Chronic Healthcare Spending Disease: A Macro Diagnosis and Prognosis

The amount Canadians spend on healthcare is set to rise rapidly over the next two decades and Canadians need to face up to tough choices to deal with this “spending disease.” The study examines the trajectory of total healthcare spending – public and private – in Canada and the policy choices Canadians must make in response. The authors estimate the extent to which healthcare spending is going to absorb a greater fraction of income than Canadians have experienced to date under two scenarios: a baseline scenario drawn from historical experience, and an optimistic scenario, which assumes an unprecedented improvement in the efficiency and effectiveness of the healthcare system and large improvement in potential economic growth. Canadians must choose some combination of: 1) a sharp reduction in public services, other than health care; 2) increased taxes to finance the public share of healthcare spending; 3) increased individual spending on healthcare services currently insured by provinces, through some form of co-payment or through delisting of services that are currently publicly financed; 4) or a degradation of publicly insured healthcare standards – longer queues, and services of poorer quality.The Health Papers, healthcare spending, Canada

Growth Characteristics of Reef-Building Corals Within and External to a Naval Ordinance Range: Vieques, Puerto Rico

The skeletal growth of reef·building corals is known to be sensitive to the environment. In particular, high levels of sedimentation and turbidity lead to decreased growth rate, suppressed growth variation, and, ultimately, coral death because of reduced illumination necessary to zooxanthellae and/or increased energy expenditure by the coral animal to remove impacted sediments. To assess the effect of Naval Ordnance Range usage at Vieques, Puerto Rico, specimens of Montastrea annulariswere collected from reefs adjacent to and removed from the range area. Growth was measured from annual increments revealed by X-radiography of medial slabs of the coral skeletons. Mean growth rates and growth variances were calculated for each station or station grouping over the common time period 1970-1977. Statistical comparison of the growth data reveals a general similarity between range and control stations. This evidence coupled with quantitative coral abundance and diversity data of others indicate a lack of anomalous and adverse sedimentation/turbidity conditions affecting corals on reefs near the range area. Chronologies of coral band widths compared to historical recorded environmental data indicate that a major natural parameter which controls coral growth in Vieques is annual water temperature variation

What Does it Mean to Teach Interpretively?

The ‘interpretive turn’ has gained traction as a research approach in recent decades in the empirical social sciences. While the contributions of interpretive research and interpretive research methods are clear, we wonder: Does an interpretive perspective lend itself to – or even demand – a particular style of teaching? This question was at the heart of a roundtable discussion we organised at the 2014 Interpretive Policy Analysis (IPA) International Conference. This essay reports on the contours of the discussion, with a focus on our reflections upon what it might mean to teach ‘interpretively’. Prior to outlining these, we introduce the defining characteristics of an interpretive perspective and describe our respective experiences and interests in this conversation. In the hope that this essay might constitute the beginning of a wider conversation, we close it with an invitation for others to respond

Effects of Drilling Mud on the Reef-Building Coral Montastrea annularis

The skeletal extension and corallite shape of individuals of the Caribbean and Atlantic reef-building coral Montastrea annularis (Ellis and Solander) were measured after more than six weeks\u27 continuous flow-through exposure in laboratory aquaria to treatments of 0, 1, 10 and 100-ppm (μl 1-1) drilling mud. Linear increase of the skeleton (extension rate) and fossa length were significantly depressed in the 100-ppm treatment. Chronic exposure to 100-ppm drilling mud impairs coral skeletal growth rate and possibly interferes with sediment rejection capability by lowering calical relief

Coral populations and growth patterns: Responses to sedimentation and turbidity associated with dredging

Analysis of coral growth patterns and populations in Bermuda reveals that living coral abundance on the reefs of Castle Harbor, a location where extensive dredging occurred during 1941- 1943, is much reduced in comparison to external North-South reefs. Dead corals, sampled in the harbor, have skeletal patterns of growth which are similar and which show a marked decline in growth for several years prior to death...

Large-scale Data Analysis and Deep Learning Using Distributed Cyberinfrastructures and High Performance Computing

Data in many research fields continues to grow in both size and complexity. For instance, recent technological advances have caused an increased throughput in data in various biological-related endeavors, such as DNA sequencing, molecular simulations, and medical imaging. In addition, the variance in the types of data (textual, signal, image, etc.) adds an additional complexity in analyzing the data. As such, there is a need for uniquely developed applications that cater towards the type of data. Several considerations must be made when attempting to create a tool for a particular dataset. First, we must consider the type of algorithm required for analyzing the data. Next, since the size and complexity of the data imposes high computation and memory requirements, it is important to select a proper hardware environment on which to build the application. By carefully both developing the algorithm and selecting the hardware, we can provide an effective environment in which to analyze huge amounts of highly complex data in a large-scale manner. In this dissertation, I go into detail regarding my applications using big data and deep learning techniques to analyze complex and large data. I investigate how big data frameworks, such as Hadoop, can be applied to problems such as large-scale molecular dynamics simulations. Following this, many popular deep learning frameworks are evaluated and compared to find those that suit certain hardware setups and deep learning models. Then, we explore an application of deep learning to a biomedical problem, namely ADHD diagnosis from fMRI data. Lastly, I demonstrate a framework for real-time and fine-grained vehicle detection and classification. With each of these works in this dissertation, a unique large-scale analysis algorithm or deep learning model is implemented that caters towards the problem and leverages specialized computing resources

Characterization of superconducting hardware for implementing quantum stabilizers

Superconducting qubits are one of the leading approaches being investigated for building a scalable quantum computer. In the presence of external noise and perturbations plus local microscopic fluctuations and dissipation in the qubit environment, arbitrary quantum states will decohere, leading to bit-flip and phase-flip errors of the qubit. In order to build a fault-tolerant quantum computer that can preserve and process quantum information in the presence of noise and dissipation, one must implement some form of quantum error correction. Stabilizer operations are at the heart of quantum error correction and are typically implemented in software-controlled entangling gates and measurements of groups of qubits. Alternatively, qubits can be designed so that the Hamiltonian includes terms that correspond directly to a stabilizer for protecting quantum information. In this thesis, we demonstrate such a hardware implementation of stabilizers in a superconducting circuit composed of chains of $\pi$-periodic Josephson elements called a plaquette. Each plaquette consists of a superconducting loop with two conventional Josephson junctions and two inductors. We study the phase dependence of the plaquette by incorporating it into a resonant multi-loop circuit and measuring the resonator\u27s frequency as a function of the external magnetic flux through each loop. To demonstrate the implementation of stabilizers in the Hamiltonian we made a superconducting circuit composed of a chain of three plaquettes shunted by a large capacitor. We map out the multidimensional flux space of the device by using on-chip bias lines to tune the magnetic flux through the three plaquettes independently. We measure the flux and charge dependence of the device\u27s energy levels with microwave spectroscopy. We compare these measurements with numerical modeling of the energy level spectrum and obtain good agreement between theory and experiment for the designed and fabricated device parameters. We observe a softening of the energy band dispersion with respect to flux that is exponential in the number of frustrated plaquettes, this corresponds to the device being protected against errors caused by dephasing due to flux noise. The large shunt capacitor suppresses tunneling between the qubit logical states, and thus protects the device against bit-flip errors. A future qubit based on this design will exhibit simultaneous protection against bit-flip and phase-flip errors leading to gate errors that are significantly improved over the current state of the art

Annual Periodicity of the 18O16O and 13C12C ratios in the coral Montastrea annularis

The isotopic ratios 18O/16O and 13C/12C show an annual periodicity in the coral Montastrea annularis from Bermuda, Jamaica and Barbados. The abundances of 18O and 13C are positively correlated in the Jamaica and Barbados samples, but inversely related in the Bermuda sample. Annual high density growth bands are formed during the season of warmest water temperature at all 3 sites and are enriched in 16O. M. Annularis has a constant displacement from oxygen isotopic equilibrium and accurately records seasonal temperature variations via the temperature-dependent aragonite-water fractionation factor. Light intensity, through the activity of the coral\u27s endosymbiotic algae, regulates the depth-dependent and seasonal variations in the skeletal carbon isotopic composition