Subdiffraction optical resolution of a gold nanosphere located within the nanojet of a Mie-resonant dielectric microsphere

pre-printWe theoretically investigate light scattering from a bi-sphere system consisting of a gold nanosphere and a lossless dielectric microsphere illuminated at a resonant optical wavelength of the microsphere. Using generalized multisphere Mie theory, we find that a gold nanosphere 100 times smaller than the dielectric microsphere can be detected with a subdiffraction resolution as fine as one-third wavelength in the background medium when the microsphere is illuminated at a Mie resonance. Otherwise, off-resonance, the spatial resolution reverts to that of the nonresonant nanojet, approximately one-half wavelength in the background medium. An important potential biophotonics application is the detection of antibody-conjugated gold nanoparticles attached to the membranes of living cells in an aqueous environment

Finite-difference time-domain modeling of free induction decay signal in chirped pulse millimeter wave spectroscopy

We have developed computational electrodynamics model of free induction decay (FID) signal in chirped pulse millimeter wave (CPMMW) spectroscopy. The computational model is based on finite-difference time-domain (FDTD) solution of Maxwell’s equations in 1-D. Molecular medium is represented by two-level system derived using density matrix (DM) formulation. Each cell in the grid is assigned an independent set of DM equations, and thus acts as an independent source of induced polarization. Computer simulations with our 1-D model have shown that FID signal is propagating entirely in the forward direction. Intensity of FID radiation increases linearly along the cell length. These results can be explained analytically by considering phases of electromagnetic field radiated by each independent region of induced polarization. We show that there is constructive interference in the forward in forward direction, and destructive interference in backscattering direction. Results in this study are consistent with experimental observations that FID has been measured in the forward scattering direction, but not in backscattering direction

Using the fragment molecular orbital method to investigate agonist–orexin-2 receptor interactions

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity and is essential for an efficient structure-based drug discovery (SBDD) process. Clearly, to begin SBDD, a structure is needed, and although there has been fantastic progress in solving G-protein-coupled receptor (GPCR) crystal structures, the process remains quite slow and is not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of X-ray crystallography to impact the drug discovery process for GPCR targets in 'real-time' and hence there is still a need for other practical and cost-efficient alternatives. We present here an approach that integrates our previously described hierarchical GPCR modelling protocol (HGMP) and the fragment molecular orbital (FMO) quantum mechanics (QM) method to explore the interactions and selectivity of the human orexin-2 receptor (OX2R) and its recently discovered nonpeptidic agonists. HGMP generates a 3D model of GPCR structures and its complexes with small molecules by applying a set of computational methods. FMO allowsab initioapproaches to be applied to systems that conventional QM methods would find challenging. The key advantage of FMO is that it can reveal information on the individual contribution and chemical nature of each residue and water molecule to the ligand binding that normally would be difficult to detect without QM. We illustrate how the combination of both techniques provides a practical and efficient approach that can be used to analyse the existing structure-function relationships (SAR) and to drive forward SBDD in a real-world example for which there is no crystal structure of the complex available

Assessment of Hydration Thermodynamics at Protein Interfaces with Grid Cell Theory

Molecular dynamics simulations have been analyzed with the Grid Cell Theory (GCT) method to spatially resolve the binding enthalpies and entropies of water molecules at the interface of 17 structurally diverse proteins. Correlations between computed energetics and structural descriptors have been sought to facilitate the development of simple models of protein hydration. Little correlation was found between GCT-computed binding enthalpies and continuum electrostatics calculations. A simple count of contacts with functional groups in charged amino acids correlates well with enhanced water stabilization, but the stability of water near hydrophobic and polar residues depends markedly on its coordination environment. The positions of X-ray-resolved water molecules correlate with computed high-density hydration sites, but many unresolved waters are significantly stabilized at the protein surfaces. A defining characteristic of ligand-binding pockets compared to nonbinding pockets was a greater solvent-accessible volume, but average water thermodynamic properties were not distinctive from other interfacial regions. Interfacial water molecules are frequently stabilized by enthalpy and destabilized entropy with respect to bulk, but counter-examples occasionally occur. Overall detailed inspection of the local coordinating environment appears necessary to gauge the thermodynamic stability of water in protein structures

Shade : a differentially private wrapper around Apache Spark

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 85-88).Enterprises usually provide strong controls to prevent external cyberattacks and inadvertent leakage of data to external entities. However, in the case where employees and data scientists have legitimate access to analyze and derive insights from the data, there are insufficient controls and employees are usually permitted access to all information about the customers of the enterprise including sensitive and private information. Though it is important to be able to identify useful patterns of one's customers for better customization and service, customers' privacy must not be sacrificed to do so. We propose an alternative - a framework that will allow privacy preserving data analytics over big data. In this paper, we present an efficient and scalable framework for Apache Spark, a cluster computing framework, that provides strong privacy guarantees for users even in the presence of an informed adversary, while still providing high utility for analysts in an interactive wrapper. The framework, titled Shade, includes two mechanisms - SparkLAP, which provides Laplacian perturbation based on a user's query and SparkSAM, which uses the contents of the database itself in order to calculate the perturbation. We show that performance of Shade is substantially better than earlier differential privacy systems without loss of accuracy, particularly when run on datasets small enough to fit in memory, and find that SparkSAM can even exceed performance of an identical non-private Spark query.by Alexander G. Heifetz.M. Eng