Nanotechnology for Early Cancer Detection

Vast numbers of studies and developments in the nanotechnology area have been conducted and many nanomaterials have been utilized to detect cancers at early stages. Nanomaterials have unique physical, optical and electrical properties that have proven to be very useful in sensing. Quantum dots, gold nanoparticles, magnetic nanoparticles, carbon nanotubes, gold nanowires and many other materials have been developed over the years, alongside the discovery of a wide range of biomarkers to lower the detection limit of cancer biomarkers. Proteins, antibody fragments, DNA fragments, and RNA fragments are the base of cancer biomarkers and have been used as targets in cancer detection and monitoring. It is highly anticipated that in the near future, we might be able to detect cancer at a very early stage, providing a much higher chance of treatment

The Magnitudes of Economic and Non-Economic Factors on the Demand for U.S. Domestic Air Travel

The primary purpose of this study is to analyze air carriers’ behavior in capturing market share by examining the economic factors affecting passenger behavior toward air travel. This study also examines non-economic factors such as seasonality, unexpected events (9/11 attack), mergers, and trends. Because the airlines included in this study compete with each other, seemingly unrelated regression estimation (SURE) is used to estimate the parameters of the demand models which have correlated error terms. The economic and statistical relationship of the factors with air passenger miles provides valuable information to understand the nature of the demand for the U.S. air passenger industry. In examining demand determinants, this study concludes that air fare, income, seasonality, and mergers play significant roles in determining the demand for air passengers

Who Are Fashion Brand Fans? An Investigation of Antecedents and Outcomes of Brand Commitment

Strong emotional bonds between consumers and brands lead consumers to be involved, committed, and dedicated to brands (Fournier, 1998). These involved and committed consumers exhibit an intense level of loyalty behavior that remains regardless of the brand’s performance and/or situational influences (Oliver, 1999). Thus, manufacturers and retailers that provide consumers with self-reflective branded products (e.g., apparel, accessories) that enable consumers to develop affective bonds may garner more emotional loyalty than retailers and manufacturers that provide branded commodities (e.g., gasoline, bleach)

Elevated intracellular cAMP exacerbates vulnerability to oxidative stress in optic nerve head astrocytes.

Glaucoma is characterized by a progressive loss of retinal ganglion cells and their axons, but the underlying biological basis for the accompanying neurodegeneration is not known. Accumulating evidence indicates that structural and functional abnormalities of astrocytes within the optic nerve head (ONH) have a role. However, whether the activation of cyclic adenosine 3',5'-monophosphate (cAMP) signaling pathway is associated with astrocyte dysfunction in the ONH remains unknown. We report here that the cAMP/protein kinase A (PKA) pathway is critical to ONH astrocyte dysfunction, leading to caspase-3 activation and cell death via the AKT/Bim/Bax signaling pathway. Furthermore, elevated intracellular cAMP exacerbates vulnerability to oxidative stress in ONH astrocytes, and this may contribute to axonal damage in glaucomatous neurodegeneration. Inhibition of intracellular cAMP/PKA signaling activation protects ONH astrocytes by increasing AKT phosphorylation against oxidative stress. These results strongly indicate that activation of cAMP/PKA pathway has an important role in astrocyte dysfunction, and suggest that modulating cAMP/PKA pathway has therapeutic potential for glaucomatous ONH degeneration

Entropic measure of directional emissions in microcavity lasers

We propose a noble notion of the directional emission in microcavity lasers. First, Shannon entropy of the far-field profiles in the polar coordinate can quantify the degree of unidirectionality of the emission, while previous notions about the unidirectionality can not efficiently measure in the robust range against a variation of the deformation parameter. Second, a divergence angle of the directional emission is defined phenomenologically in terms of full width at half maximum, and it is barely applicable to a complicated peak structure. However, Shannon entropy of semi-marginal probability of the far-field profiles in the cartesian coordinate can present equivalent results, and moreover it is applicable to even the cases with a complicated peak structure of the emission

A stochastic mixed integer programming approach to wildfire management systems

Wildfires have become more destructive and are seriously threatening societies and our ecosystems throughout the world. Once a wildfire escapes from its initial suppression attack, it can easily develop into a destructive huge fire that can result in significant loss of lives and resources. Some human-caused wildfires may be prevented; however, most nature-caused wildfires cannot. Consequently, wildfire suppression and contain- ment becomes fundamentally important; but suppressing and containing wildfires is costly. Since the budget and resources for wildfire management are constrained in reality, it is imperative to make important decisions such that the total cost and damage associated with the wildfire is minimized while wildfire containment effectiveness is maximized. To achieve this objective, wildfire attack-bases should be optimally located such that any wildfire is suppressed within the effective attack range from some bases. In addition, the optimal fire-fighting resources should be deployed to the wildfire location such that it is efficiently suppressed from an economic perspective. The two main uncertain/stochastic factors in wildfire management problems are fire occurrence frequency and fire growth characteristics. In this thesis two models for wildfire management planning are proposed. The first model is a strategic model for the optimal location of wildfire-attack bases under uncertainty in fire occurrence. The second model is a tactical model for the optimal deployment of fire-fighting resources under uncertainty in fire growth. A stochastic mixed-integer programming approach is proposed in order to take into account the uncertainty in the problem data and to allow for robust wildfire management decisions under uncertainty. For computational results, the tactical decision model is numerically experimented by two different approaches to provide the more efficient method for solving the model