Situation-Aware Rate and Power Adaptation Techniques for IEEE 802.11

The current generation of IEEE 802.11 Wireless Local Area Networks (WLANs) provide multiple data rates from which the different physical (PHY) layers may choose. The rate adaptation algorithm (RAA) is an essential component of 802.11 WLANs which completely determines the data rate a device may use. Some of the key challenges facing data rate selection are the constantly varying wireless channel, selecting the data rate that will result in the maximum throughput, assessing the conditions based on limited feedback and estimating the link conditions at the receiver. Current RAAs lack the ability to sense their environment and adapt accordingly. 802.11 WLANs are deployed in many locations and use the same technique to choose the data rate in all locations and situations. Therefore, these RAAs suffer from the inability to adapt the method they use to choose the data transmission rate. In this thesis, a new RAA for 802.11 WLANs is proposed which provides an answer to the many challenges faced by RAAs. The proposed RAA is termed SARA which stands for Situation-Aware Rate Adaptation, and combines the use of the received signal strength and packet error rate to enable situational awareness. SARA adapts to the current environmental situation experienced at the moment to rapidly take advantage of changing channel conditions. In addition to SARA, a method to optimize the transmission power for, but not limited to, IEEE 802.11 WLANs is proposed which can determine the minimum transmission power required by a station (STA) or base station (BS) for successful transmission of a data packet. The technique reduces the transmission power to the minimum level based on the current situation while maintaining QoS constraints. The method employs a Binary Search to quickly determine the minimum transmission power with low complexity and delay. Such a technique is useful to conserve battery life in mobile devices for 802.11 WLANs. Both algorithms are implemented on an Atheros device driver for the FreeBSD operating system. SARA is compared to the benchmark algorithm SampleRate while an estimate of the energy consumed as well as the energy saved is provided for the minimum transmission power determination

Initial photophysical characterization of the proteorhodopsin optical proton sensor (PROPS)

Fluorescence is not frequently used as a tool for investigating the photocycles of rhodopsins, largely because of the low quantum yield of the retinal chromophore. However, a new class of genetically encoded voltage sensors is based upon rhodopsins and their fluorescence. The first such sensor reported in the literature was the proteorhodopsin optical proton sensor (PROPS), which is capable of indicating membrane voltage changes in bacteria by means of changes in fluorescence. However, the properties of this fluorescence, such as its lifetime decay components and its origin in the protein photocycle, remain unknown. This paper reports steady-state and nanosecond time-resolved emission of this protein expressed in two strains of Escherichia coli, before and after membrane depolarization. The voltage-dependence of a particularly long lifetime component is established. Additional work to improve quantum yields and improve the general utility of PROPS is suggested

Sources and propagation of errors in quantitative phase imaging techniques using optical interferometry

Quantitative phase imaging (QPI) has many applications in a broad range of disciplines from astronomy to microbiology. QPI is often performed by optical interferometry, where two coherent beams of light are used to produce interference patterns at a detector plane. Many algorithms exist to calculate the phase of the incident light from these recorded interference patterns as well as enhance their quality by various de-noising methods. Many of these de-noising algorithms, however, corrupt the quantitative aspect of the measurement, resulting in phase contrast images. Among these phase calculation techniques and de-noising algorithms, none approach the optimization of phase measurements by theoretically addressing the various sources of error in its measurement, as well as how these errors propagate to the phase calculations. In this work, we investigate the various sources of error in the measurements required for QPI, as well as theoretically derive the influence of each source of error on the overall phase calculation for three common phase calculation techniques: the four bucket/step method, three bucket/step method, and the Carré method. The noise characteristics of each of these techniques are discussed and compared using error parameters of a readily available CCD sensor array. Additionally, experimental analysis is conducted on interferograms to investigate the influence of speckle noise on the phase measurements of the three algorithms discussed

A machine learning algorithm for identifying and tracking bacteria in three dimensions using Digital Holographic Microscopy

Digital Holographic Microscopy (DHM) is an emerging technique for three-dimensional imaging of microorganisms due to its high throughput and large depth of field relative to traditional microscopy techniques. While it has shown substantial success for use with eukaryotes, it has proven challenging for bacterial imaging because of low contrast and sources of noise intrinsic to the method (e.g. laser speckle). This paper describes a custom written MATLAB routine using machine-learning algorithms to obtain three-dimensional trajectories of live, lab-grown bacteria as they move within an essentially unrestrained environment with more than 90% precision. A fully annotated version of the software used in this work is available for public use

Differential toxicity of gold-doxorubicin in cancer cells vs. cardiomyocytes as measured by real-time growth assays and fluorescence lifetime imaging microscopy (FLIM)

The kinetics of toxicity of doxorubicin (Dox) and gold nanoparticle-conjugated doxorubicin (Au-Dox) were investigated in cultured B16 melanoma cells and cardiomyocytes using real-time cell-growth imaging. Both bolus exposure and continuous exposure were used. Modeling of the growth curve dynamics suggested patterns of uptake and/or expulsion of the drug that were different for the different cell lines and exposures. Dox alone in B16 cells fit to a model of slow drug buildup, whereas Au-Dox fit to a pattern of initial high drug efficacy followed by a decrease. In cardiomyocytes, the best fit was to a model of increasing drug concentration which then began to decrease, consistent with breakdown of the doxorubicin in solution. Cardiomyocytes were more sensitive than B16 cells to Dox alone (IC_(50) 123 ± 2 nM vs. 270 ± 2 nM with continuous exposure), but were dramatically less sensitive to Au-Dox (IC_(50) 1 ± 0.1 μM vs. 58 ± 5 nM with continuous exposure). Bolus exposure for 40 min led to significant cell death in B16 cells but not in cardiomyocytes. Fluorescence lifetime imaging (FLIM) showed different patterns of uptake of Au-Dox in the two cell types that explained the differential toxicity. While Au-Dox concentrated in the nuclei of B16 cells, it remained endosomal in cardiomyocytes. These results suggest that stable conjugates of nanoparticles to doxorubicin may be useful for treating resistant cancers while sparing healthy tissue

Use of dyes to increase phase contrast for biological holographic microscopy

Holographic microscopy is an emerging biological technique that provides amplitude and quantitative phase imaging, though the contrast provided by many cell types and organelles is low, and until now no dyes were known that increased contrast. Here we show that the metallocorrole Ga(tpfc)(SO_3H)_2, which has a strong Soret band absorption, increases contrast in both amplitude and phase and facilitates tracking of Escherichia coli with minimal toxicity. The change in phase contrast may be calculated from the dye-absorbance spectrum using the Kramers–Kronig relations, and represents a general principle that may be applied to any dye or cell type. This enables the use of holographic microscopy for all applications in which specific labeling is desired

Compact, lensless digital holographic microscope for remote microbiology

In situ investigation of microbial life in extreme environments can be carried out with microscopes capable of imaging 3-dimensional volumes and tracking particle motion. Here we present a lensless digital holographic microscope approach that provides roughly 1.5 micron resolution in a compact, robust package suitable for remote deployment. High resolution is achieved by generating high numerical-aperture input beams with radial gradient-index rod lenses. The ability to detect and track prokaryotes was explored using bacterial strains of two different sizes. In the larger strain, a variety of motions were seen, while the smaller strain was used to demonstrate a detection capability down to micron scales

Microbial Morphology and Motility as Biosignatures for Outer Planet Missions

Meaningful motion is an unambiguous biosignature, but because life in the Solar System is most likely to be microbial, the question is whether such motion may be detected effectively on the micrometer scale. Recent results on microbial motility in various Earth environments have provided insight into the physics and biology that determine whether and how microorganisms as small as bacteria and archaea swim, under which conditions, and at which speeds. These discoveries have not yet been reviewed in an astrobiological context. This paper discusses these findings in the context of Earth analog environments and environments expected to be encountered in the outer Solar System, particularly the jovian and saturnian moons. We also review the imaging technologies capable of recording motility of submicrometer-sized organisms and discuss how an instrument would interface with several types of sample-collection strategies