LLs) in a GSD system. We take the monolayer phosphorene as a GSD representative example to explicitly provide physical insights into the role of this parameter in determining the index- and magnetic field-dependence of LLs. We derive an effective one-dimensional Schr\"odinger equation for charge carriers in the presence of a perpendicular magnetic field and argue that the form of its effective potential is clearly sensitive to a dimensionless band-gap that is tunable by structural parameters. The theoretical magnitude of this effective gap and its interplay with oval shape $k$-space cyclotron orbits resolve the seeming contradiction in determining the type of the quantum Hall effect in the pristine monolayer phosphorene. Our results strongly confirm that the dependence of LLs on the magnetic field in this GSD material is as conventional two-dimensional semiconductor electron gases up to a very high field regime. Using the strain-induced gap modification scheme, we show the field dependence of the LLs continuously evolves into $B^{2/3}$ behavior, which holds for a gapless semi-Dirac system. The highlighted role of the band-gap parameter may affect the consequences of the band anisotropy in the physical properties of a GSD material, including magnetotransport, optical conductivity, dielectric function, and thermoelectric performance

An Introductory Guide to Aligning Networks Using SANA, the Simulated Annealing Network Aligner.

Sequence alignment has had an enormous impact on our understanding of biology, evolution, and disease. The alignment of biological networks holds similar promise. Biological networks generally model interactions between biomolecules such as proteins, genes, metabolites, or mRNAs. There is strong evidence that the network topology-the "structure" of the network-is correlated with the functions performed, so that network topology can be used to help predict or understand function. However, unlike sequence comparison and alignment-which is an essentially solved problem-network comparison and alignment is an NP-complete problem for which heuristic algorithms must be used.Here we introduce SANA, the Simulated Annealing Network Aligner. SANA is one of many algorithms proposed for the arena of biological network alignment. In the context of global network alignment, SANA stands out for its speed, memory efficiency, ease-of-use, and flexibility in the arena of producing alignments between two or more networks. SANA produces better alignments in minutes on a laptop than most other algorithms can produce in hours or days of CPU time on large server-class machines. We walk the user through how to use SANA for several types of biomolecular networks