Self-Assembled Discrete Molecules for Sensing Nitroaromatics

Efficient sensing of trace amount nitroaromatic (NAC) explosives has become a major research focus in recent time due to concerns over national security as well as their role as environment pollutants. NO2-containing electron-deficient aromatic compounds, such as picric acid (PA), trinitrotoluene (TNT), and dinitrotoluene (DNT), are the common constituents of many commercially available chemical explosives. In this article, we have summarized our recent developments on the rational design of electron-rich self-assembled discrete molecular sensors and their efficacy in sensing nitroaromatics both in solution as well as in vapor phase. Several p-electron-rich fluorescent metallacycles (squares, rectangles, and tweezers/pincers) and metallacages (trigonal and tetragonal prisms) have been synthesized by means of metal-ligand coordination-bonding interactions, with enough internal space to accommodate electron-deficient nitroaromatics at the molecular level by multiple supramolecular interactions. Such interactions subsequently result in the detectable fluorescence quenching of sensors even in the presence of trace quantities of nitroaromatics. The fascinating sensing characteristics of molecular architectures discussed in this article may enable future development of improved sensors for nitroaromatic explosives.

Dynamics of Plasmon in Graphene Oxide

Dynamic effects of plasmon such as scattering with defect boundaries and oxygen impurities in the graphene oxide are investigated. Study of plasmon dynamics helps in understanding electronic, opto-electronic and biological applications of graphene based nanostructures. Tuning or control over such applications is made possible by graphene nanostructure engineering. We have modeled defects with increased smoothing of defect edge in graphene keeping area of the defect constant. Scattering of plasmons in graphene with defects is modeled using an electromagnetic field coupled inter-atomic potential approach with finite element discretization of the atomic vibrational and electromagnetic field degrees of freedom. Our calculations show pi + sigma plasmon red shifting under sharp defect edges whereas pi plasmon show high extinction efficiency. Strong localization of electric fields near the sharp defect edges is observed. Observations on plasmons and its dynamics draws attention in designing novel optoelectronic devices and binders for bio-molecules.

Non-invasive pressure monitoring by hoop strain using Fiber Bragg Grating sensor

Non-invasive, real-time dynamic monitoring of pressure inside a column with the aid of Fiber Bragg Grating (FBG) sensor is presented in the present work. A bare FBG sensor is adhered on the circumference of a pressure column normal to its axis, which has the ability to acquire the hoop strain induced by the pressure variation inside the column. Pressure induced hoop strain response obtained using FBG sensor is validated against the pressure measurements obtained from conventional pressure gauge. Further, a protrusion setup on the outer surface of the column has been proposed over which a secondary FBG sensor is bonded normal to its axis, in order to increase the gauge length of this FBG sensor. This is carried out in order to validate the variation in sensitivity of the protrusion bonded FBG sensor compared to the bare FBG sensor bonded over the surface. A comparative study is done between the two FBG sensors and a conventional pressure gauge in order to establish the capacity of FBG sensor obtained hoop strain response for pressure monitoring inside the column.

Error exponent analysis of energy-based Bayesian decentralized spectrum sensing under fading

This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.

A Simple Hysteretic Energy Harvesting Method for Nonneutral AC Switches in Load Automation

This paper presents a simple hysteretic method to obtain the energy required to operate the gate-drive, sensors, and other circuits within nonneutral ac switches intended for use in load automated buildings. The proposed method features a switch-mode low part-count self-powered MOSFET ac switch that achieves efficiency and load current THD figures comparable to those of an externally gate-driven switch built using similar MOSFETS. The fundamental operation of the method is explained in detail, followed by the modifications required for practical implementation. Certain design rules that allow the method to accommodate a wide range of single-phase loads from 10 VA to 1 kVA are discussed, along with an efficiency enhancement feature based on inherent MOSFET characteristics. The limitations and side effects of the method are also mentioned according to their levels of severity. Finally, experimental results obtained using a prototype sensor switch are presented, along with a performance comparison of the prototype with an externally gate-driven MOSFET switch.

Interface electronics for an RF resonance-based displacement sensor

6 p. Paper of the 17th Conference on Sensors and Their Applications held in Dubrovnik, Croatia. Sep 16-18, 2013

Planar reflection of gaseous detonations

Pipes containing flammable gaseous mixtures may be subjected to internal detonation. When the detonation normally impinges on a closed end, a reflected shock wave is created to bring the flow back to rest. This study built on the work of Karnesky (2010) and examined deformation of thin-walled stainless steel tubes subjected to internal reflected gaseous detonations. A ripple pattern was observed in the tube wall for certain fill pressures, and a criterion was developed that predicted when the ripple pattern would form. A two-dimensional finite element analysis was performed using Johnson-Cook material properties; the pressure loading created by reflected gaseous detonations was accounted for with a previously developed pressure model. The residual plastic strain between experiments and computations was in good agreement.

During the examination of detonation-driven deformation, discrepancies were discovered in our understanding of reflected gaseous detonation behavior. Previous models did not accurately describe the nature of the reflected shock wave, which motivated further experiments in a detonation tube with optical access. Pressure sensors and schlieren images were used to examine reflected shock behavior, and it was determined that the discrepancies were related to the reaction zone thickness extant behind the detonation front. During these experiments reflected shock bifurcation did not appear to occur, but the unfocused visualization system made certainty impossible. This prompted construction of a focused schlieren system that investigated possible shock wave-boundary layer interaction, and heat-flux gauges analyzed the boundary layer behind the detonation front. Using these data with an analytical boundary layer solution, it was determined that the strong thermal boundary layer present behind the detonation front inhibits the development of reflected shock wave bifurcation.

Selective data gathering in community sensor networks

Smartphones and other powerful sensor-equipped consumer devices make it possible to sense the physical world at an unprecedented scale. Nearly 2 million Android and iOS devices are activated every day, each carrying numerous sensors and a high-speed internet connection. Whereas traditional sensor networks have typically deployed a fixed number of devices to sense a particular phenomena, community networks can grow as additional participants choose to install apps and join the network. In principle, this allows networks of thousands or millions of sensors to be created quickly and at low cost. However, making reliable inferences about the world using so many community sensors involves several challenges, including scalability, data quality, mobility, and user privacy.

This thesis focuses on how learning at both the sensor- and network-level can provide scalable techniques for data collection and event detection. First, this thesis considers the abstract problem of distributed algorithms for data collection, and proposes a distributed, online approach to selecting which set of sensors should be queried. In addition to providing theoretical guarantees for submodular objective functions, the approach is also compatible with local rules or heuristics for detecting and transmitting potentially valuable observations. Next, the thesis presents a decentralized algorithm for spatial event detection, and describes its use detecting strong earthquakes within the Caltech Community Seismic Network. Despite the fact that strong earthquakes are rare and complex events, and that community sensors can be very noisy, our decentralized anomaly detection approach obtains theoretical guarantees for event detection performance while simultaneously limiting the rate of false alarms.

椭圆芯双模光纤干涉模斑中心间距的研究

通过弱波导近似的方法，讨论了椭圆芯双模光纤中沿光纤长轴的基模模斑半径Wx和短轴的基模模斑半径Wy尺寸，分析了它们的比值随入射光波长λ及纤芯半长轴与半短轴的比值a/b的变化规律。 针对基模LP01和第一高阶模LP11间的相位差变化，计算了双模干涉模斑的分布结构。计算结果表明，当基模LP01和第一高阶模LP11间的相位差为π/2时，两瓣干涉模斑有相同的结构特征。同时，两瓣模斑的中心间距S随Wx/Wy的的增加而变大。而且，当入射波长在0.65 μm和 1.31 μm之间变化时，结合两瓣模斑的中心间距S随Wx/Wy的变化规律，首次给出了S的计算公式。这对于实际应用如传感器和光纤耦合器件设计是很重要的。

Bihotz biriketako berpiztea simulatzeko panpin baten kudeaketarako tresna

[EU]Lan honen helburua, sentsorizatutako panpina kontrolatzeko software bat garatzea da, bihotz biriketako berpiztearen inguruko ikerkuntza sustatzeko helburuarekin. Kontrol hau aurrera eramateko bihotz biriketako berpiztearen inguruko kalitate parametro garrantzitsuenak jasotzen dituzten sentsoreekin hornitutako panpina bat erabili da, softwarearen eta panpinaren sentsoreen arteko interfaze gisa NI-DAQ National Instruments-eko txartela erabili delarik. Eskema honi jarraituz, software honek eskaintzen dituen funtzionalitate garrantzitsuenak hurrengoak dira: panpinaren bihotza simulatuko duen elektrokardiograma seinale bat panpinara transferitzea, sentsoreetatik lortutako informazioa biltegiratzea eta denbora errealean bistaratzea eta aurretiaz grabatutako erregistroen erreprodukzioa. Software hau garatzearen arrazoi nagusiak, bihotz biriketako berpiztearen kalitatea hobetzea eta elektrodoen eta pazientearen azalaren arteko kontaktuak elektrokardiograman sortzen duen interferentzia ezaugarritzea dira, bihotz-geldiunea pairatzen duen pazientearen bizi-iraupena handituko duten tresnen garapena sustatuz. Izan ere, bihotz-heriotza da herrialde garatuenen lehen heriotza-arrazoia.

Modeling habits as self-sustaining patterns of sensorimotor behavior

In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel "iterant deformable sensorimotor medium (IDSM)," designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor "meso-scale" between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition

Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements.

Value of information in product recovery decisions: A Bayesian approach

There is a widespread recognition of the need for better information sharing and provision to improve the viability of end-of-life (EOL) product recovery operations. The emergence of automated data capture and sharing technologies such as RFID, sensors and networked databases has enhanced the ability to make product information; available to recoverers, which will help them make better decisions regarding the choice of recovery option for EOL products. However, these technologies come with a cost attached to it, and hence the question 'what is its value?' is critical. This paper presents a probabilistic approach to model product recovery decisions and extends the concept of Bayes' factor for quantifying the impact of product information on the effectiveness of these decisions. Further, we provide a quantitative examination of the factors that influence the value of product information, this value depends on three factors: (i) penalties for Type I and Type II errors of judgement regarding product quality; (ii) prevalent uncertainty regarding product quality and (iii) the strength of the information to support/contradict the belief. Furthermore, we show that information is not valuable under all circumstances and derive conditions for achieving a positive value of information. © 2010 Taylor & Francis.