Probing the intracellular refractive index and molecular interaction of gold nanoparticles in HeLa cells using single particle spectroscopy.

Background: We have introduced a novel method to quantify the intracellular refractive index (RI) of living cells and determine the molecular interaction of two interacting molecules using single particle spectroscopy. The advantages of this proposed technique over fluorescence-based imaging techniques is that it does not require any contrasting agent and it does not blink and bleach. Instead, our technique provides a non-destructive, non-invasive, high-resolution imaging of live cells.

Managing the Axilla in Early Breast Cancer. Impact of ACOSOG Z0011 Trial in Changing Practices in a Low Middle Income Country.

Objective: To determine the impact of the trial on surgeon practice patterns at our institution. Methodology: A comparison of patients undergoing surgery for early breast cancer before and after the implementation of the new guidelines was done. We adopted the new guidelines in April 2015.

Maternal colonization with Streptococcus agalactiae and associated stillbirth and neonatal disease in coastal Kenya.

Streptococcus agalactiae (group B streptococcus, GBS) causes neonatal disease and stillbirth, but its burden in sub-Saharan Africa is uncertain. We assessed maternal recto-vaginal GBS colonization (7,967 women), stillbirth and neonatal disease. Whole-genome sequencing was used to determine serotypes, sequence types and phylogeny.

A Gaussian Mixture Model-based continuous Boundary Detection for 3D sensor networks.

This paper proposes a high precision Gaussian Mixture Model-based novel Boundary Detection 3D (BD3D) scheme with reasonable implementation cost for 3D cases by selecting a minimum number of Boundary sensor Nodes (BNs) in continuous moving objects. It shows apparent advantages in that two classes of boundary and non-boundary sensor nodes can be efficiently classified using the model selection techniques for finite mixture models; furthermore, the set of sensor readings within each sensor node's spatial neighbors is formulated using a Gaussian Mixture Model; different from DECOMO [1] and COBOM [2], we also formatted a BN Array with an additional own sensor reading to benefit selecting Event BNs (EBNs) and non-EBNs from the observations of BNs. In particular, we propose a Thick Section Model (TSM) to solve the problem of transition between 2D and 3D.

Modeling the energy performance of event-driven wireless sensor network by using static sink and mobile sink.

Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc.