A model for an aquatic ecosystem

An ecosystem made of nutrients, plants, detritus and dissolved oxygen is presented. Its equilibria are established. Sufficient conditions for the existence of the coexistence equilibrium are derived and its feasibility is discussed in every detail

Characterization of Lipid Deposition on Contact Lenses

The purpose of this thesis was to evaluate the influence of lipid deposition on silicone hydrogel contact lens materials and to construct an in vitro platform to further explore the effect of lipid interaction with contact lenses under physiologically relevant conditions. In Chapter 3, the location of fluorescently tagged cholesteryl ester deposition was evaluated on four silicone hydrogel lens materials after simulated contact lens wear with a vial model for 1 day, 14 days and 30 days, using a CLSM technique. In Chapter 4, the design and implementation of a blink mechanism on an in vitro eye model was outlined. In Chapter 5, the design and implementation of a tear film onto an in vitro eye model was outlined. In Chapter 6, the non-invasive tear film break-up time of two silicone hydrogels were evaluated after simulated contact lens wear with an in vitro eye model. In Chapter 7, the limitations and future directions of the in vitro eye model was outlined. Overall, the amount of accumulated cholesteryl ester in silicone hydrogels increased with prolonged incubation periods. The level of surface versus bulk cholesteryl ester deposition varied with lens material depending upon their surface and bulk properties. A blink mechanism and tear film structure were established on the in vitro eye model, allowing physiological simulations of tear volume, tear flow, intermittent air exposure, and mechanical wear. Non-invasive tear break-up time of the pre-lens tear film on silicone hydrogels was successfully measured for lotrafilcon B, which presented values that were comparable to clinical tear break-up times. This thesis reported a complex relationship between lipid deposition on silicone hydrogels and detailed the developments of a physiologically relevant in vitro eye model to move towards a better understanding of the effect of lipid deposition on contact lens discomfort

Measuring the relative performance of ETFs

1 online resource (iv, 28 p.) : ill.Includes abstract.Includes bibliographical references (p. 26-28).This paper measures the relative performance of ETFs in the US market. The historical data on four ETFs and four Mutual Funds are collected through 2011 to 2013. To examine the relative performance of ETFs compared to the Mutual Funds, this paper employs the methodology of Jensen’s Alpha and Tracking Error. According to the regression, Jensen’s Alphas of the ETFs and Mutual Funds are very close, while the Tracking Error of the ETFs is larger than that of the Mutual Funds. The results of the empirical study show that ETFs do not outperform the Mutual Funds. However, ETFs have several advantages over the Mutual Funds, such as on the aspect of management cost

Magnetic fields of our Galaxy on large and small scales

Magnetic fields have been observed on all scales in our Galaxy, from AU to kpc. With pulsar dispersion measures and rotation measures, we can directly measure the magnetic fields in a very large region of the Galactic disk. The results show that the large-scale magnetic fields are aligned with the spiral arms but reverse their directions many times from the inner-most arm (Norma) to the outer arm (Perseus). The Zeeman splitting measurements of masers in HII regions or star-formation regions not only show the structured fields inside clouds, but also have a clear pattern in the global Galactic distribution of all measured clouds which indicates the possible connection of the large-scale and small-scale magnetic fields.Comment: 9 pages. Invited Talk at IAU Symp.242, 'Astrophysical Masers and their Environments', Proceedings edited by J. M. Chapman & W. A. Baa

Magnetic structure of our Galaxy: A review of observations

The magnetic structure in the Galactic disk, the Galactic center and the Galactic halo can be delineated more clearly than ever before. In the Galactic disk, the magnetic structure has been revealed by starlight polarization within 2 or 3 kpc of the Solar vicinity, by the distribution of the Zeeman splitting of OH masers in two or three nearby spiral arms, and by pulsar dispersion measures and rotation measures in nearly half of the disk. The polarized thermal dust emission of clouds at infrared, mm and submm wavelengths and the diffuse synchrotron emission are also related to the large-scale magnetic field in the disk. The rotation measures of extragalactic radio sources at low Galactic latitudes can be modeled by electron distributions and large-scale magnetic fields. The statistical properties of the magnetized interstellar medium at various scales have been studied using rotation measure data and polarization data. In the Galactic center, the non-thermal filaments indicate poloidal fields. There is no consensus on the field strength, maybe mG, maybe tens of uG. The polarized dust emission and much enhanced rotation measures of background radio sources are probably related to toroidal fields. In the Galactic halo, the antisymmetric RM sky reveals large-scale toroidal fields with reversed directions above and below the Galactic plane. Magnetic fields from all parts of our Galaxy are connected to form a global field structure. More observations are needed to explore the untouched regions and delineate how fields in different parts are connected.Comment: 10+1 pages. Invited Review for IAU Symp.259: Cosmic Magnetic Fields: From Planets, to Stars and Galaxies (Tenerife, Spain. Nov.3-7, 2009). K.G. Strassmeier, A.G. Kosovichev & J.E. Beckman (eds.

Topology-aware Debiased Self-supervised Graph Learning for Recommendation

In recommendation, graph-based Collaborative Filtering (CF) methods mitigate the data sparsity by introducing Graph Contrastive Learning (GCL). However, the random negative sampling strategy in these GCL-based CF models neglects the semantic structure of users (items), which not only introduces false negatives (negatives that are similar to anchor user (item)) but also ignores the potential positive samples. To tackle the above issues, we propose Topology-aware Debiased Self-supervised Graph Learning (TDSGL) for recommendation, which constructs contrastive pairs according to the semantic similarity between users (items). Specifically, since the original user-item interaction data commendably reflects the purchasing intent of users and certain characteristics of items, we calculate the semantic similarity between users (items) on interaction data. Then, given a user (item), we construct its negative pairs by selecting users (items) which embed different semantic structures to ensure the semantic difference between the given user (item) and its negatives. Moreover, for a user (item), we design a feature extraction module that converts other semantically similar users (items) into an auxiliary positive sample to acquire a more informative representation. Experimental results show that the proposed model outperforms the state-of-the-art models significantly on three public datasets. Our model implementation codes are available at https://github.com/malajikuai/TDSGL.Comment: 6 pages,8 figure