Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.

Fluorescent PET (Photoinduced Electron Transfer) Sensors with Targeting/Anchoring Modules as Molecular Versions of Submarine Periscopes for Mapping Membrane-Bounded Protons

The two families of fluorescent PET (photoinduced electron transfer) sensors (1-9) show that the effective proton density near the surface of several micelle membranes changes over 2-3 orders of magnitude as the microlocation of the sensor (with respect to the membrane) is altered via hydrophobic tuning.

'Off-On' Fluorescent Sensors for Physiological levels of Magnesium Ions based on Photoinduced Electron Transfer (PET) which also behave as OR Logic Gates

The fluorescence of molecules 1-3 is enhanced by factors of up to 67 in the presence of magnesium and calcium ions in neutral water which allows the selective monitoring of magnesium ions under simulated physiological conditions and permits the construction of truth tables with OR logic when these molecules are viewed as ion input-photon output molecuIar devices.

Direct Visual Indication of pH Windows: 'Off-On-Off' Fluorescent PET (Photoinduced Electron Transfer) Sensors/Switches

1–3, which contain a fluorophore and two proton receptors with opposite PET (photoinduced electron transfer) characteristics, only display strong fluorescence within a pH window whose position and width are tunable.

Arenedicarboximide Building Blocks for Fluorescent Photoinduced Electron Transfer pH Sensors Applicable with Different Media and Communication Wavelengths

N-(aminoalkyl)-4-chloronaphthalene-
1,8-dicarboximides 1, N-
(aminoalkyl)-4-acetamidonaphthalene-
1,8-dicarboximides 3 and N,N'-bis(aminoalkyl)-
perylene-3,4:9,10-tetracarboxydiimides
4 show good fluorescent off ±
on switching in aqueous alcoholic solution
with protons as required for fluorescent
PET sensor design. The excitation
wavelengths lie in the ultraviolet
(lmaxˆ345 and 351 nm) for 1 and 3 and
in the blue-green (lmaxˆ528, 492 and
461 nm) for 4; the emission wavelengths
lie in the violet (lmaxˆ408 nm) for 1, in
the blue (lmaxˆ474 nm) for 3 and in the
yellow-orange (lmaxˆ543 and 583 nm)
for 4. Compound 4b shows substantial
fluorescence enhancement with protons
when immobilized in a poly(vinylchloride)
matrix, provided that 2-nitrophenyloctyl
ether plasticizer and potassium
tetrakis(4-chlorophenyl)borate additive
are present to prevent dye crystallization
and to facilitate proton diffusion
into the membrane, respectively.

Open Source Telecommunications Framework for Time-Series Data from Smart Grid Sensors.

This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.

BAR domains as sensors of membrane curvature:the amphiphysin BAR structure

The BAR (Bin/amphiphysin/Rvs) domain is the most conserved feature in amphiphysins from yeast to human and is also found in endophilins and nadrins. We solved the structure of the Drosophila amphiphysin BAR domain. It is a crescent-shaped dimer that binds preferentially to highly curved negatively charged membranes. With its N-terminal amphipathic helix and BAR domain (N-BAR), amphiphysin can drive membrane curvature in vitro and in vivo. The structure is similar to that of arfaptin2, which we find also binds and tubulates membranes. From this, we predict that BAR domains are in many protein families, including sorting nexins, centaurins, and oligophrenins. The universal and minimal BAR domain is a dimerization, membrane-binding, and curvature-sensing module.

Measurement of Local Sodium Ion Levels near Micellar Surfaces with Fluorescent PET (Photoinduced Electron Transfer) Sensors

Na+ near membranes controls our nerve signals, besides several other crucial bioprocesses. We demonstrate that fluorescent PET (photoinduced electron transfer) sensor molecules target Na+ in nanospaces near micellar membranes with excellent discrimination against H+. They find that Na+ near anionic micelles is concentrated by factors of upto 160. Sensor molecules which are not held tight to the micelle surface find a Na+ amplification factor of 8 only. These findings are strengthened by the employment of control compounds whose PET processes are permanently ‘on’ or permanently ‘off’.