This work is focused on the issue of wireless networks according to the IEEE 802.11 standard. The main subject of research is the Rate Adaptation Algorithms (RAA). The work also contains a description of simulation environments NS-3 and OMNeT in terms of adaptation algorithms. At the end of the work there is a summary of wireless network simulations in NS-3 and OMNeT environments and their comparison with the actual measurement of network parameters.

Indiana University-Purdue University Indianapolis (IUPUI) / The DNA Base Excision Repair (BER) pathway repairs DNA damaged by endogenous and exogenous agents including chemotherapeutic agents. Removal of the damaged base by a DNA glycosylase creates an apurinic / apyrimidinic (AP) site. AP endonuclease1 (Ape1), a critical component in this pathway, hydrolyzes the phosphodiester backbone 5’ to the AP site to facilitate repair. Additionally, Ape1 also functions as a redox factor, known as Ref-1, to reduce and activate key transcription factors such as AP-1 (Fos/Jun), p53, HIF-1α and others. Elevated Ape1 levels in cancers are indicators of poor prognosis and chemotherapeutic resistance, and removal of Ape1 via methodology such as siRNA sensitizes cancer cell lines to chemotherapeutic agents. However, since Ape1 is a multifunctional protein, removing it from cells not only inhibits its DNA repair activity but also impairs its other functions. Our hypothesis is that a small molecule inhibitor of the DNA repair activity of Ape1 will help elucidate the importance (role) of its repair function in cancer progression as wells as tumor drug response and will also give us a pharmacological tool to enhance cancer cells’ sensitivity to chemotherapy. In order to discover an inhibitor of Ape1’s DNA repair function, a fluorescence-based high-throughput screening (HTS) assay was used to screen a library of drug-like compounds. Four distinct compounds (AR01, 02, 03 and 06) that inhibited Ape1’s DNA repair activity were identified. All four compounds inhibited the DNA repair activity of purified Ape1 protein and also inhibited Ape1’s activity in cellular extracts. Based on these and other in vitro studies, AR03 was utilized in cell culture-based assays to test our hypothesis that inhibition of the DNA repair activity of Ape1 would sensitize cancer cells to chemotherapeutic agents. The SF767 glioblastoma cell line was used in our assays as the chemotherapeutic agents used to treat gliobastomas induce lesions repaired by the BER pathway. AR03 is cytotoxic to SF767 glioblastoma cancer cells as a single agent and enhances the cytotoxicity of alkylating agents, which is consistent with Ape1’s inability to process the AP sites generated. I have identified a compound, which inhibits Ape1’s DNA repair activity and may have the potential in improving chemotherapeutic efficacy of selected chemotherapeutic agents as well as to help us understand better the role of Ape1’s repair function as opposed to its other functions in the cell.

Master of Science / Department of Agronomy / William T. Schapaugh / Remote sensing technologies might serve as indirect selection tools to improve phenotyping to differentiate genotypes for yield in soybean breeding program as well as the assessment of soybean cyst nematode (SCN), Heterodera glycines. The objective of these studies were to: i) investigate potential use of spectral reflectance indices (SRIs) and canopy temperature (CT) as screening tools for soybean grain yield in an elite, segregating population; ii) determine the most appropriate growth stage(s) to measure SRI’s for predicting grain yield; and iii) estimate SCN population density among and within soybean cultivars utilizing canopy spectral reflectance and canopy temperature. Experiment 1 was conducted at four environments (three irrigated and one rain-fed) in Manhattan, KS in 2012 and 2013. Each environment evaluated 48 F4- derived lines. In experiment 2, two SCN resistant cultivars and two susceptible cultivars were grown in three SCN infested field in Northeast KS, in 2012 and 2013. Initial (Pi) and final SCN soil population (Pf) densities were obtained. Analyses of covariance (ANCOVA) revealed that the green normalized vegetation index (GNDVI) was the best predictive index for yield compared to other SRI’s and differentiated genotype performance across a range of reproductive growth stages. CT did not differentiate genotypes across environments. In experiment 2, relationships between GNDVI, reflectance at single wavelengths (675 and 810 nm) and CT with Pf were not consistent across cultivars or environments. Sudden death syndrome (SDS) may have confounded the relationships between remote sensing data and Pf. Therefore, it would be difficult to assess SCN populations using remote sensing based on these results.

ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California / The integrated Network Enhanced Telemetry effort (iNET) was launched to create a telemetry network that will enhance the traditional point-to-point telemetry link from test articles (TAs) to ground stations (GS). Two of the critical needs identified by the Central Test and Evaluation Investment Program (CTEIP) are, "the need to be able to provide reliable coverage in potentially high capacity environments, even in Over-The-Horizon (OTH) settings", and "the need to make more efficient use of spectrum resources through dynamic sharing of said resources, based on instantaneous demand thereof". Research conducted at Morgan State University (MSU) has focused on providing solutions for both critical problems. The Mixed Network architecture developed by MSU has shown that a hybrid network can be used to provide coverage for TAs that are beyond the coverage area of the GS. The mixed network uses clustering techniques to partition the aggregate network into clusters or sub-networks based on properties of each TA, which currently include signal strengths, and location. The paper starts with a detailed analysis of two parameters that affect the performance of each sub-network: contention between the TAs in the mobile ad-hoc network, and queuing at the Gateway TAs that serve as the link between the mobile ad-hoc and the Cellular networks. Contention and queuing will be used to evaluate two performance (distance) measures for each sub-network: throughput and delay. We define a new distance measure known as "power", which is equal to the ratio of throughput over delay, and is used as a measure of performance of the mixed network for Quality of Service (QOS). This paper describes the analytical foundation used to prove that the "power" performance measure is an excellent tool for optimizing the clustering of a mixed network to provide QOS.

The increased use of mass spectrometry in the clinical setting has led to a demand for high sample throughput. Developments such as ultra high performance liquid chromatography and the ambient ionization techniques enable high sample throughput by reducing chromatographic run times or by removing the requirement for sample preparation and fractionation prior to analysis. This thesis assesses the reproducibility and robustness of these high throughput techniques for the analysis of clinical and pharmaceutical samples by ion mobility-mass spectrometry. The rapid quantitative analysis of the urinary biomarkers of chronic obstructive pulmonary disease, desmosine and isodesmosine has been performed by ultra high performance liquid chromatography combined with ion mobility-mass spectrometry. The determination of health status based on the free unbound fraction rather than the total bound and unbound desmosine and isodesmosine, significantly reduces the time taken in sample preparation. The potential for direct analysis of the urinary metabolites from undeveloped TLC plates using a solvent extraction surface sample probe is demonstrated. The use of a solvent gradient for the extraction separates urinary metabolites from salts and other matrix components and allows fractionation of the sample as a result of differential retention on the undeveloped RP-TLC plate. This separation, combined with ion mobility-mass spectrometry provides a rapid ambient ionization method for urinary profiling. The combination of a thermal desorption probe with extractive electrospray ionization has been applied to the direct detection of a known genotoxic impurity from a surrogate active pharmaceutical ingredient. The volatility of the impurity compared to the matrix, allowed selective thermal desorption of the analyte, which was ionized by extractive electrospray and detected by mass spectrometry. The use of a rapid on-probe derivatisation reaction, combined with thermal desorption is demonstrated for the direct determination of urinary creatinine. The aqueous acylation of creatinine significantly increases the volatility of the analyte enabling separation from the urine matrix and analysis by thermal desorption extractive electrospray combined with ion mobility-mass spectrometry.

This project presents a mechanism for instrumentation of secure VoIP calls. The experiments were run under different network conditions and security systems. VoIP services such as Google Talk, Express Talk and Skype were under test. The project allowed analysis of the voice quality of the VoIP services based on the Mean Opinion Score (MOS) values generated by Perceptual valuation of Speech Quality (PESQ). The quality of the audio streams produced were subjected to end-to-end delay, jitter, packet loss and extra processing in the networking hardware and end devices due to Internetworking Layer security or Transport Layer security implementations. The MOS values were mapped to Perceptual Evaluation of Speech Quality for wideband (PESQ-WB) scores. From these PESQ-WB scores, the graphs of the mean of 10 runs and box and whisker plots for each parameter were drawn. Analysis on the graphs was performed in order to deduce the quality of each VoIP service. The E-model was used to predict the network readiness and Common vulnerability Scoring System (CVSS) was used to predict the network vulnerabilities. The project also provided the mechanism to measure the throughput for each test case. The overall performance of each VoIP service was determined by PESQ-WB scores, CVSS scores and the throughput. The experiment demonstrated the relationship among VoIP performance, VoIP security and VoIP service type. The experiment also suggested that, when compared to an unsecure IPIP tunnel, Internetworking Layer security like IPSec ESP or Transport Layer security like OpenVPN TLS would improve a VoIP security by reducing the vulnerabilities of the media part of the VoIP signal. Morever, adding a security layer has little impact on the VoIP voice quality.

9 pp. / As today's dairy industry consolidates, cows are being milked more rapidly through larger milking parlors on larger dairies than ever before. Because milk is the primary commodity and source of income for producers, the harvesting of milk is the single most important job on any dairy. Producing high-quality milk to maximize yields and economic value requires effective parlor management, an enormous challenge for producers. Managing large parlors includes managing labor, milking equipment, as well as monitoring and evaluating parlor performance. Decisions concerning the milking center are some of the most complicated decisions a dairy producer has to make. Milking procedures, herd size, milking interval, the milk market, and the equity position of a producer influence these decisions. Producers will have to make the following decisions before they can select or develop management protocols for a milking parlor: 1. How many cows will be milked through the parlor? 2. What milking procedure will be used (minimal or full)? 3. If a full milking routine; how much contact time do you want (strips per teat)? 4. Which milking routine will be used (sequential, grouping, or territorial)? 5. Are you willing to train teams of milkers to operate large parlors?

Breast cancers with overexpression or amplification of the HER2 tyrosine kinase receptor are more aggressive, resistant to chemotherapy, and associated with a worse prognosis. Currently, these breast cancers are treated with the monoclonal antibody trastuzumab (Herceptin®). Unfortunately, not all patients respond to trastuzumab drug therapy; some patients show de novo resistance, while others acquire resistance during treatment. This thesis describes our RNAi studies to identify novel regulators of the HER2 signaling pathway in breast cancer. Three kinome-wide siRNA screens were performed on five HER2 amplified and seven HER2 non-amplified breast cancer cell lines, two normal breast cell lines, as well as two HER2-positive breast cancer cell lines with acquired trastuzumab resistance and their isogenic trastuzumab-sensitive controls. To understand the main kinase drivers of HER2 signaling, we performed a comprehensive screen that selected against growth inhibitors of the non-HER2 amplified breast cancer cell lines. This screen identified the loss of the HER2/HER3 heterodimer as the most prominent selective inhibitor of HER2-amplified breast cancers. In a trastuzumab sensitization screen on five trastuzumab-treated breast cancer cell lines, we identified several siRNA against the PI3K pathway as well as various other signaling pathways that inhibited proliferation. Finally, in a screen for acquired trastuzumab resistance, PKCη and its downstream targets were identified. Loss of PKCη resulted in a decrease in G1/S transition and upregulation of the cyclin dependent kinase inhibitor p27. Initial data suggest that PKCη promotes p27 ubiquitination and degradation. Taken together, these studies provide novel insight into the complex signaling of HER2-positive breast cancers and the mechanisms of resistance to trastuzumab therapy. This work describes how various kinases can modulate cell proliferation, and points to possible novel drug targets for the treatment of HER2-positive breast cancers.

Glycosylation, the addition of one or more carbohydrates molecules to a protein, is crucial for many cellular processes. Aberrant glycosylation is a key marker for various diseases such as cancer and rheumatoid arthritis. It has also recently been discovered that glycosylation is important in the ability of the Human Immunodeficiency Virus (HIV) to evade recognition by the immune system. Given the importance of glycosylation in disease, major efforts are underway in life science research to investigate the glycome, the entire glycosylation profile of an organelle, cell or tissue type. To date, little bioinformatics research has been performed in glycomics due to the complexity of glycan structures and the low throughput of carbohydrate analysis. Recent advances in mass spectrometry (MS) have greatly facilitated the analysis of the glycome. Increasingly, this technology is preferred over traditional methods of carbohydrate analysis which are often laborious and unsuitable for low abundance glycoproteins. When subject to mass spectrometry with collision-induced dissociation, glycopeptides produce characteristic MS/MS spectra that can be detected by visual inspection. However, given the high volume of data output from proteome studies today, manually searching for glycopeptides is an impractical task. In this thesis, we present a tool to automate the identification of glycopeptide spectra from MS/MS data. Further, we discuss some methodologies to automate the elucidation of the structure of the carbohydrate moiety of glycopeptides by adapting traditional MS/MS ion searching techniques employed in peptide sequence determination. MS/MS ion searching, a common technique in proteomics, aims to interpret MS/MS spectra by correlating structures from a database to the patterns represented in the spectrum. The tool was tested on high throughput proteomics data and was shown to identify 97% of all glycopeptides present in the test data. Further, the tool assigned correct carbohydrate structures to many of these glycopeptide MS/MS spectra. Applications of the tool in a proteomics environment for the analysis of glycopeptide expression in cancer tissue are also be presented.

The term of Cognitive Radio (CR) used to indicate that spectrum radio could be accessed dynamically and opportunistically by unlicensed users. In CR Networks, Interference between nodes, hidden terminal problem, and spectrum sensing errors are big issues to be widely discussed in the research field nowadays. To improve the performance of such kind of networks, this thesis proposes Cognitive Medium Access Control (MAC) protocols for Mobile Ad-Hoc Networks (MANETs). From the concept of CR, this thesis has been able to develop a cognitive MAC framework in which a cognitive process consisting of cognitive elements is considered, which can make efficient decisions to optimise the CR network. In this context, three different scenarios to maximize the secondary user's throughput have been proposed. We found that the throughput improvement depends on the transition probabilities. However, considering the past information state of the spectrum can dramatically increases the secondary user's throughput by up to 40%. Moreover, by increasing the number of channels, the throughput of the network can be improved about 25%. Furthermore, to study the impact of Physical (PHY) Layer errors on cognitive MAC layer in MANETs, in this thesis, a Sensing Error-Aware MAC protocols for MANETs has been proposed. The developed model has been able to improve the MAC layer performance under the challenge of sensing errors. In this context, the proposed model examined two sensing error probabilities: the false alarm probability and the missed detection probability. The simulation results have shown that both probabilities could be adapted to maintain the false alarm probability at certain values to achieve good results. Finally, in this thesis, a cooperative sensing scheme with interference mitigation for Cognitive Wireless Mesh Networks (CogMesh) has been proposed. Moreover, a prioritybased traffic scenario to analyze the problem of packet delay and a novel technique for dynamic channel allocation in CogMesh is presented. Considering each channel in the system as a sub-server, the average delay of the users' packets is reduced and the cooperative sensing scenario dramatically increases the network throughput 50% more as the number of arrival rate is increased.