Chemical Communication in the Gregarious Psocid Cerastipsocus sivorii (Psocoptera: Psocidae)

The objectives of this study were: (1) to test the existence of an aggregation pheromone in the gregarious psocid Cerastipsocus sivorii; (2) to compare the attractiveness of odors from different aggregations; (3) to test whether nymphs are able to chemically recognize damage-released alarm signals. In a choice experiment conducted in the laboratory, we showed that psocids are able to detect chemical cues from groups of conspecifics. Laboratory experiments also showed that nymphs are capable of chemically recognizing the aggregations where they came from. Finally, in a field experiment, most aggregations dispersed when exposed to the body fluids of a crushed conspecific, but no aggregations dispersed upon exposure to a crushed termite. The implications of these results for the evolution of sociality in psocopterans are discussed.

Sistema de sensoriamento eletromagnético utilizado para detecção da contaminação do óleo isolante do motor no método de elevação artificial do tipo bombeio centrífugo submerso

In the artificial lift method by Electrical Submersible Pump (ESP), the energy is transmitted for the well´s deep through a flat electric handle, where it is converted into mechanical energy through an engine of sub-surface, which is connected to a centrifugal pump. This transmits energy to the fluid under the pressure form, bringing it to the surface In this method the subsurface equipment is basically divided into: pump, seal and motor. The main function of the seal is the protect the motor, avoiding the motor´s oil be contaminated by oil production and the consequent burning of it. Over time, the seal will be wearing and initiates a contamination of motor oil, causing it to lose its insulating characteristics. This work presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type Electrical Submersible Pump (ESP). The objective of this sensor is to generate alarm signal just the moment when the contamination in the isolated oil is present, enabling the implementation of a predictive maintenance. The prototype was designed to work in harsh conditions to reach a depth of 2000m and temperatures up to 150°C. It was used a simulator software to defined the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62HP motor showed a good reliability and fast response of the prototype.

Sistemi innovativi per il miglioramento della qualità e della sicurezza degli alimenti

Nell’attuale contesto, caratterizzato da un’elevata attenzione alla qualità e alla sicurezza degli alimenti e alle soluzioni tese a garantirli, l’implementazione di sistemi microelettronici per il controllo del prodotto attraverso supporti miniaturizzati e a basso costo può risultare un’opportunità strategica. Oggetto della ricerca di dottorato sono stati lo studio dell’utilizzo di sensori e strumentazione innovativi per la misurazione ed il controllo di parametri ambientali di conservazione di prodotti alimentari e per la loro identificazione mediante la tecnologia della radiofrequenza. Allo scopo è stato studiato il contesto in cui operano gli attori principali della filiera agroalimentare ed è stata sviluppata un’idea di etichetta progettata per essere in grado di emettere attivamente segnale di allarme in caso di necessità (etichetta RFID intelligente semi-passiva). Il prototipo di chip, realizzato in via sperimentale, è stato validato positivamente, sia come strumento di misura, sia in termini di prestazione nel caso studio del monitoraggio della conservazione di un prodotto alimentare in condizioni controllate di temperatura e radiazione luminosa. Le significative evidenze analitiche di reazioni di degradazione dello stato qualitativo del prodotto, quali analisi di pH e colore, raccolte durante il periodo di osservazione di 64 giorni, hanno trovato riscontro con le misure rilevate dal chip prototipo. I risultati invitano ad individuare un partner industriale, con il quale sperimentare l’applicazione della tecnologia proposta.

Sistema de sensoriamento eletromagnético utilizado para detecção da contaminação do óleo isolante do motor no método de elevação artificial do tipo bombeio centrífugo submerso

In the artificial lift method by Electrical Submersible Pump (ESP), the energy is transmitted for the well´s deep through a flat electric handle, where it is converted into mechanical energy through an engine of sub-surface, which is connected to a centrifugal pump. This transmits energy to the fluid under the pressure form, bringing it to the surface In this method the subsurface equipment is basically divided into: pump, seal and motor. The main function of the seal is the protect the motor, avoiding the motor´s oil be contaminated by oil production and the consequent burning of it. Over time, the seal will be wearing and initiates a contamination of motor oil, causing it to lose its insulating characteristics. This work presents a design of a magnetic sensor capable of detecting contamination of insulating oil used in the artificial lift method of oil-type Electrical Submersible Pump (ESP). The objective of this sensor is to generate alarm signal just the moment when the contamination in the isolated oil is present, enabling the implementation of a predictive maintenance. The prototype was designed to work in harsh conditions to reach a depth of 2000m and temperatures up to 150°C. It was used a simulator software to defined the mechanical and electromagnetic variables. Results of field experiments were performed to validate the prototype. The final results performed in an ESP system with a 62HP motor showed a good reliability and fast response of the prototype.

Design and performance analysis of a signal detector based on suprathreshold stochastic resonance

This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation sigma of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum sigma also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum sigma depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. (C) 2012 Elsevier B.V. All rights reserved.

Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array

This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

Mouse alarm pheromone shares structural similarity with predator scents.

Sensing the chemical warnings present in the environment is essential for species survival. In mammals, this form of danger communication occurs via the release of natural predator scents that can involuntarily warn the prey or by the production of alarm pheromones by the stressed prey alerting its conspecifics. Although we previously identified the olfactory Grueneberg ganglion as the sensory organ through which mammalian alarm pheromones signal a threatening situation, the chemical nature of these cues remains elusive. We here identify, through chemical analysis in combination with a series of physiological and behavioral tests, the chemical structure of a mouse alarm pheromone. To successfully recognize the volatile cues that signal danger, we based our selection on their activation of the mouse olfactory Grueneberg ganglion and the concomitant display of innate fear reactions. Interestingly, we found that the chemical structure of the identified mouse alarm pheromone has similar features as the sulfur-containing volatiles that are released by predating carnivores. Our findings thus not only reveal a chemical Leitmotiv that underlies signaling of fear, but also point to a double role for the olfactory Grueneberg ganglion in intraspecies as well as interspecies communication of danger.

Chemical communication in Apis mellifera: Temporal modulation of alarm behaviors

The effect of pheromones and their chemical analogues in honeybee alarm behaviors was studied in observation boxes. Defensive behaviors, as follows: a) attraction to scent source, b) elevation of wings in 'V', c) abdomen elevation, d) abdomen elevation and pumping and e) first leg pair elevation had been temporarily registered when the following compounds were presented: isoamyl alcohol, octyl alcohol, benzyl alcohol, n-butyl acetate, n-octyl acetate, isopentyl acetate, benzyl acetate and 2-heptanone. The results were as follows: 1. the bees elicited some characteristic behaviors when chemical alarm messages were presented, 2. agression (stinging) was not completed with any compound tested, probably because there was not a target (visual stimulus), 3. in all situations the attraction to scent source was low, 4. all the behaviors were elicited in a temporarily different way, 5. the compounds that elicited stronger responses and a greater number of the investigated behaviors were: isopentyl acetate, 2-heptanone, octyl acetate and n-octyl alcohol. In all situations, the first behavior response (and the most intense one) was the elevation and pumping the abdomen. This suggests that the chemical message was promptly recognized and then transmitted to each worker. So, the results obtained in the present work, suggest that chemical alarm messages may be recognized by different mechanisms of neural integration.

Sensitivity and Bias within the Binary Signal Detection Theory, BSDT

Similar to classic Signal Detection Theory (SDT), recent optimal Binary Signal Detection Theory (BSDT) and based on it Neural Network Assembly Memory Model (NNAMM) can successfully reproduce Receiver Operating Characteristic (ROC) curves although BSDT/NNAMM parameters (intensity of cue and neuron threshold) and classic SDT parameters (perception distance and response bias) are essentially different. In present work BSDT/NNAMM optimal likelihood and posterior probabilities are analytically analyzed and used to generate ROCs and modified (posterior) mROCs, optimal overall likelihood and posterior. It is shown that for the description of basic discrimination experiments in psychophysics within the BSDT a ‘neural space’ can be introduced where sensory stimuli as neural codes are represented and decision processes are defined, the BSDT’s isobias curves can simultaneously be interpreted as universal psychometric functions satisfying the Neyman-Pearson objective, the just noticeable difference (jnd) can be defined and interpreted as an atom of experience, and near-neutral values of biases are observers’ natural choice. The uniformity or no-priming hypotheses, concerning the ‘in-mind’ distribution of false-alarm probabilities during ROC or overall probability estimations, is introduced. The BSDT’s and classic SDT’s sensitivity, bias, their ROC and decision spaces are compared.

A novel signal processing method for intraoperative neurophysiological monitoring in spinal surgeries

Intraoperative neurophysiologic monitoring is an integral part of spinal surgeries and involves the recording of somatosensory evoked potentials (SSEP). However, clinical application of IONM still requires anywhere between 200 to 2000 trials to obtain an SSEP signal, which is excessive and introduces a significant delay during surgery to detect a possible neurological damage. The aim of this study is to develop a means to obtain the SSEP using a much less, twelve number of recordings. The preliminary step involved was to distinguish the SSEP with the ongoing brain activity. We first establish that the brain activity is indeed quasi-stationary whereas an SSEP is expected to be identical every time a trial is recorded. An algorithm was developed using Chebychev time windowing for preconditioning of SSEP trials to retain the morphological characteristics of somatosensory evoked potentials (SSEP). This preconditioning was followed by the application of a principal component analysis (PCA)-based algorithm utilizing quasi-stationarity of EEG on 12 preconditioned trials. A unique Walsh transform operation was then used to identify the position of the SSEP event. An alarm is raised when there is a 10% time in latency deviation and/or 50% peak-to-peak amplitude deviation, as per the clinical requirements. The algorithm shows consistency in the results in monitoring SSEP in up to 6-hour surgical procedures even under this significantly reduced number of trials. In this study, the analysis was performed on the data recorded in 29 patients undergoing surgery during which the posterior tibial nerve was stimulated and SSEP response was recorded from scalp. This method is shown empirically to be more clinically viable than present day approaches. In all 29 cases, the algorithm takes 4sec to extract an SSEP signal, as compared to conventional methods, which take several minutes. The monitoring process using the algorithm was successful and proved conclusive under the clinical constraints throughout the different surgical procedures with an accuracy of 91.5%. Higher accuracy and faster execution time, observed in the present study, in determining the SSEP signals provide a much improved and effective neurophysiological monitoring process.