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Wireless technology is used daily across the globe. A very common wireless technology is Bluetooth. The Bluetooth technology exists everywhere, from cars to mobile phones and even kitchen appliances. Recently, Bluetooth Low Energy has added support for another physical layer, LE 2M PHY. This physical layer is supposed to be faster and more energy efficient than its predecessor, LE 1M PHY, with a decrease in range. Because of this new physical layer, Bluetooth Low Energy can now compete with Bluetooth Classic during data transmission, in both speed and energy efficiency. This thesis aims to find the breaking point where Bluetooth Low Energy becomes less energy efficient than Bluetooth Classic, in relation to bit rate speed and total amount of bytes sent. Before experiments were conducted, multiple iterations of an artifact had to be done to end up with an artifact that provides valid and reliable data. The experiments were then conducted by changing the bit rate speed and sending different amounts of bytes. The results from the experiments show that Bluetooth Classic is practically both faster and more energy efficient with its fastest modulation than Bluetooth Low Energy is with LE 2M PHY enabled, even though this should not be the case theoretically. Bluetooth Classic is overall more energy efficient than Bluetooth Low Energy and thus the conclusion of this study is that no breaking points between the two technologies exist.

This simulation study was carried out at a company in the automotive industry. In their factory, the company manufactures gearboxes, where the gearbox assembly is one step in the manufacturing process. In the main assembly line, many different gearbox variants are manufactured, each with its own cycle time in the different assembly stations. Due to this variation in cycle times the throughput in the main assembly line can fluctuate depending on which gearbox variants are produced. To maintain a desired throughput a tool for forecasting the throughput would be of great value to the company. Due to the large number of gearbox variants, the company also experiences difficulties understanding if there are stations in the assembly which are recurring bottlenecks. The purpose of this project is to create a tool that can forecast the daily throughput of the main assembly line and identify bottlenecks in the main assembly line. The purpose is also to investigate whether some stations often are bottleneck stations during a certain period. The model evaluation was based on validation of input-output-transformation. A bottleneck analysis based on the active times of the stations was carried out with the best-performing model. The best-performing model version resulted in 68 percent valid forecasts for the 57 historical production days. The forecasts were valid for all historical production days which were Mondays, Tuesdays, Wednesdays, and Thursdays. For Fridays and Sundays, 25 and 0 percent were valid, respectively. A bottleneck analysis was carried out for 37 historical production days where the result showed that, based on the share of active time, a single station was identified as the bottleneck station for all days. The difference between the bottleneck station’s share of active time and other stations’ share of active time was deemed small enough to be within the error margin. Additionally, the queues in the main assembly line indicated that the bottleneck was located within another group of stations. Due to the ambiguity of the results, the conclusion drawn was that the main assembly line did not experience any clear bottleneck station during the 37 historical production days. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

<p>The 20^th century introduction of antibiotics made once fatal infectious diseases readily treatable. This taken-for-granted therapy is now threatened by rising antibiotic resistance. The ability of pathogens to acquire numerous simultaneous resistance mechanisms has given rise to an alarming number of increasingly difficult to treat multi-drug resistant infections. When coupled with a sharp decline in development of novel antibiotic therapies, health practitioners today are left with limited therapeutic options. Several alternative methodologies have been employed to find novel therapeutics, including new techniques in natural product isolation and the production of semi-synthetic and synthetic antibiotics; however, there has been limited focus on targeting antibiotic resistance mechanisms directly to create synergistic therapies. We demonstrate the potential in using small molecules to target antibiotic kinases, thereby rescuing the antibiotic action of aminoglycosides and macrolides when used in combination. We conducted a thorough examination of these enzymes including: kinetic analysis; an assessment of phosphate donor specificity; and in-depth structural comparison, including a case study on the structure-function relationship of APH(4)-Ia. This analysis culminated in an intensive screening initiative of fourteen antibiotic kinases against a set of well defined protein kinase inhibitors. From this work, we have identified several inhibitors that have the potential for use in future combination therapeutics. This study illustrates the benefit of a structure-activity based approach to drug discovery, an important tool at a time when novel therapeutic strategies are required.</p> / Doctor of Philosophy (PhD)

<p>The current rise in multi-drug resistant Gram-negative bacterial infections is of particularconcern. Gram-negative pathogens are difficult to treat due to their intrinsic resistome.The outer membrane (OM) of Gram-negative bacteria serves as a permeability barrier tomany antibiotics, due in large part to the lipopolysaccharide (LPS) component that isunique to these organisms, and in addition to, the OM is lined with a number of multidrugresistant efflux pumps. As the clinical effectiveness of first line therapies declines inthe face of this resistance, novel strategies to discover new antibiotics are required. Theidentification of new antibiotic targets is one method currently being applied to meet thischallenge. This work examines the permeability barrier of Escherichia coli as a possibletarget for antibiotic adjuvants. A structure-function analysis of GmhA and GmhB, whichcatalyze the first and third conserved steps in LPS ADP-heptose biosynthesis, wasperformed. The active site residues of each of these enzymes were identified viacrystallographic, mutagenic, and kinetic analyses. Potential mechanisms have beenproposed, offering insight into the function of these potential adjuvant targets. In addition,a whole screen of E. coli was performed to identify compounds that potentiatenovobiocin, an antibiotic with limited activity against Gram-negative pathogens due toOM permeability. Four small molecules were found that were able to synergize withnovobiocin. One of these, A22, is known to alter bacterial cell shape, suggesting a newpathway for antibiotic adjuvants to combat Gram-negative infection. Together, thesestudies highlight the varied targets available for novel therapeutic strategies.</p> / Doctor of Philosophy (PhD)

<p>The human interactome presents a goldmine of potentially powerful therapeutic targets, yet very few small molecule modulators of protein-protein interactions (PPI) have been identified. PPI pose a particular challenge for drug discovery, and one of the major obstacles to fully exploiting these interactions is a lack of appropriate technologies to screen for modulating compounds. This thesis aims to address the need for function- based approaches that target PPI by using magnetic beads (MB) and mass spectrometry (MS) to develop efficient assays to monitor these interactions and their modulation by small molecules. The work begins with the validation of a novel magnetic “fishing” assay, which uses affinity-capture MB to isolate intact complexes of a “bait” protein from solution. By monitoring the recovery of the secondary binding partner, this assay was used to functionally screen a library of 1000 compounds for small molecule modulators of a calmodulin/melittin (CaM/Mel) model system. The versatility of magnetic “fishing” is clearly demonstrated during a study of a more relevant CaM-based system, which uncovered a novel mode of interaction for the CaM-binding domain of transcription factor SOX9. In addition to the MB-based approach, a simple MS-based competitive displacement assay is developed to identify minimal inhibitory fragments of a target complex as indicators of potential ‘hot-spots’. The assay was used to probe a DNA repair complex of XRCC4/ligaseIV, and identified a short helix that can be used as a more defined target surface for future high-throughput screening and rational drug design. The functional MS-based assays herein are highly adaptable tools to monitor PPI, and will facilitate the study of these and other important biomolecular interactions.</p> / Doctor of Philosophy (PhD)

<p>Mammoths (<em>Mammuthus</em>) have been studied extensively at the genetic level. However due to both taphonomic and technological limitations, only one of several late Pleistocene mammoth species, the woolly mammoth (<em>M. primigenius</em>), has been investigated. This limits our impression of mammoth population history to the the northern latitudes, just one of several environments in which mammoths lived and went extinct. It also obscures their evolutionary chronology, which prevents proper climatic and biogeographic contextualization of their history. Fortunately recent technological advances in high-throughput sequencing and targeted enrichment promise to expand Pleistocene faunal population phylogeography to non-permafrost, non-cave burial contexts. However the capacity and behavior of these combined technologies for characterizing ancient DNA is largely unexplored, preventing efficient and routine use for population-level studies. In this thesis I test and apply these technologies to remains of mammoth species from throughout North America. I first demonstrate their potential for poorly-preserved DNA, and then I evaluate their efficient application to large sample sets, as well as for capturing complete nuclear genomes. I then use these technologies to sequence dozens of mitochondrial genomes from Columbian (<em>M. columbi</em>)<em> </em>and other non-woolly mammoths, reconstructing their matrilineal phylogeography south of the ice. The revealed patterns not only imply a deep chronology for mammoth matrilineal diversity, but also that North American mammoth evolution was occurred via separate episodes of interbreeding between resident and invading populations, and between ecotypes. Overall the biological and methodological discoveries afforded by this body of work outline future research avenues on mammoth evolution, behavior, and extinction.</p> / Doctor of Philosophy (PhD)

<p>Research in this thesis has focused on development and application of novel methodologies that enhance sample throughput and data fidelity when performing untargeted metabolome profiling by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Metabolomics is a valuable tool in functional genomics research to investigate underlying molecular mechanisms associated with human health since metabolites are “real-world” end-products of gene expression. CE-MS is well-suited for metabolomics because it is a high efficiency microseparation technique that can be used to resolve complex mixtures of polar metabolites in human biofluids without complicated sample workup. In this thesis, a novel CE-MS assay for estrogens and their intact ionic conjugates has been described (<em>Chapter II</em>) to expand metabolome coverage that enables resolution of positional isomers with high selectivity. This is critical for better understanding of underlying perturbations in estrogen metabolism since the biological activity of estrogens are dependent on specific primary and secondary metabolic transformations. MSI-CE-MS has been introduced as a high-throughput approach for large-scale metabolomic studies based on serial injection of multiple segments of sample within a single fused-silica capillary (<em>Chapter III</em>). It reduces analysis times while increasing data quality and confidence in peak assignment together with better quality assurance. An accelerated workflow for metabolomics has also been developed when using MSI-CE-MS, where a dilution trend filter is used as a primary screen to authenticate reproducible sample-derived metabolites from a pooled sample while eliminating spurious artifact and background signals. In this way, complicated time alignment and peak picking algorithms are avoided when processing data in metabolomics to reduce false discoveries. This strategy was subsequently used in two metabolomics applications (<em>Chapters IV</em> and <em>V</em>) to identify plasma markers associated with strenuous exercise and adaptive training responses following a six-week high intensity interval training. The impact of exercise intervention to improve the glucose tolerance of a cohort of overweight/obese yet non-diabetic women was investigated on an individual level when using a cross-over design. Personalized interventions are critical in designing more effective therapies to prevent metabolic diseases due to inter-subject variations in treatment responses, including potential adverse effects. MSI-CE-MS offers a revolutionary approach for biomarker discovery in metabolomics with high sample throughput and high data fidelity, which is critical for validation of safe yet effective lifestyle interventions that promote human health and reduce risk for chronic diseases.</p> / Doctor of Philosophy (PhD)

Silicones are widely used polymeric materials due to their unique properties. The material properties of silicones may be altered by incorporating various organic groups. Traditional methods for linear silicone synthesis involve ring-opening polymerization, which leaves the growing chain susceptible to acid or base mediated chain redistribution and the formation of cyclic monomer byproducts. The Piers-Rubinsztajn (PR) reaction is an alternative siloxane synthetic route that avoids the use of tin- or platinum- based, or of Brønsted acid/base catalysts. Siloxane bond formation is catalyzed by tris(pentafluorophenyl)borane (B(C6F5)3) (R’3Si-H + RO-SiR”3 → R’3Si-O-SiR”3 + RH); alkoxysilanes can be replaced with silanols or alkoxybenzenes. The catalytic activity of B(C6F5)3 was shown to be hindered by trace water in solution; water acts as a Lewis base coordinating to B(C6F5)3. Since the hydrate-free form of B(C6F5)3 is required to initiate a PR reaction, water can act as an inhibitor. In a somewhat contradictory fashion, water was also shown to react with hydrosilanes via a B(C6F5)3 catalyzed hydrolysis reaction to give silanols, that themselves are reagents for the process. The reactivity of alkoxysilanes (or aryl ethers) in the PR reaction was found to be much quicker than water. This was exploited in the synthesis of Ax(AB)yAx triblock copolymers. The aryl rich AB core was first synthesized using the PR reaction. Excess silicone condensed via hydrolysis forming the A blocks. This method of exploiting relative reactivity to tune structure was applied to elastomers made using a single linker (eugenol) with multiple functional groups – elastomer morphology was controlled by changing order of addition. The development of aryl dense silicones is of interest for use in electronic devices. Phenylmethyl homopolymers and highly ordered phenyl pendant copolymers (Ph/Si ratio of 0.5-1.5) were synthesized from monomers to give polymers with high refractive indices (1.51-1.59) and Mw up to 170 kDa. Statistically relevant libraries of aryl functional silicones were developed using combinatorial chemistry in order to analyze their structure-property relationship. Incorporating aromatic groups into silicones worked to elevate thermal stability, refractive index and improve the mechanical strength of silicone rubbers. / Thesis / Doctor of Science (PhD) / Silicone fluids and elastomers possess numerous desirable characteristics which leads to their use in a wide range of applications in the automotive, electronics and biomedical fields, among others. Developing techniques to create well defined, ordered, modified silicones with improved optical properties, mechanical strength and thermal stability was the main focus of this thesis. These objectives were accomplished by incorporating aromatic groups into silicones using boron catalysis. Following the initial (intended) Piers-Rubinsztajn reaction, atmospheric moisture was utilized to promote further polymerization. Statistically relevant libraries of silicone elastomers were prepared using both standard and combinatorial chemistry techniques. This library of elastomers permitted the analysis of trends associated with small changes in elastomer formulation, which could not be accomplished using traditional one-by-one reaction methods in a timely fashion. The modified silicone materials exhibited high refractive indices (up to 1.59), elevated stiffness and improved thermal stability (maintain structure up to 500 °C) when compared to previously synthesized polymers.