Interplay between double-exchange, superexchange, and Lifshitz localization in doped manganites

Considering the disorder caused in manganites by the substitution Mn→Fe or Ga, we accomplish a systematic study of doped manganites begun in previous papers. To this end, a disordered model is formulated and solved using the variational mean-field technique. The subtle interplay between double exchange, superexchange, and disorder causes similar effects on the dependence of T_(C) on the percentage of Mn substitution in the cases considered. Yet, in La_(2/3)Ca_(1/3)Mn_(1-y)Ga_(y)O_(3) our results suggest a quantum critical point (QCP) for y ≈ 0.1–0.2, associated to the localization of the electronic states of the conduction band. In the case of La_(x)Ca_(x)Mn_(1-y)Fe_(y)O_(3) (with x = 1/3,3/8) no such QCP is expected.

Localization of quantum biequivariant D-modules and q-W algebras

Peer reviewed

Nerve localization techniques for peripheral nerve block and possible future directions

Ultrasound guidance is now a standard nerve localization technique for peripheral nerve block (PNB). Ultrasonography allows simultaneous visualization of the target nerve, needle, local anesthetic injectate and surrounding anatomical structures. Accurate deposition of local anesthetic next to the nerve is essential to the success of the nerve block procedure. Unfortunately, due to limitations in the visibility of both needle tip and nerve surface, the precise relationship between needle tip and target nerve is unknown at the moment of injection. Importantly, nerve injury may result both from an inappropriately placed needle tip and inappropriately placed local anesthetic. The relationship between the block needle tip and target nerve is of paramount importance to the safe conduct of peripheral nerve block. This review summarizes the evolution of nerve localization in regional anesthesia, characterizes a problem faced by clinicians in performing ultrasound guided nerve block and explores the potential technological solutions to this problem.

Using Coding to Improve Localization and Backscatter Communication Performance in Low-Power Sensor Networks

Backscatter communication is an emerging wireless technology that recently has gained an increase in attention from both academic and industry circles. The key innovation of the technology is the ability of ultra-low power devices to utilize nearby existing radio signals to communicate. As there is no need to generate their own energetic radio signal, the devices can benefit from a simple design, are very inexpensive and are extremely energy efficient compared with traditional wireless communication. These benefits have made backscatter communication a desirable candidate for distributed wireless sensor network applications with energy constraints.

The backscatter channel presents a unique set of challenges. Unlike a conventional one-way communication (in which the information source is also the energy source), the backscatter channel experiences strong self-interference and spread Doppler clutter that mask the information-bearing (modulated) signal scattered from the device. Both of these sources of interference arise from the scattering of the transmitted signal off of objects, both stationary and moving, in the environment. Additionally, the measurement of the location of the backscatter device is negatively affected by both the clutter and the modulation of the signal return.

This work proposes a channel coding framework for the backscatter channel consisting of a bi-static transmitter/receiver pair and a quasi-cooperative transponder. It proposes to use run-length limited coding to mitigate the background self-interference and spread-Doppler clutter with only a small decrease in communication rate. The proposed method applies to both binary phase-shift keying (BPSK) and quadrature-amplitude modulation (QAM) scheme and provides an increase in rate by up to a factor of two compared with previous methods.

Additionally, this work analyzes the use of frequency modulation and bi-phase waveform coding for the transmitted (interrogating) waveform for high precision range estimation of the transponder location. Compared to previous methods, optimal lower range sidelobes are achieved. Moreover, since both the transmitted (interrogating) waveform coding and transponder communication coding result in instantaneous phase modulation of the signal, cross-interference between localization and communication tasks exists. Phase discriminating algorithm is proposed to make it possible to separate the waveform coding from the communication coding, upon reception, and achieve localization with increased signal energy by up to 3 dB compared with previous reported results.

The joint communication-localization framework also enables a low-complexity receiver design because the same radio is used both for localization and communication.

Simulations comparing the performance of different codes corroborate the theoretical results and offer possible trade-off between information rate and clutter mitigation as well as a trade-off between choice of waveform-channel coding pairs. Experimental results from a brass-board microwave system in an indoor environment are also presented and discussed.

RNA Localization and Translational Regulation on the Endoplasmic Reticulum

mRNA localization is emerging as a critical cellular mechanism for the spatiotemporal regulation of protein expression and serves important roles in oogenesis, embryogenesis, cell fate specification, and synapse formation. Signal sequence-encoding mRNAs are localized to the endoplasmic reticulum (ER) membrane by either of two mechanisms, a canonical mechanism of translation on ER-bound ribosomes (signal recognition particle pathway), or a poorly understood direct ER anchoring mechanism. In this study, we identify that the ER integral membrane proteins function as RNA-binding proteins and play important roles in the direct mRNA anchoring to the ER. We report that one of the ER integral membrane RNA-binding protein, AEG-1 (astrocyte elevated gene-1), functions in the direct ER anchoring and translational regulation of mRNAs encoding endomembrane transmembrane proteins. HITS-CLIP and PAR-CLIP analyses of the AEG-1 mRNA interactome of human hepatocellular carcinoma cells revealed a high enrichment for mRNAs encoding endomembrane organelle proteins, most notably encoding transmembrane proteins. AEG-1 binding sites were highly enriched in the coding sequence and displayed a signature cluster enrichment downstream of encoded transmembrane domains. In overexpression and knockdown models, AEG-1 expression markedly regulates translational efficiency and protein functions of two of its bound transcripts, MDR1 and NPC1. This study reveals a molecular mechanism for the selective localization of mRNAs to the ER and identifies a novel post-transcriptional gene regulation function for AEG-1 in membrane protein expression.

Axis Mapping: The Estimation of Surface Orientations and its Applications in Vehicle Localization and Structural Geology

The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.

Localization of a mobile robot based on odometry and natural landmarks using extended kalman filter

SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

Multirobot Tethering for Localization and Control

Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. This becomes more critical if the state estimate is an integral part of system control. We investigate the use of particle filter estimation techniques on a hovercraft vehicle. The marginally stable dynamics of a hovercraft require reliable state estimates for proper stability and control. We use the Monte Carlo localization method, which implements a particle filter in a recursive state estimate algorithm. An H-infinity controller, designed to accommodate the latency inherent in our state estimation, provides stability and controllability to the hovercraft. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. By tracking and controlling the secondary robot, we can position the mobile feature throughout the environment to ensure a high confidence estimate, thus maintaining stability in the system. A laser rangefinder is the sensor the hovercraft uses to track the secondary robot, observe the environment, and facilitate successful localization and stability in motion.

Localization of a mobile robot based on odometry and natural landmarks using extended kalman filter

SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.

Expression-based and co-localization detection of arabinogalactan protein 6 and arabinogalactan protein 11 interactors in Arabidopsis pollen and pollen tubes

Arabinogalactan proteins (AGPs) are cell wall proteoglycans that have been shown to be important for pollen development. An Arabidopsis double null mutant for two pollen-specific AGPs (agp6 agp11) showed reduced pollen tube growth and compromised response to germination cues in vivo. A microarray experiment was performed on agp6 agp11 pollen tubes to search for genetic interactions in the context of pollen tube growth. A yeast two-hybrid experiment for AGP6 and AGP11 was also designed.

CONCURRENT LOCALIZATION AND MAPPING WITH SONAR SENSORS AND CONSIDERATION OF VEHICLE MOTION

Simultaneous Localization and Mapping (SLAM) is a procedure used to determine the location of a mobile vehicle in an unknown environment, while constructing a map of the unknown environment at the same time. Mobile platforms, which make use of SLAM algorithms, have industrial applications in autonomous maintenance, such as the inspection of flaws and defects in oil pipelines and storage tanks. A typical SLAM consists of four main components, namely, experimental setup (data gathering), vehicle pose estimation, feature extraction, and filtering. Feature extraction is the process of realizing significant features from the unknown environment such as corners, edges, walls, and interior features. In this work, an original feature extraction algorithm specific to distance measurements obtained through SONAR sensor data is presented. This algorithm has been constructed by combining the SONAR Salient Feature Extraction Algorithm and the Triangulation Hough Based Fusion with point-in-polygon detection. The reconstructed maps obtained through simulations and experimental data with the fusion algorithm are compared to the maps obtained with existing feature extraction algorithms. Based on the results obtained, it is suggested that the proposed algorithm can be employed as an option for data obtained from SONAR sensors in environment, where other forms of sensing are not viable. The algorithm fusion for feature extraction requires the vehicle pose estimation as an input, which is obtained from a vehicle pose estimation model. For the vehicle pose estimation, the author uses sensor integration to estimate the pose of the mobile vehicle. Different combinations of these sensors are studied (e.g., encoder, gyroscope, or encoder and gyroscope). The different sensor fusion techniques for the pose estimation are experimentally studied and compared. The vehicle pose estimation model, which produces the least amount of error, is used to generate inputs for the feature extraction algorithm fusion. In the experimental studies, two different environmental configurations are used, one without interior features and another one with two interior features. Numerical and experimental findings are discussed. Finally, the SLAM algorithm is implemented along with the algorithms for feature extraction and vehicle pose estimation. Three different cases are experimentally studied, with the floor of the environment intentionally altered to induce slipping. Results obtained for implementations with and without SLAM are compared and discussed. The present work represents a step towards the realization of autonomous inspection platforms for performing concurrent localization and mapping in harsh environments.

THE ROLE OF THE MECHANICAL ENVIRONMENT ON CANCER CELL TRANSMIGRATION AND MRNA LOCALIZATION

Most cancer-related deaths are due to metastasis formation, the ability of cancer cells to break away from the primary tumor site, transmigrate through the endothelium, and form secondary tumors in distant areas. Many studies have identified links between the mechanical properties of the cellular microenvironment and the behavior of cancer cells. Cells may experience heterogeneous microenvironments of varying stiffness during tumor progression, transmigration, and invasion into the basement membrane. In addition to mechanical factors, the localization of RNAs to lamellipodial regions has been proposed to play an important part in metastasis. This dissertation provides a quantitative evaluation of the biophysical effects on cancer cell transmigration and RNA localization. In the first part of this dissertation, we sought to compare cancer cell and leukocyte transmigration and investigate the impact of matrix stiffness on transmigration process. We found that cancer cell transmigration includes an additional step, ‘incorporation’, into the endothelial cell (EC) monolayer. During this phase, cancer cells physically displace ECs and spread into the monolayer. Furthermore, the effects of subendothelial matrix stiffness and endothelial activation on cancer cell incorporation are cell-specific, a notable difference from the process by which leukocytes transmigrate. Collectively, our results provide mechanistic insights into tumor cell extravasation and demonstrate that incorporation into the endothelium is one of the earliest steps. In the next part of this work, we investigated how matrix stiffness impacts RNA localization and its relevance to cancer metastasis. In migrating cells, the tumor suppressor protein, adenomatous polyposis coli (APC) targets RNAs to cellular protrusions. We observed that increasing stiffness promotes the peripheral localization of these APC-dependent RNAs and that cellular contractility plays a role in regulating this pathway. We next investigated the mechanism underlying the effect of substrate stiffness and cellular contractility. We found that contractility drives localization of RNAs to protrusions through modulation of detyrosinated microtubules, a network of modified microtubules that associate with, and are required for localization of APC-dependent RNAs. These results raise the possibility that as the matrix environment becomes stiffer during tumor progression, it promotes the localization of RNAs and ultimately induces a metastatic phenotype.

Silencing the gip gene of Phytophthora cinnamomi by iRNA and studying the subcellular localization of GIP and NPP1 proteins

Ink Disease is considered one of the most important causes of the decline of chestnut orchards. The break in yield of Castanea sativa Mill is caused by two species: Phytophthora cinnamomi and Phytophthora cambivora, being the first one the foremost pathogen of ink disease in Portugal. P. cinnamomi is one of the most aggressive and widespread plant pathogen with nearly 1,000 host species. This oomycete causes enormous economic losses and it is responsible for the decline of many plant species in Europe and worldwide. Up to now no efficient treatments are available to fight these pathogens. Because of the importance of chestnut at economical and ecological levels, especially in Portugal, it becomes essential to explore the molecular mechanisms that determine the interaction between Phytophthora species and host plants through the study of proteins GIP (glucanase inhibitor protein) and NPP1 (necrosis-inducing Phytophthora protein 1) produced by P. cinnamomi during the infection. The technique of RNA interference was used to knockdown the gip gene of P. cinnamomi. Transformants obtained with the silenced gene have been used to infect C. sativa, in order to determine the effect of gene silencing on the plant phenotype. To know more about the function of GIP and NPP1 involved in the mechanism of infection, the ORF’s of gip and npp1 genes have been cloned to the pTOR-eGFP vector for a future observation of P. cinnamomi transformants with fluorescent microscopy and determination of the subcellular localization. Moreover the prediction by bioinformatics tools indicates that both GIP and NPP1 proteins are secreted. The results allow to predict the secretory destination of both GIP and NPP1 proteins and confirm RNAi as a potential alternative biological tool in the control and management of P. cinnamomi. Keywords:

Alzheimer’s electroencephalogram event scalp and source localization

Alzheimer’s disease is the most common cause of dementia which causes a progressive and irreversible impairment of several cognitive functions. The aging population has been increasing significantly in recent decades and this disease affects mainly the elderly. Its diagnostic accuracy is relatively low and there is not a biomarker able to detect AD without invasive tests. Despite the progress in better understanding the disease there remains no prospect of cure at least in the near future. The electroencephalogram (EEG) test is a widely available technology in clinical settings. It may help diagnosis of brain disorders, once it can be used in patients who have cognitive impairment involving a general decrease in overall brain function or in patients with a located deficit. This study is a new approach to improve the scalp localization and the detection of brain anomalies (EEG temporal events) sources associated with AD by using the EEG.