Structural determinants of subunit -subunit interactions and subcellular localization of the calcium /calmodulin -dependent protein kinase II

The multifunctional Ca$\sp{2+}$/calmodulin-dependent protein kinase II (CaM kinase) is a Ser/Thr directed protein kinase that participates in diverse Ca$\sp{2+}$ signaling pathways in neurons. The function of CaM kinase depends upon the ability of subunits to form oligomers and to interact with other proteins. Oligomerization is required for autophosphorylation which produces significant functional changes that include Ca$\sp{2+}$/calmodulin-independent activity and calmodulin trapping. Associations with other proteins localize CaM kinase to specific substrates and effectors which serves to optimize the efficiency and speed of signal transduction. In this thesis, we investigate the interactions that underlie the appropriate positioning of CaM kinase activity in cells. We demonstrate that the subcellular distribution of CaM kinase is dynamic in hippocampal slices exposed to anoxic/aglycemic insults and to high K$\sp{+}$-induced depolarization. We determine the localization of CaM kinase domains expressed in neurons and PC-12 cells and find that the C-terminal domain of the $\alpha$ subunit is necessary for localization to dendrites. Moreover, monomeric forms of the enzyme gain access to the nucleus. Attempts made to identify novel CaM kinase binding proteins using the yeast two-hybrid system resulted in the isolation of hundreds of positive clones. Those that have been sequenced are identical to CaM kinase isoforms. Finally, we report the discovery of specific regions within the C-terminal domain that are necessary and sufficient for subunit-subunit interactions. Differences between the $\alpha$ and $\beta$ isoforms were discovered that indicate unique structural requirements for oligomerization. A model for how CaM kinase subunits interact to form holoenzymes and how structural heterogeneity might influence CaM kinase function is presented. ^

Localization of ion-regulatory epithelia in embryos and hatchlings of two cephalopods

The tissue distribution and ontogeny of Na+/K+-ATPase has been examined as an indicator for ion-regulatory epithelia in whole animal sections of embryos and hatchlings of two cephalopod species: the squid Loligo vulgaris and the cuttlefish Sepia officinalis. This is the first report of the immunohistochemical localization of cephalopod Na+/K+-ATPase with the polyclonal antibody alpha (H-300) raised against the human alpha1-subunit of Na+/K+-ATPase. Na+/K+-ATPase immunoreactivity was observed in several tissues (gills, pancreatic appendages, nerves), exclusively located in baso-lateral membranes lining blood sinuses. Furthermore, large single cells in the gill of adult L. vulgaris specimens closely resembled Na+/K+-ATPase-rich cells described in fish. Immunohistochemical observations indicated that the amount and distribution of Na+/K+-ATPase in late cuttlefish embryos was similar to that found in juvenile and adult stages. The ion-regulatory epithelia (e.g., gills, excretory organs) of the squid embryos and paralarvae exhibited less differentiation than adults. Na+/K+-ATPase activities for whole animals were higher in hatchlings of S. officinalis (157.0 ± 32.4 µmol/g FM/h) than in those of L. vulgaris (31.8 ± 3.3 µmol/g FM/h). S. officinalis gills and pancreatic appendages achieved activities of 94.8 ± 18.5 and 421.8 ± 102.3 µmol ATP/g FM/h, respectively. High concentrations of Na+/K+-ATPase in late cephalopod embryos might be important in coping with the challenging abiotic conditions (low pH, high pCO2) that these organisms encounter inside their eggs. Our results also suggest a higher sensitivity of squid vs. cuttlefish embryos to environmental acid-base disturbances.

Nonparametric Message Passing Methods for Cooperative Localization and Tracking

The objective of this thesis is the development of cooperative localization and tracking algorithms using nonparametric message passing techniques. In contrast to the most well-known techniques, the goal is to estimate the posterior probability density function (PDF) of the position of each sensor. This problem can be solved using Bayesian approach, but it is intractable in general case. Nevertheless, the particle-based approximation (via nonparametric representation), and an appropriate factorization of the joint PDFs (using message passing methods), make Bayesian approach acceptable for inference in sensor networks. The well-known method for this problem, nonparametric belief propagation (NBP), can lead to inaccurate beliefs and possible non-convergence in loopy networks. Therefore, we propose four novel algorithms which alleviate these problems: nonparametric generalized belief propagation (NGBP) based on junction tree (NGBP-JT), NGBP based on pseudo-junction tree (NGBP-PJT), NBP based on spanning trees (NBP-ST), and uniformly-reweighted NBP (URW-NBP). We also extend NBP for cooperative localization in mobile networks. In contrast to the previous methods, we use an optional smoothing, provide a novel communication protocol, and increase the efficiency of the sampling techniques. Moreover, we propose novel algorithms for distributed tracking, in which the goal is to track the passive object which cannot locate itself. In particular, we develop distributed particle filtering (DPF) based on three asynchronous belief consensus (BC) algorithms: standard belief consensus (SBC), broadcast gossip (BG), and belief propagation (BP). Finally, the last part of this thesis includes the experimental analysis of some of the proposed algorithms, in which we found that the results based on real measurements are very similar with the results based on theoretical models.

A new set of relativistic screening constants for the screened hydrogenic model

AnewRelativisticScreenedHydrogenicModel has been developed to calculate atomic data needed to compute the optical and thermodynamic properties of high energy density plasmas. The model is based on anewset of universal screeningconstants, including nlj-splitting that has been obtained by fitting to a large database of ionization potentials and excitation energies. This database was built with energies compiled from the National Institute of Standards and Technology (NIST) database of experimental atomic energy levels, and energies calculated with the Flexible Atomic Code (FAC). The screeningconstants have been computed up to the 5p3/2 subshell using a Genetic Algorithm technique with an objective function designed to minimize both the relative error and the maximum error. To select the best set of screeningconstants some additional physical criteria has been applied, which are based on the reproduction of the filling order of the shells and on obtaining the best ground state configuration. A statistical error analysis has been performed to test the model, which indicated that approximately 88% of the data lie within a ±10% error interval. We validate the model by comparing the results with ionization energies, transition energies, and wave functions computed using sophisticated self-consistent codes and experimental data.

A low power routing algorithm for localization in IEEE 802.15.4 networks

Many context-aware applications rely on the knowledge of the position of the user and the surrounding objects to provide advanced, personalized and real-time services. In wide-area deployments, a routing protocol is needed to collect the location information from distant nodes. In this paper, we propose a new source-initiated (on demand) routing protocol for location-aware applications in IEEE 802.15.4 wireless sensor networks. This protocol uses a low power MAC layer to maximize the lifetime of the network while maintaining the communication delay to a low value. Its performance is assessed through experimental tests that show a good trade-off between power consumption and time delay in the localization of a mobile device.

An energy-efficient strategy for combined RSS-PDR indoor localization

We propose an optimization-based framework to minimize the energy consumption in a sensor network when using an indoor localization system based on the combination of received signal strength (RSS) and pedestrian dead reckoning (PDR). The objective is to find the RSS localization frequency and the number of RSS measurements used at each localization round that jointly minimize the total consumed energy, while ensuring at the same time a desired accuracy in the localization result. The optimization approach leverages practical models to predict the localization error and the overall energy consumption for combined RSS-PDR localization systems. The performance of the proposed strategy is assessed through simulation, showing energy savings with respect to other approaches while guaranteeing a target accuracy.

A Bayesian strategy to enhance the performance of indoor localization systems

This work describes the probabilistic modelling af a Bayesian-based mechanism to improve location estimates of an already deployed location system by fusing its outputs with low-cost binary sensors. This mechanism takes advantege of the localization captabilities of different technologies usually present in smart environments deployments. The performance of the proposed algorithm over a real sensor deployment is evaluated using simulated and real experimental data.

Dynamic chanel model LMS updating for RSS-based localization

Received signal strength-based localization systems usually rely on a calibration process that aims at characterizing the propagation channel. However, due to the changing environmental dynamics, the behavior of the channel may change after some time, thus, recalibration processes are necessary to maintain the positioning accuracy. This paper proposes a dynamic calibration method to initially calibrate and subsequently update the parameters of the propagation channel model using a Least Mean Squares approach. The method assumes that each anchor node in the localization infrastructure is characterized by its own propagation channel model. In practice, a set of sniffers is used to collect RSS samples, which will be used to automatically calibrate each channel model by iteratively minimizing the positioning error. The proposed method is validated through numerical simulation, showing that the positioning error of the mobile nodes is effectively reduced. Furthermore, the method has a very low computational cost; therefore it can be used in real-time operation for wireless resource-constrained nodes.

Equation of state for hot dense matter using a relativistic screened hydrogenic model

The study of matter under conditions of high density, pressure, and temperature is a valuable subject for inertial confinement fusion (ICF), astrophysical phenomena, high-power laser interaction with matter, etc. In all these cases, matter is heated and compressed by strong shocks to high pressures and temperatures, becomes partially or completely ionized via thermal or pressure ionization, and is in the form of dense plasma. The thermodynamics and the hydrodynamics of hot dense plasmas cannot be predicted without the knowledge of the equation of state (EOS) that describes how a material reacts to pressure and how much energy is involved. Therefore, the equation of state often takes the form of pressure and energy as functions of density and temperature. Furthermore, EOS data must be obtained in a timely manner in order to be useful as input in hydrodynamic codes. By this reason, the use of fast, robust and reasonably accurate atomic models, is necessary for computing the EOS of a material.

Optimized edge appearance probability for cooperative localization based on tree-reweighted nonparametric belief propagation

Nonparametric belief propagation (NBP) is a well-known particle-based method for distributed inference in wireless networks. NBP has a large number of applications, including cooperative localization. However, in loopy networks NBP suffers from similar problems as standard BP, such as over-confident beliefs and possible nonconvergence. Tree-reweighted NBP (TRW-NBP) can mitigate these problems, but does not easily lead to a distributed implementation due to the non-local nature of the required so-called edge appearance probabilities. In this paper, we propose a variation of TRWNBP, suitable for cooperative localization in wireless networks. Our algorithm uses a fixed edge appearance probability for every edge, and can outperform standard NBP in dense wireless networks.

A Radio Frequency Identification System for accurate indoor localization

In this paper we present a novel Radio Frequency Identification (RFID) system for accurate indoor localization. The system is composed of a standard Ultra High Frequency (UHF), ISO-18006C compliant RFID reader, a large set of standard passive RFID tags whose locations are known, and a newly developed tag-like RFID component that is attached to the items that need to be localized. The new semi-passive component, referred to as sensatag (sense-a-tag), has a dual functionality wherein it can sense the communication between the reader and standard tags which are in its proximity, and also communicate with the reader like standard tags using backscatter modulation. Based on the information conveyed by the sensatags to the reader, localization algorithms based on binary sensor principles can be developed. We present results from real measurements that show the accuracy of the proposed system.

Relativistic description of 3He(e,e'p)2H

The relativistic distorted-wave impulse approximation is used to describe the 3He(e, e′ p)2H process. We describe the 3He nucleus within the adiabatic hyperspherical expansion method with realistic nucleon-nucleon interactions. The overlap between the 3He and the deuteron wave functions can be accurately computed from a three-body calculation. The nucleons are described by solutions of the Dirac equation with scalar and vector (S–V) potentials. The wave function of the outgoing proton is obtained by solving the Dirac equation with a S–V optical potential fitted to elastic proton scattering data on the residual nucleus. Within this theoretical framework, we compute the cross section of the reaction and other observables like the transverse-longitudinal asymmetry, and compare them with the available experimental data measured at JLab.

Improving target localization accuracy of wireless visual sensor networks

This paper discusses the target localization problem of wireless visual sensor networks. Specifically, each node with a low-resolution camera extracts multiple feature points to represent the target at the sensor node level. A statistical method of merging the position information of different sensor nodes to select the most correlated feature point pair at the base station is presented. This method releases the influence of the accuracy of target extraction on the accuracy of target localization in universal coordinate system. Simulations show that, compared with other relative approach, our proposed method can generate more desirable target localization's accuracy, and it has a better trade-off between camera node usage and localization accuracy.

Subcellular localization and tissue specific expression of amidase 1 from Arabidopsis thaliana

Amidase 1 (AMI1) from Arabidopsis thaliana converts indole-3-acetamide (IAM), into indole-3-acetic acid (IAA). AMI1 is part of a small isogene family comprising seven members in A. thaliana encoding proteins which share a conserved glycine- and serine-rich amidase-signature. One member of this family has been characterized as an N-acylethanolamine-cleaving fatty acid amidohydrolase (FAAH) and two other members are part of the preprotein translocon of the outer envelope of chloroplasts (Toc complex) or mitochondria (Tom complex) and presumably lack enzymatic activity. Among the hitherto characterized proteins of this family, AMI1 is the only member with indole-3-acetamide hydrolase activity, and IAM is the preferred substrate while N-acylethanolamines and oleamide are not hydrolyzed significantly, thus suggesting a role of AMI1 in auxin biosynthesis. Whereas the enzymatic function of AMI1 has been determined in vitro, the subcellular localization of the enzyme remained unclear. By using different GFP-fusion constructs and an A. thaliana transient expression system, we show a cytoplasmic localization of AMI1. In addition, RT-PCR and anti-amidase antisera were used to examine tissue specific expression of AMI1 at the transcriptional and translational level, respectively. AMI1-expression is strongest in places of highest IAA content in the plant. Thus, it is concluded that AMI1 may be involved in de novo IAA synthesis in A. thaliana.