Development of physical and mathematical models for the Porous Ceramic Tube Plant Nutrification System (PCTPNS)

A physical model of the Porous Ceramic Tube Plant Nutrification System (PCTPNS) was developed through microscopic observations of the tube surface under various operational conditions. In addition, a mathematical model of this system was developed which incorporated the effects of the applied suction pressure, surface tension, and gravitational forces as well as the porosity and physical dimensions of the tubes. The flow of liquid through the PCTPNS was thus characterized for non-biological situations. One of the key factors in the verification of these models is the accurate and rapid measurement of the 'wetness' or holding capacity of the ceramic tubes. This study evaluated a thermistor based moisture sensor device and recommendations for future research on alternative sensing devices are proposed. In addition, extensions of the physical and mathematical models to include the effects of plant physiology and growth are also discussed for future research

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

Real-time information processing of environmental sensor network data using Bayesian Gaussian processes

In this article, we consider the problem faced by a sensor network operator who must infer, in real time, the value of some environmental parameter that is being monitored at discrete points in space and time by a sensor network. We describe a powerful and generic approach built upon an efficient multi-output Gaussian process that facilitates this information acquisition and processing. Our algorithm allows effective inference even with minimal domain knowledge, and we further introduce a formulation of Bayesian Monte Carlo to permit the principled management of the hyperparameters introduced by our flexible models. We demonstrate how our methods can be applied in cases where the data is delayed, intermittently missing, censored, and/or correlated. We validate our approach using data collected from three networks of weather sensors and show that it yields better inference performance than both conventional independent Gaussian processes and the Kalman filter. Finally, we show that our formalism efficiently reuses previous computations by following an online update procedure as new data sequentially arrives, and that this results in a four-fold increase in computational speed in the largest cases considered

Resistive MHD reconstruction of two-dimensional coherent structures in space

We present a reconstruction technique to solve the steady resistive MHD equations in two dimensions with initial inputs of field and plasma data from a single space- craft as it passes through a coherent structure in space. At least two components of directly measured electric fields (the spacecraft spin-plane components) are required for the reconstruction, to produce two-dimensional (2-D) field and plasma maps of the cross section of the structure. For con- venience, the resistivity tensor η is assumed diagonal in the reconstruction coordinates, which allows its values to be es- timated from Ohm’s law, E+v×B=η·j. In the present paper, all three components of the electric field are used. We benchmark our numerical code by use of an exact, axi- symmetric solution of the resistive MHD equations and then apply it to synthetic data from a 3-D, resistive, MHD numer- ical simulation of reconnection in the geomagnetic tail, in a phase of the event where time dependence and deviations from 2-D are both weak. The resistivity used in the simu- lation is time-independent and localized around the recon- nection site in an ellipsoidal region. For the magnetic field, plasma density, and pressure, we find very good agreement between the reconstruction results and the simulation, but the electric field and plasma velocity are not predicted with the same high accuracy

Reconstruction of a Large-Scale Reconnection Exhaust Structure in the Solar Wind

We recover two-dimensional (2-D) magnetic field and flow field configurations from three spacecraft encounters with a single large-scale reconnection exhaust structure in the solar wind, using a new reconstruction method (Sonnerup and Teh, 2008) based on the ideal single-fluid MHD equations in a steady-state, 2-D geometry. The reconstruction is performed in the rest frame of the X-line, where the flow into, and the plasma jetting within, the exhaust region are clearly visible. The event was first identified by Phan et al. (2006) in the ACE, Cluster, and Wind data sets; they argued that quasi-steady reconnection persisted for over 2 h at a long (390 RE) X-line. The reconnection exhaust is sandwiched between two discontinuities, both of which contain elements of intermediate- and slow-mode behavior; these elements are co-located rather than being spatially separated. These composite discontinuities do not satisfy the coplanarity condition or the standard MHD jump conditions. For all three spacecraft, the Walén regression line slope was positive (negative) for the leading (trailing) discontinuity. Our MHD reconstruction shows that: (1) the X-line orientation was close to the bisector of the overall magnetic shear angle and exhibited a slow rotating motion toward the Sun-Earth line; (2) the X-line moved earthward, dawnward, and southward; (3) the reconnection electric field was small (~0.02 mV/m on average) and gradually decreased from the first crossing (ACE) to the last (Wind). The magnetic field and flow field configurations recovered from ACE and Cluster are similar while those recovered from Wind also include a magnetic island and an associated vortex. Reconnection persisted for at least 2.4 h involving inflow into the exhaust region from its two sides. Time-dependence in the reconnection electric fields seen by ACE and Wind indicates local temporal variations in the field configuration. In addition to the reconstruction results, we provide a description and analysis of many details from the crossings by the spacecraft

Learning nuanced cross-disciplinary citation metric normalization using the hierarchical Dirichlet process on big scholarly data

Citation counts have long been used in academia as a way of measuring, inter alia, the importance of journals, quantifying the significance and the impact of a researcher's body of work, and allocating funding for individuals and departments. For example, the h-index proposed by Hirsch is one of the most popular metrics that utilizes citation analysis to determine an individual's research impact. Among many issues, one of the pitfalls of citation metrics is the unfairness which emerges when comparisons are made between researchers in different fields. The algorithm we described in the present paper learns evidence based, nuanced, and probabilistic representations of academic fields, and uses data collected by crawling Google Scholar to perform field of study based normalization of citation based impact metrics such as the h-index.Postprin

Reconstruction of a Large-Scale Reconnection Exhaust Structure in the Solar Wind

We recover two-dimensional (2-D) magnetic field and flow field configurations from three spacecraft encounters with a single large-scale reconnection exhaust structure in the solar wind, using a new reconstruction method (Sonnerup and Teh, 2008) based on the ideal single-fluid MHD equations in a steady-state, 2-D geometry. The reconstruction is performed in the rest frame of the X-line, where the flow into, and the plasma jetting within, the exhaust region are clearly visible. The event was first identified by Phan et al. (2006) in the ACE, Cluster, and Wind data sets; they argued that quasi-steady reconnection persisted for over 2 h at a long (390 RE) X-line. The reconnection exhaust is sandwiched between two discontinuities, both of which contain elements of intermediate- and slow-mode behavior; these elements are co-located rather than being spatially separated. These composite discontinuities do not satisfy the coplanarity condition or the standard MHD jump conditions. For all three spacecraft, the Walén regression line slope was positive (negative) for the leading (trailing) discontinuity. Our MHD reconstruction shows that: (1) the X-line orientation was close to the bisector of the overall magnetic shear angle and exhibited a slow rotating motion toward the Sun-Earth line; (2) the X-line moved earthward, dawnward, and southward; (3) the reconnection electric field was small (~0.02 mV/m on average) and gradually decreased from the first crossing (ACE) to the last (Wind). The magnetic field and flow field configurations recovered from ACE and Cluster are similar while those recovered from Wind also include a magnetic island and an associated vortex. Reconnection persisted for at least 2.4 h involving inflow into the exhaust region from its two sides. Time-dependence in the reconnection electric fields seen by ACE and Wind indicates local temporal variations in the field configuration. In addition to the reconstruction results, we provide a description and analysis of many details from the crossings by the spacecraft

Negative and positive selection of antigen-specific cytotoxic T lymphocytes affected by the α3 domain of MHC I molecules

THE α1 and α2 domains of major histocompatibility complex (MHC) class I molecules function in the binding and presentation of foreign peptides to the T-cell antigen receptor and control both negative and positive selection of the T-cell repertoire. Although the α3 domain of class I is not involved in peptide binding, it does interact with the T-cell accessory molecule, CDS. CDS is important in the selection of T cells as anti-CDS antibody injected into perinatal mice interfers with this process. We previously used a hybrid class I molecule with the α1/α2 domains from L^d and the α3 domain from Q7^b and showed that this molecule binds an L^d-restricted peptide but does not interact with CD8-dependent cytotoxic T lymphocytes. Expression of this molecule in transgenic mice fails to negatively select a subpopulation of anti-L^d cytotoxic T lymphocytes. In addition, positive selection of virus-specific L^d-restricted cytotoxic T lymphocytes does not occur. We conclude that besides the α1/α2 domains of class I, the α3 domain plays an important part in both positive and negative selection of antigen-specific cells