A major driving force for development of new catalyst systems is the need for more efficient synthesis of chemical compounds essential to modern life. Catalysts having superior performance offer significant environmental and economic advantages, but their discovery is not trivial. Well-defined, homogeneous catalysts can offer unparalleled understanding of ligand effects, which proves invaluable in directing redesign strategies. This thesis work focuses on the design of ruthenium complexes for applications in dinitrogen activation and olefin metathesis. The complexes developed create new directions in small-molecule activation and asymmetric catalysis by late-metal complexes. Also examined are the dual challenges, ubiquitous in catalysis, of adequate interrogation of catalyst structure and performance. Insight into both is essential to enable correlation of ligand properties with catalyst activity and/or selectivity. Improved methods for accelerated assessment of catalyst performance are described, which expand high-throughput catalyst screening to encompass parallel acquisition of kinetic data. A final aspect focuses on direct examination of metal complexes, both as isolated species, and under catalytic conditions. Applications of charge-transfer MALDI mass spectrometry to structural elucidation in organometallic chemistry is described, and the technique is employed to gain insight into catalyst decomposition pathways under operating conditions.

Wireless Networks have been the topic of fundamental research in recent years with the aim of achieving reliable and efficient communications. However, due to their complexity, there are still many aspects of such configurations that remain as open problems. The focus of this thesis is to investigate some throughput limits of wireless networks. The network under consideration consists of $n$ source-destination pairs (links) operating in a single-hop fashion. In Chapters 2 and 3, it is assumed that each link can be active and transmit with a constant power P or remain silent. Also, fading is assumed to be the dominant factor affecting the strength of the channels between transmitter and receiver terminals. The objective is to choose a set of active links such that the throughput is maximized, where the rate of active links are either unconstrained or constrained. For the unconstrained throughput maximization, by deriving an upper bound and a lower bound, it is shown that in the case of Rayleigh fading: (i) the maximum throughput scales like $\log n$, (ii) the maximum throughput is achievable in a distributed fashion. The upper bound is obtained using probabilistic methods, where the key point is to upper bound the throughput of any random set of active links by a chi-squared random variable. To obtain the lower bound, a threshold-based link activation strategy (TBLAS) is proposed and analyzed. The achieved throughput of TBLAS is by a factor of four larger than what was obtained in previous works with centralized methods and with multihop communications. When the active links are constrained to transmit with a constant rate $\lambda$, an upper bound is derived that shows the number of active links scales at most like $\frac{1}{\lambda} \log n$. It is proved that TBLAS \emph{asymptotically almost surely(a.a.s.)} yields a feasible solution for the constrained throughput maximization problem. This solution, which is suboptimal in general, performs close to the upper bound for small values of $\lambda$. To improve the suboptimal solution, a double-threshold-based link activation strategy (DTBLAS) is proposed and analyzed based on some results from random graph theory. It is demonstrated that DTBLAS performs very close to the optimum. Specifically, DTBLAS is a.a.s. optimum when $\lambda$ approaches $\infty$ or $0$. The optimality results are obtained in an interference-limited regime. However, it is shown that, by proper selection of the algorithm parameters, DTBLAS also allows the network to operate in a noise-limited regime in which the transmission rates can be adjusted by the transmission powers. The price for this flexibility is a decrease in the throughput scaling law by a factor of $\log \log n$. In Chapter 4, the problem of throughput maximization by means of power allocation is considered. It is demonstrated that under individual power constraints, in the optimum solution, the power of at least one link should take its maximum value. Then, for the special case of $n=2$ links, it is shown that the optimum power allocation strategy for throughput maximization is such that either both links use their maximum power or one of them uses its maximum power and the other keeps silent.

The focus of this thesis work is to evaluate the RSS (Received Signal Strength) Performance of the University of Gävle (HiG) based on IEEE 802.11 standards both indoor and outdoor. Authors investigated the issues of deploying access points for wireless local area networks in the library-2nd floor, building 99-4th floor and outdoor university campus. By using the program VisiWave Site Survey, Global Position System (GPS) and RSS sensor to analysis the received signal strength, throughput and radio map. The influence of the building material and distance for the signal strength and the throughput are done by investigating indoor environment. The results of investigation suggest that most parts of library-2nd floor and building 99-4th floor possess at least a good RSS performance. However, minority parts of these places have a poor RSS performance, and the new resolution of Access Points’ (AP) deployment for these poor-RSS-performance parts is provided. For the outdoor campus part, the RSS in the area which near the walls of building is satisfactory (Received Signal Strength Indication (RSSI) between -79.8 dBm and -57 dBm), however in the centre of outdoor campus the RSS is poor. Thus, the evaluation of APs deployment in HiG is achieved.

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.

Wireless Networks have been the topic of fundamental research in recent years with the aim of achieving reliable and efficient communications. However, due to their complexity, there are still many aspects of such configurations that remain as open problems. The focus of this thesis is to investigate some throughput limits of wireless networks. The network under consideration consists of $n$ source-destination pairs (links) operating in a single-hop fashion. In Chapters 2 and 3, it is assumed that each link can be active and transmit with a constant power P or remain silent. Also, fading is assumed to be the dominant factor affecting the strength of the channels between transmitter and receiver terminals. The objective is to choose a set of active links such that the throughput is maximized, where the rate of active links are either unconstrained or constrained. For the unconstrained throughput maximization, by deriving an upper bound and a lower bound, it is shown that in the case of Rayleigh fading: (i) the maximum throughput scales like $\log n$, (ii) the maximum throughput is achievable in a distributed fashion. The upper bound is obtained using probabilistic methods, where the key point is to upper bound the throughput of any random set of active links by a chi-squared random variable. To obtain the lower bound, a threshold-based link activation strategy (TBLAS) is proposed and analyzed. The achieved throughput of TBLAS is by a factor of four larger than what was obtained in previous works with centralized methods and with multihop communications. When the active links are constrained to transmit with a constant rate $\lambda$, an upper bound is derived that shows the number of active links scales at most like $\frac{1}{\lambda} \log n$. It is proved that TBLAS \emph{asymptotically almost surely(a.a.s.)} yields a feasible solution for the constrained throughput maximization problem. This solution, which is suboptimal in general, performs close to the upper bound for small values of $\lambda$. To improve the suboptimal solution, a double-threshold-based link activation strategy (DTBLAS) is proposed and analyzed based on some results from random graph theory. It is demonstrated that DTBLAS performs very close to the optimum. Specifically, DTBLAS is a.a.s. optimum when $\lambda$ approaches $\infty$ or $0$. The optimality results are obtained in an interference-limited regime. However, it is shown that, by proper selection of the algorithm parameters, DTBLAS also allows the network to operate in a noise-limited regime in which the transmission rates can be adjusted by the transmission powers. The price for this flexibility is a decrease in the throughput scaling law by a factor of $\log \log n$. In Chapter 4, the problem of throughput maximization by means of power allocation is considered. It is demonstrated that under individual power constraints, in the optimum solution, the power of at least one link should take its maximum value. Then, for the special case of $n=2$ links, it is shown that the optimum power allocation strategy for throughput maximization is such that either both links use their maximum power or one of them uses its maximum power and the other keeps silent.

This research investigates cross-layer design in multi-hop wireless networks with random access. Due to the complexity of the problem, we study cross-layer design with a simple slotted ALOHA medium access control (MAC) protocol without considering any network dynamics. Firstly, we study the optimal joint configuration of routing and MAC parameters in slotted ALOHA based wireless networks under a signal to interference plus noise ratio based physical interference model. We formulate a joint routing and MAC (JRM) optimization problem under a saturation assumption to determine the optimal max-min throughput of the flows and the optimal configuration of routing and MAC parameters. The JRM optimization problem is a complex non-convex problem. We solve it by an iterated optimal search (IOS) technique and validate our model via simulation. Via numerical and simulation results, we show that JRM design provides a significant throughput gain over a default configuration in a slotted ALOHA based wireless network. Next, we study the optimal joint configuration of routing, MAC, and network coding in wireless mesh networks using an XOR-like network coding without opportunistic listening. We reformulate the JRM optimization problem to include the simple network coding and obtain a more complex non-convex problem. Similar to the JRM problem, we solve it by the IOS technique and validate our model via simulation. Numerical and simulation results for different networks illustrate that (i) the jointly optimized configuration provides a remarkable throughput gain with respect to a default configuration in a slotted ALOHA system with network coding and (ii) the throughput gain obtained by the simple network coding is significant, especially at low transmission power, i.e., the gain obtained by jointly optimizing routing, MAC, and network coding is significant even when compared to an optimized network without network coding. We then show that, in a mesh network, a significant fraction of the throughput gain for network coding can be obtained by limiting network coding to nodes directly adjacent to the gateway. Next, we propose simple heuristics to configure slotted ALOHA based wireless networks without and with network coding. These heuristics are extensively evaluated via simulation and found to be very efficient. We also formulate problems to jointly configure not only the routing and MAC parameters but also the transmission rate parameters in multi-rate slotted ALOHA systems without and with network coding. We compare the performance of multi-rate and single rate systems via numerical results. We model the energy consumption in terms of slotted ALOHA system parameters. We found out that the energy consumption for various cross-layer systems, i.e., single rate and multi-rate slotted ALOHA systems without and with network coding, are very close.

In order to meet the increasing demand for higher data rates, next generation wireless networks must incorporate additional functionalities to enhance network throughput. Multihop networks are considered as a promising alternative due to their ability to exploit spatial reuse and to extend coverage. Recently, industry has shown increased interest in multihop networks as they do not require additional infrastructure and have relatively low deployment costs. Many advances in physical and network layer techniques have been proposed in the recent past and they have been studied mostly in single-hop networks. Very few studies, if any, have tried to quantify the gains that these techniques could provide in multihop networks. We investigate the impact of simple network coding, advanced physical layer and cooperative techniques on the maximum achievable throughput of wireless multihop networks of practical size. We consider the following advanced physical layer techniques: successive interference cancellation, superposition coding, dirty-paper coding, and some of their combinations. We achieve this by formulating several cross-layer frameworks when these techniques are jointly optimized with routing and scheduling. We also formulate power allocation subproblems for the cases of continuous power control and superposition coding. We also provide numerous engineering insights by solving these problems to optimality.

The initial research of this thesis involves the evaluation of different strategies for developing diverse chemistries of highly stable coatings for the automated 96-blade (thin-film) solid phase microextraction (SPME) system. Thin-film geometry increases the volume of extractive phase, and consequently improves the sensitivity of the analysis. Sol-gel technology was used for the preparation of octadecyl (C18)-silica gel thin-film coating. The evaluation of the C18-silica gel SPME extractive phase resulted in stable physical and chemical characteristics and long-term reusability with a high degree of reproducibility. Biocompatible polyacrylonitrile (PAN) polymer was used for the preparation of particle-based extractive phases in order to improve the biocompatible characteristics of SPME coatings for the extraction from biological samples. Three different immobilization strategies were evaluated for developing highly stable coatings for the automated 96-blade SPME system. The spraying was found to be the optimal method in terms of stability and reusability for long-term use. The optimized C18-PAN coating demonstrated improved biocompatibility, stability, and reusability for the extraction of benzodiazepines from human plasma in comparison with those of C18-silica gel coating. To improve the biocompatible properties of the C18-PAN SPME coating for long-term direct analysis from whole blood, different modification strategies were studied and evaluated. The modification of the coating with an extra layer of biocompatible polyacrylonitrile resulted in significant improvement in the blood compatibility in long-term use. ‘Extracted blood spot’ (EBS) sampling was introduced as a novel approach to overcome the limitations of dried blood spot sampling. EBS includes the application of a biocompatible SPME coating for spot sampling of blood or other biofluids. The compatibility of EBS sampling with different analytical methods was demonstrated. The utilization of EBS as a fast sampling and sample preparation method resulted in a significant reduction of matrix effects through efficient sample clean-up. Modified polystyrene-divinylbenzene (PS-DVB)-PAN and phenylboronic acid (PBA)-PAN 96-blade SPME coatings were developed and evaluated for the extraction of analytes in a wide range of polarity. These coatings demonstrated efficient extraction recovery for both polar and non-polar groups of compounds, and presented chemical and mechanical stabilities and reproducible extraction efficiencies for more than 100 usages in biological sample.

Code-Division Multiple-Access (CDMA) is one of the leading digital wireless communication methods currently employed throughout the world. Third generation (3G) and future wireless CDMA systems are required to provide services to a large number of users where each user sends data burst only occasionally. The preferred approach is packet based CDMA so that many users share the same physical channel simultaneously. In CDMA, each user is assigned a pseudo-random (PN) code sequence. PN codephase synchronization between received signals and a locally generated replica by the receiver is one of the fundamental requirements for successful implementation of any CDMA technique. The customary approach is to start each CDMA packet with a synchronization preamble which consists of PN code without data modulation. Packets with preambles impose overheads for communications in CDMA systems especially for short packets such as mouse-clicks or ATM packets of a few hundred bits. Thus, it becomes desirable to perform PN codephase synchronization using the information-bearing signal without a preamble. This work uses a segmented matched filter (SMF) which is capable of acquiring PN codephase in the presence of data modulation. Hence the preamble can be eliminated, reducing the system overhead. Filter segmentation is also shown to increase the tolerance to Doppler shift and local carrier frequency offset. <p>Computer simulations in MATLAB® were carried out to determine various performance measures of the acquisition system. Substantial improvement in probability of correct codephase detection in the presence of multiple-access interference and data modulation is obtained by accumulating matched filter samples over several code cycles prior to making the codephase decision. Correct detection probabilities exceeding 99% are indicated from simulations with 25 co-users and 10 kHz carrier frequency offset or Doppler shift by accumulating five or more PN code cycles, using maximum selection detection criterion. Analysis and simulation also shows that cyclic accumulation can improve packet throughput by 50% and by as much as 100% under conditions of high offered traffic and Doppler shift for both fixed capacity and infinite capacity systems.

A stochastic processing network is a system that takes materials of various kinds as inputs, and uses processing resources to produce other materials as outputs. Such a network provides a powerful abstraction of a wide range of real world, complex systems, including semiconductor wafer fabrication facilities, networks of data switches, and large-scale call centers. Key performance measures of a stochastic processing network include throughput, cycle time, and holding cost. The network performance can dramatically be affected by the choice of operational policies. We propose a family of operational policies called maximum pressure policies. The maximum pressure policies are attractive in that their implementation uses minimal state information of the network. The deployment of a resource (server) is decided based on the queue lengths in its serviceable buffers and the queue lengths in their immediate downstream buffers. In particular, the decision does not use arrival rate information that is often difficult or impossible to estimate reliably. We prove that a maximum pressure policy can maximize throughput for a general class of stochastic processing networks. We also establish an asymptotic optimality of maximum pressure policies for stochastic processing networks with a unique bottleneck. The optimality is in terms of minimizing workload process. A key step in the proof of the asymptotic optimality is to show that the network processes under maximum pressure policies exhibit a state space collapse.