Contactless Charging Adapter

Currently, most cell phones utilize wired adapters to charge, which cause a minor hassle when one frequently needs to unplug and replug their device whenever they pick it up to use while it is charging. The charging adapter is a pad that phones can be placed on to wirelessly charge the device. The charging adapter consists of two components: the wireless charging platform to supply and transmit the power, and the wireless charging receiver for phones that do not already have an internal receiver included, specifically targeting newer generation iPhones that utilize a lightning port (i.e. iPhone 5, 6, 6s, 7, 7s). The wireless charging receiver connects to the smartphone through the charging port and rests between the back of the phone and its casing. The entire system fully charges the device to 100% battery capacity within three hours and automatically shuts off upon completion. A unique feature of the charger is that it operates regardless of the orientation of the phone on the pad (an LED indicator notifies the user that the device is charging). The size of the entire charging assembly does not exceed that of a small textbook, allowing ease of transportation and use on a table or surface with limited space. Additionally, the incorporation of an ellipsed surface at the top of the 3D-printed base centers the phone while charging and biases it towards the middle where optimum power transfer is achieved. Reverse engineering was done on market examples and designs were made to create a charging platform to supply power. Then a development kit was used to test methods of improving the performance

Topology of Reticulate Evolution

The standard representation of evolutionary relationships is a bifurcating tree. However, many types of genetic exchange, collectively referred to as reticulate evolution, involve processes that cannot be modeled as trees. Increasing genomic data has pointed to the prevalence of reticulate processes, particularly in microorganisms, and underscored the need for new approaches to capture and represent the scale and frequency of these events. This thesis contains results from applying new techniques from applied and computational topology, under the heading topological data analysis, to the problem of characterizing reticulate evolution in molecular sequence data. First, we develop approaches for analyzing sequence data using topology. We propose new topological constructions specific to molecular sequence data that generalize standard constructions such as Vietoris-Rips. We draw on previous work in phylogenetic networks and use homology to provide a quantitative measure of reticulate events. We develop methods for performing statistical inference using topological summary statistics. Next, we apply our approach to several types of molecular sequence data. First, we examine the mosaic genome structure in phages. We recover inconsistencies in existing morphology-based taxonomies, use a network approach to construct a genome-based representation of phage relationships, and identify conserved gene families within phage populations. Second, we study influenza, a common human pathogen. We capture widespread patterns of reassortment, including nonrandom cosegregation of segments and barriers to subtype mixing. In contrast to traditional influenza studies, which focus on the phylogenetic branching patterns of only the two surface-marker proteins, we use whole-genome data to represent influenza molecular relationships. Using this representation, we identify unexpected relationships between divergent influenza subtypes. Finally, we examine a set of pathogenic bacteria. We use two sources of data to measure rates of reticulation in both the core genome and the mobile genome across a range of species. Network approaches are used to represent the population of S. aureus and analyze the spread of antibiotic resistance genes. The presence of antibiotic resistance genes in the human microbiome is investigated

Integrated circuit-based electrochemical sensor for spatially resolved detection of redox-active metabolites in biofilms

Despite advances in monitoring spatiotemporal expression patterns of genes and proteins with fluorescent probes, direct detection of metabolites and small molecules remains challenging. A technique for spatially resolved detection of small molecules would benefit the study of redox-active metabolites that are produced by microbial biofilms and can affect their development. Here we present an integrated circuit-based electrochemical sensing platform featuring an array of working electrodes and parallel potentiostat channels. ‘Images’ over a 3.25 0.9 mm2 area can be captured with a diffusion-limited spatial resolution of 750 mm. We demonstrate that square wave voltammetry can be used to detect, identify and quantify (for concentrations as low as 2.6 mM) four distinct redox-active metabolites called phenazines. We characterize phenazine production in both wild-type and mutant Pseudomonas aeruginosa PA14 colony biofilms, and find correlations with fluorescent reporter imaging of phenazine biosynthetic gene expression

The impact of smoke exposure on the clinical phenotype of alpha-1 antitrypsin deficiency in Ireland: exploiting a national registry to understand a rare disease.

Individuals with Alpha-1 antitrypsin deficiency (AATD) have mutations in the SERPINA1 gene causing genetic susceptibility to early onset lung and liver disease that may result in premature death. Environmental interactions have a significant impact in determining the disease phenotype and outcome in AATD. The aim of this study was to assess the impact of smoke exposure on the clinical phenotype of AATD in Ireland. Clinical demographics and available thoracic computerised tomography (CT) imaging were detected from 139 PiZZ individuals identified from the Irish National AATD Registry. Clinical information was collected by questionnaire. Data was analysed to assess AATD disease severity and evaluate predictors of clinical phenotype. Questionnaires were collected from 107/139 (77%) and thoracic CT evaluation was available in 72/107 (67.2%). 74% of respondents had severe Chronic Obstructive Pulmonary Disease (COPD) (GOLD stage C or D). Cigarette smoking was the greatest predictor of impairment in FEV1 and DLCO (%predicted) and the extent of emphysema correlated most significantly with DLCO. Interestingly the rate of FEV1 decline was similar in ex-smokers when compared to never-smokers. Passive smoke exposure in childhood resulted in a greater total pack-year smoking history. Radiological evidence of bronchiectasis was a common finding and associated with increasing age. The Irish National AATD Registry facilitates clinical and basic science research of this condition in Ireland. This study illustrates the detrimental effect of smoke exposure on the clinical phenotype of AATD in Ireland and the benefit of immediate smoking cessation at any stage of lung disease

Low-Altitude UAV Imaging Accurately Quantifies Eelgrass Wasting Disease From Alaska to California

Declines in eelgrass, an important and widespread coastal habitat, are associated with wasting disease in recent outbreaks on the Pacific coast of North America. This study presents a novel method for mapping and predicting wasting disease using Unoccupied Aerial Vehicle (UAV) with low-altitude autonomous imaging of visible bands. We conducted UAV mapping and sampling in intertidal eelgrass beds across multiple sites in Alaska, British Columbia, and California. We designed and implemented a UAV low-altitude mapping protocol to detect disease prevalence and validated against in situ results. Our analysis revealed that green leaf area index derived from UAV imagery was a strong and significant (inverse) predictor of spatial distribution and severity of wasting disease measured on the ground, especially for regions with extensive disease infection. This study highlights a novel, efficient, and portable method to investigate seagrass disease at landscape scales across geographic regions and conditions