Improvement in the removal of micropollutants at Porto Marghera industrial wastewaters treatment plant by MBR technology.

This paper deals with the case of one of the most important industrial application of membrane technology in the world: the upgrading of the main industrial wastewater treatment plant (WWTP) of the petrochemical site of Porto Marghera, Northern Italy, completed on December 2005 and tested on September 2006. It describes the principal interventions of the plant upgrading and it discusses the removal obtained during the test periods for conventional pollutants as well as for micropollutants. The plant upgrading consisted of a series of improvements of the existing industrial WWTP, in order to increase the removal efficiency of the total suspended solids and the associate removal of ten micropollutant compounds, the so called forbidden substances. The most important intervention was the conversion of the existing activated sludge section into a membrane biological reactor, in order to guarantee adherence to the severe limits imposed by the special law issued to protect the Venice Lagoon, with particular reference to the mentioned 10 forbidden compounds. The experimental results and the numerous test-runs conducted confirmed the respect of the legal limits for the pollutants in the final effluent as well of the required removal rates for the different parameters. Therefore, the upgraded treatment plant was declared agreeing with the approved design.

Frontal brain asymmetries as effective parameters to assess the quality of audiovisual stimuli perception in adult and young cochlear implant users.

How is music perceived by cochlear implant (CI) users? This question arises as "the next step" given the impressive performance obtained by these patients in language perception. Furthermore, how can music perception be evaluated beyond self-report rating, in order to obtain measurable data? To address this question, estimation of the frontal electroencephalographic (EEG) alpha activity imbalance, acquired through a 19-channel EEG cap, appears to be a suitable instrument to measure the approach/withdrawal (AW index) reaction to external stimuli. Specifically, a greater value of AW indicates an increased propensity to stimulus approach, and vice versa a lower one a tendency to withdraw from the stimulus. Additionally, due to prelingually and postlingually deafened pathology acquisition, children and adults, respectively, would probably differ in music perception. The aim of the present study was to investigate children and adult CI users, in unilateral (UCI) and bilateral (BCI) implantation conditions, during three experimental situations of music exposure (normal, distorted and mute). Additionally, a study of functional connectivity patterns within cerebral networks was performed to investigate functioning patterns in different experimental populations. As a general result, congruency among patterns between BCI patients and control (CTRL) subjects was seen, characterised by lowest values for the distorted condition (vs. normal and mute conditions) in the AW index and in the connectivity analysis. Additionally, the normal and distorted conditions were significantly different in CI and CTRL adults, and in CTRL children, but not in CI children. These results suggest a higher capacity of discrimination and approach motivation towards normal music in CTRL and BCI subjects, but not for UCI patients. Therefore, for perception of music CTRL and BCI participants appear more similar than UCI subjects, as estimated by measurable and not self-reported parameters.

Analysis of EEG variables to measure the affective dimensions of arousal and valence related to the vision of emotional pictures.

The present work aims to investigate the electroencephalographic (EEG) activity elicited by the observation of emotional pictures selected from the International Affective Picture System (IAPS) database. We analyzed the evoked activity within time intervals of increasing duration taking into account the related ratings of Valence and Arousal. The scalp statistical maps of Power Spectral Density (PSD), related to pictures with high valence, revealed an enhanced activity across frontal areas in the theta band and the involvement of fronto-parietal circuits in the alpha band. Difference in the processing of low and high arousing pictures, however, seems to be highly dependent on the valence dimension: for low valenced pictures, the difference in arousal was processed immediately after the observation of the picture, while for the high-valenced ones the processing took part in the second part of the observation. These results appear to be congruent with the literature, while the novelty of the current study is represented by the comparison of the activity elicited in different time windows by both the Arousal and Valence dimensions. It is possible, in this way, to observe how the processing of one variable influences the other, creating a dynamic description of the Valence-Arousal space.

Alpha EEG Frontal Asymmetries during Audiovisual Perception in Cochlear Implant Users. A Study with Bilateral and Unilateral Young Users.

OBJECTIVES: The aim of the present study is to investigate the variations of the electroencephalographic (EEG) alpha rhythm in order to measure the appreciation of bilateral and unilateral young cochlear implant users during the observation of a musical cartoon. The cartoon has been modified for the generation of three experimental conditions: one with the original audio, another one with a distorted sound and, finally, a mute version. METHODS: The EEG data have been recorded during the observation of the cartoons in the three experimental conditions. The frontal alpha EEG imbalance has been calculated as a measure of motivation and pleasantness to be compared across experimental populations and conditions. RESULTS: The EEG frontal imbalance of the alpha rhythm showed significant variations during the perception of the different cartoons. In particular, the pattern of activation of normal-hearing children is very similar to the one elicited by the bilateral implanted patients. On the other hand, results related to the unilateral subjects do not present significant variations of the imbalance index across the three cartoons. CONCLUSION: The presented results suggest that the unilateral patients could not appreciate the difference in the audio format as well as bilaterally implanted and normal hearing subjects. The frontal alpha EEG imbalance is a useful tool to detect the differences in the appreciation of audiovisual stimuli in cochlear implant patients.

An electroencephalographic Peak Density Function to detect memorization during the observation of TV commercials.

Nowadays, there is a growing interest in measuring the impact of advertisements through the estimation of cerebral reactions. Several techniques and methods are used and discussed in the consumer neuroscience. In such a context, the present paper provides a novel method to estimate the level of memorization occurred in subjects during the observation of TV commercials. In particular, the present work introduce the Peak Density Function (PDF) as an electroencephalographic (EEG) time-varying variable which is correlated with the cerebral events of memorization of TV commercials. The analysis has been performed on the EEG activity recorded on twenty healthy subjects during the exposition to several advertisements. After the EEG recordings, an interview has been performed to obtain the information about the memorized scenes for all the video clips watched by the subjects. Such information has been put in correlation with the occurrence of transient peaks of EEG synchronization in the theta band, by computing the PDF. The present results show that the increase of PDF is positively correlated, scene by scene, (R=0.46, p<;0.01) with the spontaneous recall of subjects. This technology could be of help for marketers to overcome the drawbacks of the standard marketing tools (e.g., interviews, focus groups) when analyzing the impact of advertisements.

The great beauty: a neuroaesthetic study by neuroelectric imaging during the observation of the real Michelangelo's Moses sculpture.

Recent studies have been showed as the perception of real or displayed masterpieces by ancient or modern painters generate stable neuroelectrical correlates in humans. In this study, we collected the neuroelectrical brain activity correlated with the observation of the real sculpture of Michelangelo's Moses within the church where it is actually installed in a group of healthy subjects. In addition to the cerebral activity also the heart rate (HR) and the galvanic skin response (GSR) were collected simultaneously, to assess the emotional engage of the investigated population. The Moses sculpture was observed by the group from three different point of views, each one revealing different details of the sculpture. In addition, in each location the light conditions related to the specific observation of the sculpture were explicitly changed. Results showed that cerebral activity of the subjects varied significantly across the three different views and for light condition against no light condition (p<;0.04). Furthermore, the emotional engage estimated on the whole population is higher for a point of observation in which the Mose's face is directed toward the eyes of the observers (p<;0.02). Finally, the cerebral appreciation of the investigated group was found maximum from a perspective in which all the details of the sculpture could be easily grab by the eyes. Results suggested how the perception of the sculpture depends critically by the point of view of the observers and how such point of view can produce separate emotional and cerebral responses.

Evaluation of the workload and drowsiness during car driving by using high resolution EEG activity and neurophysiologic indices.

Sleep deprivation and/or a high workload situation can adversely affect driving performance, decreasing a driver's capacity to respond effectively in dangerous situations. In this context, to provide useful feedback and alert signals in real time to the drivers physiological and brain activities have been increasingly investigated in literature. In this study, we analyze the increase of cerebral workload and the insurgence of drowsiness during car driving in a simulated environment by using high resolution electroencephalographic techniques (EEG) as well as neurophysiologic variables such as heart rate (HR) and eye blinks rate (EBR). The simulated drive tasks were modulated with five levels of increasing difficulty. A workload index was then generated by using the EEG signals and the related HR and EBR signals. Results suggest that the derived workload index is sensitive to the mental efforts of the driver during the different drive tasks performed. Such workload index was based on the estimation the variation of EEG power spectra in the theta band over prefrontal cortical areas and the variation of the EEG power spectra over the parietal cortical areas in alpha band. In addition, results suggested as HR increases during the execution of the difficult driving tasks while instead it decreases at the insurgence of the drowsiness. Finally, the results obtained showed as the EBR variable increases of its values when the insurgence of drowsiness in the driver occurs. The proposed workload index could be then used in a near future to assess on-line the mental state of the driver during a drive task.

The effect of normalization of Partial Directed Coherence on the statistical assessment of connectivity patterns: a simulation study.

Partial Directed Coherence (PDC) is a spectral multivariate estimator for effective connectivity, relying on the concept of Granger causality. Even if its original definition derived directly from information theory, two modifies were introduced in order to provide better physiological interpretations of the estimated networks: i) normalization of the estimator according to rows, ii) squared transformation. In the present paper we investigated the effect of PDC normalization on the performances achieved by applying the statistical validation process on investigated connectivity patterns under different conditions of Signal to Noise ratio (SNR) and amount of data available for the analysis. Results of the statistical analysis revealed an effect of PDC normalization only on the percentages of type I and type II errors occurred by using Shuffling procedure for the assessment of connectivity patterns. No effects of the PDC formulation resulted on the performances achieved during the validation process executed instead by means of Asymptotic Statistic approach. Moreover, the percentages of both false positives and false negatives committed by Asymptotic Statistic are always lower than those achieved by Shuffling procedure for each type of normalization.

Differences in the perceived music pleasantness between monolateral cochlear implanted and normal hearing children assessed by EEG.

The perception of the music in cochlear implanted (CI) patients is an important aspect of their quality of life. In fact, the pleasantness of the music perception by such CI patients can be analyzed through a particular analysis of EEG rhythms. Studies on healthy subjects show that exists a particular frontal asymmetry of the EEG alpha rhythm which can be correlated with pleasantness of the perceived stimuli (approach-withdrawal theory). In particular, here we describe differences between EEG activities estimated in the alpha frequency band for a monolateral CI group of children and a normal hearing one during the fruition of a musical cartoon. The results of the present analysis showed that the alpha EEG asymmetry patterns related to the normal hearing group refers to a higher pleasantness perception when compared to the cerebral activity of the monolateral CI patients. In fact, the present results support the statement that a monolateral CI group could perceive the music in a less pleasant way when compared to normal hearing children.

Neuroelectric brain imaging during a real visit of a fine arts gallery: a neuroaesthetic study of XVII century Dutch painters.

Neuroaesthetic is a scientific discipline founded more than a decade ago and it refers to the study of the neural bases of beauty perception in art. The aim of this paper is to investigate the neuroelectrical correlates of brain activity of the observation of real paintings showed in a national fine arts gallery (Scuderie del Quirinale) in Rome, Italy. In fact, the present study was designed to examine how motivational factors as indexed by EEG asymmetry over the prefrontal cortex (relative activity of the left and right hemispheres) could be related to the experience of viewing a series of figurative paintings. The fine arts gallery was visited by a group of 25 subjects during an exhibition of the XVII century Dutch painters. Results suggested a strict correlation of the estimated EEG asymmetry with the verbal pleasantness scores reported by the subjects (p<0,05) and an inverse correlation of the perceived pleasantness with the observed painting's surface dimensions (p<0,002).

Frontal EEG theta changes assess the training improvements of novices in flight simulation tasks.

The aim of the study is to analyze the variation of the EEG power spectra in theta band when a novice starts to learn a new task. In particular, the goal is to find out the differences from the beginning of the training to the session in which the performance level is good enough for considering him/her able to complete the task without any problems. While the novices were engaged in the flight simulation tasks we recorded the brain activity by using high resolution EEG techniques as well as neurophysiologic variables such as heart rate (HR) and eye blinks rate (EBR). Results show clear changes in the EEG power spectra in theta band over the frontal brain areas, either over the left, the midline and the right side, during the learning process of the task. These results are also supported by the autonomic signals of HR and EBR, by the performances' trends and by the questionnaires for the evaluation of the perceived workload level.

A new statistical approach for the extraction of adjacency matrix from effective connectivity networks.

Graph theory is a powerful mathematical tool recently introduced in neuroscience field for quantitatively describing the main properties of investigated connectivity networks. Despite the technical advancements provided in the last few years, further investigations are needed for overcoming actual limitations in the field. In fact, the absence of a common procedure currently applied for the extraction of the adjacency matrix from a connectivity pattern has been leading to low consistency and reliability of ghaph indexes among the investigated population. In this paper we proposed a new approach for adjacency matrix extraction based on a statistical threshold as valid alternative to empirical approaches, extensively used in Neuroscience field (i.e. fixing the edge density). In particular we performed a simulation study for investigating the effects of the two different extraction approaches on the topological properties of the investigated networks. In particular, the comparison was performed on two different datasets, one composed by uncorrelated random signals (null-model) and the other one by signals acquired on a mannequin head used as a phantom (EEG null-model). The results highlighted the importance to use a statistical threshold for the adjacency matrix extraction in order to describe the real existing topological properties of the investigated networks. The use of an empirical threshold led to an erroneous definition of small-world properties for the considered connectivity patterns.

An integrated system for monitoring the quality of sample transportation.

OBJECTIVES: Due to the consolidation of laboratory testing facilities, there is an increasing need for systems able to assure quality and safety in biological sample transportation, although little evidence on this aspect is available in literature. DESIGN AND METHODS: An integrated system for sample transportation, implemented and monitored over a five-year period by our team, consists of secondary and tertiary containers, a device for temperature and time recording, and a system manager allowing the acceptance or rejection of biological samples through the immediate visualization and validation of registered data. RESULTS: Data collected between 2009 and October 2011, after a preliminary phase for optimizing the temperature inside the containers, demonstrated the frequency of transportations at an acceptable temperature (<20 °C) had increased and that of transportations at an excessively high temperature (>25 °C) had decreased by ~80%. CONCLUSIONS: The integrated system and related operating instructions allow improvement in the quality of sample transportation over time.

EEG frontal asymmetry related to pleasantness of music perception in healthy children and cochlear implanted users.

Interestingly, the international debate about the quality of music fruition for cochlear implanted users does not take into account the hypothesis that bilateral users could perceive music in a more pleasant way with respect to monolateral users. In this scenario, the aim of the present study was to investigate if cerebral signs of pleasantness during music perception in healthy child are similar to those observed in monolateral and in bilateral cochlear implanted users. In fact, previous observations in literature on healthy subjects have indicated that variations of the frontal EEG alpha activity are correlated with the perceived pleasantness of the sensory stimulation received (approach-withdrawal theory). In particular, here we described differences between cortical activities estimated in the alpha frequency band for a healthy child and in patients having a monolateral or a bilateral cochlear implant during the fruition of a musical cartoon. The results of the present analysis showed that the alpha EEG asymmetry patterns observed in a healthy child and that of a bilateral cochlear implanted patient are congruent with the approach-withdrawal theory. Conversely, the scalp topographic distribution of EEG power spectra in the alpha band resulting from the monolateral cochlear user presents a different EEG pattern from the normal and bilateral implanted patients. Such differences could be explained at the light of the approach-withdrawal theory. In fact, the present findings support the hypothesis that a monolateral cochlear implanted user could perceive the music in a less pleasant way when compared to a healthy subject or to a bilateral cochlear user.

Towards the time varying estimation of complex brain connectivity networks by means of a General Linear Kalman Filter approach.

One of the main limitations of the brain functional connectivity estimation methods based on Autoregressive Modeling, like the Granger Causality family of estimators, is the hypothesis that only stationary signals can be included in the estimation process. This hypothesis precludes the analysis of transients which often contain important information about the neural processes of interest. On the other hand, previous techniques developed for overcoming this limitation are affected by problems linked to the dimension of the multivariate autoregressive model (MVAR), which prevents from analysing complex networks like those at the basis of most cognitive functions in the brain. The General Linear Kalman Filter (GLKF) approach to the estimation of adaptive MVARs was recently introduced to deal with a high number of time series (up to 60) in a full multivariate analysis. In this work we evaluated the performances of this new method in terms of estimation quality and adaptation speed, by means of a simulation study in which specific factors of interest were systematically varied in the signal generation to investigate their effect on the method performances. The method was then applied to high density EEG data related to an imaginative task. The results confirmed the possibility to use this approach to study complex connectivity networks in a full multivariate and adaptive fashion, thus opening the way to an effective estimation of complex brain connectivity networks.

How the statistical validation of functional connectivity patterns can prevent erroneous definition of small-world properties of a brain connectivity network.

The application of Graph Theory to the brain connectivity patterns obtained from the analysis of neuroelectrical signals has provided an important step to the interpretation and statistical analysis of such functional networks. The properties of a network are derived from the adjacency matrix describing a connectivity pattern obtained by one of the available functional connectivity methods. However, no common procedure is currently applied for extracting the adjacency matrix from a connectivity pattern. To understand how the topographical properties of a network inferred by means of graph indices can be affected by this procedure, we compared one of the methods extensively used in Neuroscience applications (i.e. fixing the edge density) with an approach based on the statistical validation of achieved connectivity patterns. The comparison was performed on the basis of simulated data and of signals acquired on a polystyrene head used as a phantom. The results showed (i) the importance of the assessing process in discarding the occurrence of spurious links and in the definition of the real topographical properties of the network, and (ii) a dependence of the small world properties obtained for the phantom networks from the spatial correlation of the neighboring electrodes.

Describing relevant indices from the resting state electrophysiological networks.

The "Default Mode Network" concept was defined, in fMRI field, as a consistent pattern, involving some regions of the brain, which is active during resting state activity and deactivates during attention demanding or goal-directed tasks. Several fMRI studies described its features also correlating the deactivations with the attentive load required for the task execution. Despite the efforts in EEG field, aiming at correlating the spectral features of EEG signals with DMN, an electrophysiological correlate of the DMN hasn't yet been found. In this study we used advanced techniques for functional connectivity estimation for describing the neuroelectrical properties of DMN. We analyzed the connectivity patterns elicited during the rest condition by 55 healthy subjects by means of Partial Directed Coherence. We extracted some graph indexes in order to describe the properties of the resting network in terms of local and global efficiencies, symmetries and influences between different regions of the scalp. Results highlighted the presence of a consistent network, elicited by more than 70% of analyzed population, involving mainly frontal and parietal regions. The properties of the resting network are uniform among the population and could be used for the construction of a normative database for the identification of pathological conditions.

Cortical activity and functional hyperconnectivity by simultaneous EEG recordings from interacting couples of professional pilots.

Controlling an aircraft during a flight is a compelling condition, which requires a strict and well coded interaction between the crew. The interaction level between the Captain and the First Officer changes during the flight, ranging from a maximum (during takeoff and landing, as well as in case of a failure of the instrumentation or other emergency situations) to a minimum during quiet mid-flight. In this study, our aim is to investigate the neural correlates of different kinds and levels of interaction between couples of professional crew members by means of the innovative technique called brain hyperscanning, i.e. the simultaneous recording of the hemodynamic or neuroelectrical activity of different human subjects involved in interaction tasks. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects, and, even more interestingly, of the functional links existing between the brain activities of the subjects interacting together. In this EEG hyperscanning study, different phases of a flight were reproduced in a professional flight simulator, which allowed, on one side, to reproduce the ecological setting of a real flight, and, on the other, to keep under control the different levels of interaction induced in the crew by means of systematic and simulated failures of the aircraft instrumentation. Results of the procedure of linear inverse estimation, together with functional hyperconnectivity estimated by means of Partial Directed Coherence, showed a dense network of connections between the activity in the two brains in the takeoff and landing phases, when the cooperation between the crew is maximal, while conversely no significant links were shown during the phases in which the activity of the two pilots was independent.

Assessment of mental fatigue during car driving by using high resolution EEG activity and neurophysiologic indices.

Driving tasks are vulnerable to the effects of sleep deprivation and mental fatigue, diminishing driver's ability to respond effectively to unusual or emergent situations. Physiological and brain activity analysis could help to understand how to provide useful feedback and alert signals to the drivers for avoiding car accidents. In this study we analyze the insurgence of mental fatigue or drowsiness during car driving in a simulated environment by using high resolution EEG techniques as well as neurophysiologic variables such as heart rate (HR) and eye blinks rate (EBR). Results suggest that it is possible to introduce a EEG-based cerebral workload index that it is sensitive to the mental efforts of the driver during drive tasks of different levels of difficulty. Workload index was based on the estimation of increase of EEG power spectra in the theta band over prefrontal areas and the simultaneous decrease of EEG power spectra over parietal areas in alpha band during difficult drive conditions. Such index could be used in a future to assess on-line the mental state of the driver during the drive task.

Subject identification through standard EEG signals during resting states.

In the present work, we used the brain electroencephalografic activity as an alternative means to identify individuals. 50 healthy subjects participated to the study and 56 EEG signals were recorded through a high-density cap during one minute of resting state either with eyes open and eyes closed. By computing the power spectrum density (PSD) on segments of 10 seconds, we obtained a feature vector of 40 points, notably the PSD values in the standard frequency range (1-40 Hz), for each EEG channel. By using a naive Bayes classifier and K-fold cross-validations, we observed high correct recognition rates (CRR) at the parieto-occipital electrodes (~78% during eyes open, ~89% during eyes closed). Notably, the eyes closed resting state elicited the highest CRRs at the occipital electrodes (92% O2, 91% O1), suggesting these biometric characteristics as the most suitable, among those investigated here, for identifying individuals.