A new modulation technique for high data rate low power UWB wireless optical communication in implantable biotelemetry systems

We report on the development of a novel modulation technique for UWB wireless optical communication systems for application in a transcutaneous biotelemetry. The solution, based on the generation of short laser pulses, allows for a high data rate link whilst achieving a significant power reduction (energy per bit) compared to the state-of-the-art. These features make this particularly suitable for emerging biomedical applications such as implantable neural/biosensor systems. The relatively simple architecture consists of a transmitter and receiver that can be integrated in a standard CMOS technology in a compact Silicon footprint. These parts include circuits for bias and drive current generation, conditioning and processing, optimised for low-volt age/low-power operation. Preliminary experimental findings validate the new paradigm and show good agreement with expected results. The complete system achieves a BER less than 10-7, with maximum data rate of 125Mbps and estimated total power consumption of less than 3mW

Advanced Vehicle Tracking system using GSM/GPRS and GPS

Vehicle Tracker is a Universal Anti-Larceny System for all kinds of motorcycles. The gadget is inserted inside a vehicle whose position is to be resolved and followed continuously. The composed device works utilizing Global Positioning System (GPS) and Global system for mobile communication/General Packet Radio Service (GSM/GPRS) technology that is the most widely recognized courses for vehicle tracking system. GPS and high sensitivity antenna are used for effective and precise location tracking of motorcycle through mobile application. Accelerometer sensor will alert the user of a possible larceny by detecting the slightest transition of the motorcycle. Immobilizer relay to remotely enable/incapacitate motorcycle ignition. Ignition switch status monitoring is utilized to detect key insertion. Fuel level sensor used to detect fuel larceny and to determine the information about fuel level in automobile tank

Physiological role for GABAA receptor desensitization in the induction of long-term potentiation at inhibitory synapses.

GGABAA receptors (GABAARs) are pentameric ligand-gated ion channels distributed throughout the brain where they mediate synaptic and tonic inhibition. Following activation, these receptors undergo desensitization which involves entry into long-lived agonist-bound closed states. Although the kinetic effects of this state are recognised and its structural basis has been uncovered, the physiological impact of desensitization on inhibitory neurotransmission remains unknown. Here we describe an enduring form of long-term potentiation at inhibitory synapses that elevates synaptic current amplitude for 24 h following desensitization of GABAARs in response to agonist exposure or allosteric modulation. Using receptor mutants and allosteric modulators we demonstrate that desensitization of GABAARs facilitates their phosphorylation by PKC, which increases the number of receptors at inhibitory synapses. These observations provide a physiological relevance to the desensitized state of GABAARs, acting as a signal to regulate the efficacy of inhibitory synapses during prolonged periods of inhibitory neurotransmission

Use of approximations of Hamilton-Jacobi-Bellman inequality for solving periodic optimization problems

We show that necessary and sufficient conditions of optimality in periodic optimization problems can be stated in terms of a solution of the corresponding HJB inequality, the latter being equivalent to a max-min type variational problem considered on the space of continuously differentiable functions. We approximate the latter with a maximin problem on a finite dimensional subspace of the space of continuously differentiable functions and show that a solution of this problem (existing under natural controllability conditions) can be used for construction of near optimal controls. We illustrate the construction with a numerical example.Comment: 29 pages, 2 figure

A search for candidate radio supernova remnants in the nearby irregular starburst galaxies NGC 4214 and NGC 4395

We present the results of a search for new candidate radio su­pernova remnants (SNRs) in the nearby starburst irregular galaxies NGC 4214 and NGC 4395 using archived radio observations made with the Very Large Array (VLA) at the wavelengths of 3.5 cm, 6 cm and 20 cm for NGC 4214 and 6 cm and 20 cm for NGC 4395. These observations were analyzed as part of our ongoing search for candidate radio SNRs in nearby galaxies: the goal of this search is to prepare a large sample of candidate radio SNRs for the purpose of a robust statistical study of the properties of these sources. Based on our analysis, we have confirmed the nonthermal nature of the discrete radio sources α and β in NGC 4214 and classify these sources as candidate radio SNRs based on their positional coincidences with HII regions in that galaxy. We have measured the flux densities of the two candidate radio SNRs at each wavelength and calculated corresponding spectral indices: we have also measured flux densities of two other discrete radio sources in these galaxies - ρ in NGC 4214 and #3 in NGC 4395 which we suspect to be additional candidate radio SNRs based on their positional coincidences with other HII regions in these galaxies. However, the radio data presently available for these sources can­not confirm such a classification and additional observations are needed. We have also calculated the radio luminosities Lradio at the wavelength of 20 cm for these two candidate radio SNRs as well as the corresponding values for the minimum total energy Emin required to power these radio sources via synchrotron emission and the corresponding magnetic field strength Bmin. We have compared our mean calculated values for these properties with the mean values for populations of candidate radio SNRs in other starburst galaxies: while the values for Lradio and Bmin are roughly comparable to the values seen in other starburst galaxies, the mean value for Emin is higher than the mean value of any other starburst galaxy. Finally, we include these two candidate radio SNRs in a discussion of the Σ − D relation for extragalactic candidate radio SNRs and find that these sources are located on the shallower end of the master Σ − D relation for all extragalactic SNRs as derived by Urošević et al.(2005).published_or_final_versio

Sorafenib dose escalation is not uniformly associated with blood pressure elevations in normotensive patients with advanced malignancies.

Hypertension after treatment with vascular endothelial growth factor (VEGF) receptor inhibitors is associated with superior treatment outcomes for advanced cancer patients. To determine whether increased sorafenib doses cause incremental increases in blood pressure (BP), we measured 12-h ambulatory BP in 41 normotensive advanced solid tumor patients in a randomized dose-escalation study. After 7 days' treatment (400 mg b.i.d.), mean diastolic BP (DBP) increased in both study groups. After dose escalation, group A (400 mg t.i.d.) had marginally significant further increase in 12-h mean DBP (P = 0.053), but group B (600 mg b.i.d.) did not achieve statistically significant increases (P = 0.25). Within groups, individuals varied in BP response to sorafenib dose escalation, but these differences did not correlate with changes in steady-state plasma sorafenib concentrations. These findings in normotensive patients suggest BP is a complex pharmacodynamic biomarker of VEGF inhibition. Patients have intrinsic differences in sensitivity to sorafenib's BP-elevating effects

Tensor Product Approximation (DMRG) and Coupled Cluster method in Quantum Chemistry

We present the Copupled Cluster (CC) method and the Density matrix Renormalization Grooup (DMRG) method in a unified way, from the perspective of recent developments in tensor product approximation. We present an introduction into recently developed hierarchical tensor representations, in particular tensor trains which are matrix product states in physics language. The discrete equations of full CI approximation applied to the electronic Schr\"odinger equation is casted into a tensorial framework in form of the second quantization. A further approximation is performed afterwards by tensor approximation within a hierarchical format or equivalently a tree tensor network. We establish the (differential) geometry of low rank hierarchical tensors and apply the Driac Frenkel principle to reduce the original high-dimensional problem to low dimensions. The DMRG algorithm is established as an optimization method in this format with alternating directional search. We briefly introduce the CC method and refer to our theoretical results. We compare this approach in the present discrete formulation with the CC method and its underlying exponential parametrization.Comment: 15 pages, 3 figure

TugaTAC Broker: A Fuzzy Logic Adaptive Reasoning Agent for Energy Trading

Smart Grid technologies are changing the way energy is generated, distributed and consumed. With the increasing spread of renewable power sources, new market strategies are needed to guarantee a more sustainable participation and less dependency of bulk generation. In PowerTAC (Power Trading Agent Competition), different software agents compete in a simulated energy market, impersonating broker companies to create and manage attractive tariffs for customers while aiming to profit. In this paper, we present TugaTAC Broker, a PowerTAC agent that uses a fuzzy logic mechanism to compose tariffs based on its customers portfolio. Fuzzy sets allow adaptive configurations for brokers in different scenarios. To validate and compare the performance of TugaTAC, we have run a local version of the PowerTAC competition. The experiments comprise TugaTAC competing against other simple agents and a more realistic configuration, with instances of the winners of previous editions of the competition. Preliminary results show a promising dynamic: our approach was able to manage imbalances and win the competition in the simple case, but need refinements to compete with more sophisticated market. (c) Springer International Publishing Switzerland 2016

Cognitively-inspired Agent-based Service Composition for Mobile & Pervasive Computing

Automatic service composition in mobile and pervasive computing faces many challenges due to the complex and highly dynamic nature of the environment. Common approaches consider service composition as a decision problem whose solution is usually addressed from optimization perspectives which are not feasible in practice due to the intractability of the problem, limited computational resources of smart devices, service host's mobility, and time constraints to tailor composition plans. Thus, our main contribution is the development of a cognitively-inspired agent-based service composition model focused on bounded rationality rather than optimality, which allows the system to compensate for limited resources by selectively filtering out continuous streams of data. Our approach exhibits features such as distributedness, modularity, emergent global functionality, and robustness, which endow it with capabilities to perform decentralized service composition by orchestrating manifold service providers and conflicting goals from multiple users. The evaluation of our approach shows promising results when compared against state-of-the-art service composition models.Comment: This paper will appear on AIMS'19 (International Conference on Artificial Intelligence and Mobile Services) on June 2