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Biological aerosol in indoor environments, such as museums, libraries and archives, can represent a hazard both for artworks, due to the presence of microorganisms, and for the health of operators and visitors, due to their potential infectious, allergenic or toxic effects. The detection of microbial colonization of air and surfaces, based on morphological and molecular analysis, is of fundamental importance for a correct preventive conservation and sustainable fruition. The results of the monitoring on both manufacts (prints, drawings), showing alterations potentially related to biological systems (foxing) and on furniture (metal cabinets, shelves, boxes) have been performed in the Central Institute for Graphic Arts (Rome). Sampling on manufacts surfaces was carried out by two non-destructive and non-invasive techniques using nitrocellulose membranes and nylon membranes fragments. The goal was to settle two parameters: the Microbial Build-up (MB the total number of microorganisms accumulated on a surface in an unknown period of time prior to the sampling) and the Hourly Microbial Fallout (HMF the number of microorganisms that settle on a surface during one hour). The results for MB and HMF were expressed as cfu/square decimeter (dm2). Fungal and bacterial taxa were identified through molecular biology techniques. The qualitative and quantitative analysis of microbial contamination showed any risk for the conservation of graphic artworks examined. This investigation represents a contribution for assessing the microbial contamination of graphic collections kept in indoor environments, this work is part of a broader research project whose goal is the definition of standardized methods for preventive conservation of organic cultural heritage.

Cardiotocographic data provide physicians information about foetal development and permit to assess conditions such as foetal distress. An incorrect evaluation of the foetal status can be of course very dangerous. To improve interpretation of cardiotocographic recordings, great interest has been dedicated to foetal heart rate variability spectral analysis. It is worth reminding, however, that foetal heart rate is intrinsically an uneven series, so in order to produce an evenly sampled series a zero-order, linear or cubic spline interpolation can be employed. This is not suitable for frequency analyses because interpolation introduces alterations in the foetal heart rate power spectrum. In particular, interpolation process can produce alterations of the power spectral density that, for example, affects the estimation of the sympatho-vagal balance (computed as low-frequency/high-frequency ratio), which represents an important clinical parameter. In order to estimate the frequency spectrum alterations of the foetal heart rate variability signal due to interpolation and cardiotocographic storage rates, in this work, we simulated uneven foetal heart rate series with set characteristics, their evenly spaced versions (with different orders of interpolation and storage rates) and computed the sympatho-vagal balance values by power spectral density. For power spectral density estimation, we chose the Lomb method, as suggested by other authors to study the uneven heart rate series in adults. Summarising, the obtained results show that the evaluation of SVB values on the evenly spaced FHR series provides its overestimation due to the interpolation process and to the storage rate. However, cubic spline interpolation produces more robust and accurate results. © 2010 Elsevier Ltd. All rights reserved.

Congenital Nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations, and its pathogenesis is still unknown. The pathology is defined as “congenital” from the onset time of its arise which could be at birth or in the first months of life. Visual acuity in CN subjects is often diminished due to nystagmus continuous oscillations, mainly on the horizontal plane, which disturb image fixation on the retina. However, during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals) the image of a given target can still be stable, allowing a subject to reach a higher visual acuity. In CN subjects, visual acuity is usually assessed both using typical measurement techniques (e.g. Landolt C test) and with eye movement recording in different gaze positions. The offline study of eye movement recordings allows physicians to analyse nystagmus main features such as waveform shape, amplitude and frequency and to compute estimated visual acuity predictors. This analytical functions estimates the best corrected visual acuity using foveation time and foveation position variability, hence a reliable estimation of this two parameters is a fundamental factor in assessing visual acuity. This work aims to enhance the foveation time estimation in CN eye movement recording, computing a second order approximation of the slow phase components of nystag-mus oscillations. About 19 infrared-oculographic eye-movement recordings from 10 CN subjects were acquired and the visual acuity assessed with an acuity predictor was compared to the one measured in primary position. Results suggest that visual acuity measurements based on foveation time estimation obtained from interpolated data are closer to value obtained during Landolt C tests.

The aim of the study is to characterize the local muscles motion in individuals undergoing whole body mechanical stimulation. In this study we aim also to evaluate how subject positioning modifies vibration dumping, altering local mechanical stimulus. Vibrations were delivered to subjects by the use of a vibrating platform, while stimulation frequency was increased linearly from 15 to 60 Hz. Two different subject postures were here analysed. Platform and muscles motion were monitored using tiny MEMS accelerometers; a contra lateral analysis was also presented. Muscle motion analysis revealed typical displacement trajectories: motion components were found not to be purely sinusoidal neither in phase to each other. Results also revealed a mechanical resonant-like behaviour at some muscles, similar to a second-order system response. Resonance frequencies and dumping factors depended on subject and his positioning. Proper mechanical stimulation can maximize muscle spindle solicitation, which may produce a more effective muscle activation.

Congenital nystagmus is an ocular-motor disorder characterised by involuntary, conjugated and bilateral to and fro ocular oscillations. In this study a method to recognise automatically jerk waveform inside a congenital nystagmus recording and to compute foveation time and foveation position variability is presented. The recordings were performed with subjects looking at visual targets, presented in nine eye gaze positions; data were segmented into blocks corresponding to each gaze position. The nystagmus cycles were identified searching for local minima and maxima (SpEp sequence) in intervals centred on each slope change of the eye position signal (position criterion). The SpEp sequence was then refined using an adaptive threshold applied to the eye velocity signal; the outcome is a robust detection of each slow phase start point, fundamental to accurately compute some nystagmus parameters. A total of 1206 slow phases was used to compute the specificity in waveform recognition applying only the position criterion or adding the adaptive threshold; results showed an increase in negative predictive value of 25.1% using both features. The duration of each foveation window was measured on raw data or using an interpolating function of the congenital nystagmus slow phases; foveation time estimation less sensitive to noise was obtained in the second case.

Whole body vibration (WBV) aims to mechanically activate muscles by eliciting stretch reflexes. Mechanical vibrations are usually transmitted to the patient body standing on a oscillating plate. WBV is now more and more utilized not only for fitness but also in physical therapy, rehabilitation and in sport medicine. Effects depend on intensity, direction and frequency of vibration; however, the training frequency is one of the most important factors involved. A preliminary vibratory session can be dedicated to find the best vibration frequency for each subject by varying, stepwise, the stimulation frequency and analyzing the resulting EMG activity. This study concentrates on the analysis of muscle motion in response to a vibration frequency sweep, while subjects held two different postures. The frequency of a vibrating platform was increased linearly from 10 to 60 Hz in 26 s, while platform and single muscles (Rectus Femoris, Biceps Femoris – long head and Gastrocnemius Lateralis) motions were monitored using tiny, lightweight three-axial MEMS accelerometers. Displacements were estimated integrating twice the acceleration data after gravity contribution removal. Mechanical frequency response (amplitude and phase) of the mechanical chains ending at the single muscles was characterized. Results revealed a mechanical resonant-like behavior at some muscles, very similar to a second-order system in the frequency interval explored; resonance frequencies and dumping factors depended on subject and its positioning onto the vibrating platform. Stimulation at the resonant frequency maximizes muscle lengthening, and in turn muscle spindle solicitation, which produce muscle activation.

Cardiotocographic data provide physicians information about foetal development and, through assessment of specific parameters (like accelerations, uterine contractions, ...), permit to assess conditions such as foetal distress. An incorrect evaluation of foetal status can be of course very dangerous. In the last decades, to improve interpretation of cardiotocographic recordings, great interest has been dedicated to FHRV spectral analysis. It is worth reminding that FHR is intrinsically an uneven series and that to obtain evenly sampled series, many commercial cardiotocographs use a zero-order interpolation (storage rate of CTG data equal to 4 Hz). This is not suitable for frequency analyses because interpolation introduces alterations in the FHR power spectrum. In particular, this interpolation process can produce artifacts and an attenuation of the high-frequency components of the PSD that, for example, affects the estimation of the sympatho-vagal balance (SVB - computed as low-frequency/high-frequency ratio), which represents an important clinical parameter. In order to estimate the frequency spectrum alterations due to zero-order interpolation and other CTG storage rates, in this work, we simulated uneven FHR series with set characteristics, their evenly spaced versions (with different storage rates) and computed SVB values by PSD. For PSD estimation, we chose the Lomb method, as suggested by other authors in application to uneven HR series

The aim of this study is to highlight the relation between muscle motion and electromyographyc activity during whole body vibration. This treatment is accounted for eliciting a reflex muscle activity in response to vibratory stimulation. Simultaneous recordings from quadriceps Rectus Femoris EMG and 3D muscle accelerations on fifteen subjects undergoing vibration treatments were collected. In our study vibrations were delivered via a sinusoidal oscillating platform at different frequencies (10-45 Hz), with a constant amplitude. Muscle motion was estimated by processing accelerometer data. Displacements revealed a mechanical resonant-like behaviour of the muscle; resonance frequencies and dumping factors depended on subject. Large EMG motion artifacts were removed using sharp notch filters centred at the vibration frequency and its superior harmonics. RMS values of artifact-free EMG were found correlated to the actual muscle displacement. The results were in accordance to the hypothesis of a proprioceptive response during vibration treatment. Nevertheless, motion artifacts produced an overestimation of muscle activity, therefore its removal was essential. © 2009 Springer Berlin Heidelberg.

A valuable alternative to US cardiotocography, for fetal surveillance, can be offered by phonocardiography, a passive and low cost acoustic recording of fetal heart sounds. A crucial point is the exact recognizing of the fetal heart sounds, associated to each fetal heart beat, and then the estimation of FHR signal. In this work, software for FHR assessment from phonocardiographic signals was developed. To check the reliability of the software, obtained results were compared with those of simultaneously recorded cardiotocographic signals. Results seemed to be satisfying, as provided FHR series were almost all confined within FHR-CTG +/- 3 bpm, where FHR-CTG were FHR series provided by commercial US cardiotocographic devices, currently employed in clinical routine.

Congenital nystagmus is an ocular-motor disorder that develops in the first few months of life; its pathogenesis is still unknown. Patients affected by congenital nystagmus show continuous, involuntary, rhythmical oscillations of the eyes. Monitoring eye movements, nystagmus main features such as shape, amplitude and frequency, can be extracted and analysed. Previous studies highlighted, in some cases, a much slower and smaller oscillation, which appears added up to the ordinary nystagmus waveform. This sort of baseline oscillation, or slow nystagmus, hinder precise cycle-to-cycle image placement onto the fovea. Such variability of the position may reduce patient visual acuity. This study aims to analyse more extensively eye movements recording including the baseline oscillation and investigate possible relationships between these slow oscillations and nystagmus. Almost 100 eye movement recordings (either infrared-oculographic or electrooculographic), relative to different gaze positions, belonging to 32 congenital nystagmus patients were analysed. The baseline oscillation was assumed sinusoidal; its amplitude and frequency were computed and compared with those of the nystagmus by means of a linear regression analysis. The results showed that baseline oscillations were characterised by an average frequency of 0.36 Hz (SD 0.11 Hz) and an average amplitude of 2.1° (SD 1.6°). It also resulted in a considerable correlation (R2 scored 0.78) between nystagmus amplitude and baseline oscillation amplitude; the latter, on average, resulted to be about one-half of the correspondent nystagmus amplitude.

Congenital nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations and its pathogenesis is still under investigation. This kind of nystagmus is termed congenital (or infantile) since it could be present at birth or it can arise in the first months of life. Most of CN patients show a considerable decrease of their visual acuity: image fixation on the retina is disturbed by nystagmus continuous oscillations, mainly horizontal. However, the image of a given target can still be stable during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals). To quantify the extent of nystagmus, eye movement recording are routinely employed, allowing physicians to extract and analyse nystagmus main features such as waveform shape, amplitude and frequency. Using eye movement recording, it is also possible to compute estimated visual acuity predictors: analytical functions which estimates expected visual acuity using signal features such as foveation time and foveation position variability. Use of those functions extend the information from typical visual acuity measurement (e.g. Landolt C test) and could be a support for therapy planning or monitoring. This study focuses on detection of CN patients' waveform type and on foveation time measure. Specifically, it proposes a robust method to recognize cycles corresponding to the specific CN waveform in the eye movement pattern and, for those cycles, evaluate the exact signal tracts in which a subject foveates. About 40 eyemovement recordings, either infrared-oculographic or electrooculographic, were acquired from 16 CN subjects. Results suggest that the use of an adaptive threshold applied to the eye velocity signal could improve the estimation of slow phase start point. This can enhance foveation time computing and reduce influence of repositioning saccades and data noise on the waveform type identification.

Congenital nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations, that can arise since the first months of life. Pathogenesis of congenital nystagmus is still under investigation. In general, CN patients show a considerable decrease of their visual acuity: image fixation on the retina is disturbed by nystagmus continuous oscillations, mainly horizontal. However, image stabilisation is still achieved during the short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals). To quantify the extent of nystagmus, eye movement recording are routinely employed, allowing physicians to extract and analyse nystagmus main features such as shape, amplitude and frequency. Using eye movement recording, it is also possible to compute estimated visual acuity predictors: analytical functions which estimates expected visual acuity using signal features such as foveation time and foveation position variability. Use of those functions add information to typical visual acuity measurement (e.g. Landolt C test) and could be a support for therapy planning or monitoring. This study focus on robust detection of CN patients' foveations. Specifically, it proposes a method to recognize the exact signal tracts in which a subject foveates, This paper also analyses foveation sequences. About 50 eyemovement recordings, either infrared-oculographic or electrooculographic, from different CN subjects were acquired. Results suggest that an exponential interpolation for the slow phases of nystagmus could improve foveation time computing and reduce influence of breaking saccades and data noise. Moreover a concise description of foveation sequence variability can be achieved using non-fitting splines. © 2009 Springer Berlin Heidelberg.

Vibration treatment by oscillating platforms is more and more employed in the fields of exercise physiology and bone research. The rationale of this treatment is based on the neuromuscular system response elicited by vibration loads. surface Electromyography (EMG) is largely utilized to assess muscular response elicited by vibrations and Root Mean Square of the electromyography signals is often used as a concise quantitative index of muscle activity; in general, EMG envelope or RMS is expected to increase during vibration. However, it is well known that during surface bio-potential recording, motion artifacts may arise from relative motion between electrodes and skin and between skin layers. Also the only skin stretch, modifying the internal charge distribution, results in a variation of electrode potential. The aim of this study is to highlight the movements of muscles, and the succeeding relevance of motion artifacts on electrodes, in subjects undergoing vibration treatments. EMGs from quadriceps of fifteen subjects were recorded during vibration at different frequencies (15-40 Hz); Triaxial accelerometers were placed onto quadriceps, as close as possible to muscle belly, to monitor motion. The computed muscle belly displacements showed a peculiar behavior reflecting the mechanical properties of the structures involved. Motion artifact related to the impressed vibration have been recognized and related to movement of the soft tissues. In fact large artifacts are visible on EMGs and patellar electrodes recordings during vibration. Signals spectra also revealed sharp peaks corresponding to vibration frequency and its harmonics, in accordance with accelerometers data. © 2008 Springer-Verlag.

Congenital nystagmus (CN) is an ocular-motor disorder that appears at birth or during the first few months of life; it is characterised by involuntary, conjugated, bilateral to and fro ocular oscillations mainly horizontal. Pathogenesis of congenital nystagmus is still unknown. In general, CN patients show a considerable decrease of the visual acuity: image fixation on the retina is disturbed by nystagmus continuous oscillations; however, image stabilisation is still achieved during the short periods in which eye velocity slows down while the target image is placed onto the fovea (foveation intervals) [1]. To quantify extent of nystagmus, eye movement recording are routinely employed, allowing physicians to extract and analyse nystagmus main features such as shape, amplitude and frequency. Eye movement recording study leads to the computation of estimated visual acuity predictors; their use could integrate usual visual acuity measurement, such as Landolt C test, and could be a support for therapy planning or monitoring [2,3,4]. This study concentrates on identification of the foveation in CN eye-movement recordings, and proposes a method to recognize signal tracts in which a subject foveates, that is the time in which eye position is confined within ±0.5 degree from the local foveation point, while velocity is lower than 4 degree/s (the so called foveation window).

Congenital nystagmus (CN) is an ocular-motor disorder that appears at birth or during the first few months of life; it is characterised by involuntary, conjugated, bilateral to and fro ocular oscillations. Pathogenesis of congenital nystagmus is still unknown. Eye movement recording allow to extract and analyse nystagmus main features such as shape, amplitude and frequency; depending on the morphology of the oscillations nystagmus can be classified in different categories (pendular, jerk, horizontal unidirectional, bidirectional). In general, CN patient show a considerable decrease of the visual acuity: image fixation on the retina is disturbed by nystagmus continuous oscillations; however, image stabilisation is still achieved during the short foveation periods in which eye velocity slows down while the target image is placed onto the fovea. Visual acuity was found to be mainly dependent on foveation periods duration, but cycle-to-cycle foveation repeatability and reduction of retinal image velocities also contribute in increasing visual acuity. This study concentrate on cycle-to-cycle image position variation onto fovea, trying to characterise the sequences of foveation positions. Eye-movement (infrared oculographic or electro oculographic) recordings, relative to different gaze positions and belonging to more than 30 CN patients, were analysed. Preliminary results suggest that sequences of foveations show a cyclic pattern with a dominant frequency (around 0.3 Hz on average) much lower than that of the nystagmus (about 3.3 Hz on average). Sequences of foveations reveals an horizontal ocular swing of more than 2 degree on average, which can explain the low visual acuity of the CN patient. Current CN therapies, pharmacological treatment or surgery of the ocular muscles, mainly aim to increase the patient's visual acuity. Hence, it is fundamental to have an objective parameter (expected visual acuity) for therapy planning. The information about sequences of foveations can improve estimation of patient visual acuity.

Event landside inventory maps can be prepared using conventional or new mapping methods. Conventional methods, including field mapping and the visual interpretation of stereoscopic aerial photographs, are time consuming and resource intensive, restricting the ability to prepare event inventory maps rapidly, repeatedly, and for large and very large areas. This is a significant drawback for regional landslide studies and post event remedial efforts. Investigators are currently experimenting new methods for preparing landslide event inventories exploiting remotely sensed data, including qualitative (visual) and quantitative (numerical) analysis of very-high resolution (VHR) digital elevation models obtained chiefly through LiDAR surveys, and the interpretation and analysis of satellite images, including panchromatic, multispectral, and synthetic aperture radar images. We devised a stepwise, semi-automatic approach to detect, map, and classify internally rainfall-induced shallow landslides exploiting multispectral satellite images taken shortly after a landslide-triggering event, and information on the topographic signature of landslides obtained from a pre-event digital elevation model. In a Bayesian framework, the approach combines a standard image classification obtained by a supervised classifier (e.g., the Mahalanobis Distance classifier) applied to a post-event image, with information on the morphometric landslide signature measured by statistics of terrain slope and cross section convexity in landslide and stable areas. The semi-automatic approach is applied in two steps. First, the rainfall-induced landslides are detected and mapped, separating them from the stable areas. Next, the mapped landslides are classified internally, separating the source from the run out areas. We have applied the approach in a 117 km2 study area in Taiwan, where shallow landslides triggered by high intensity rainfall brought by typhoon Morakot in august 2009 were abundant. Comparison in a GIS of the event landslide inventory produced by the proposed semi-automatic method with a similar event inventory obtained through the visual interpretation of post-event ortho-photographs reveals a degree of matching > 90%. The new approach is flexible, it can exploit different satellite imagery and terrain elevation data, and can be used to map and classify landslides caused by various triggers in different physiographical environments. We expect our new method to contribute to the production of event landslide inventory maps

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Air pollution, caused by fuel industries and urban traffic and its environmental impact, are of considerable interest to studies in air quality. In this paper, the monitoring of the air pollution over urban areas in Italy through Aerosol Optical Thickness (AOT) data retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements is presented. The high spatio-temporal frequency of MODIS AOT products (twice per day at 470nm, 1km full resolution) demonstrates that this satellite can be potentially used to routinely monitor the air pollution over land, especially urban area, which is the main source of aerosol particles. In this work AOT data derived by MODIS from November 2010 to February 2011 (winter period) and from May 2011 to August 2011 (summer period) were compared with AOT measurements from 6 different Aerosol Robotic Network (AERONET) stations over Italy (Bari, Lecce, Roma, Ispra, Potenza, Etna). The statistical analysis shows a good agreement between the ground based AOT measurements and the values retrieved using space based sensors, as shown in Figure 1. For all the stations the mean error is negligible, with a correlation ranging from 0.725 (in the worst case) to 0.96 (see Table 1). Moreover, LANDSAT-panchromatic images were used to discriminate urban and rural areas, based on the typical finger-like projections of urban land uses. The results of this study will be presented and commented.

— Long term recording of biomedical signals such as ECG, EMG, respiration and other information (e.g. body motion) can improve diagnosis and potentially monitor the evolution of many widespread diseases. However, long term monitoring requires specific solutions, portable and wearable equipment that should be particularly comfortable for patients. The key-issues of portable biomedical instrumentation are: power consumption, long-term sensor stability, comfortable wearing and wireless connectivity. In this scenario, it would be valuable to realize prototypes using available technologies to assess long-term personal monitoring and foster new ways to provide healthcare services. The aim of this work is to discuss the advantages and the drawbacks in long term monitoring of biopotentials and body movements using textile electrodes embedded in clothes. The textile electrodes were embedded into garments; tiny shirt and short were used to acquire electrocardiographic and electromyographic signals. The garment was equipped with low power electronics for signal acquisition and data wireless transmission via Bluetooth. A small, battery powered, biopotential amplifier and three-axes acceleration body monitor was realized. Patient monitor incorporates a microcontroller, analog-to-digital signal conversion at programmable sampling frequencies. The system was able to acquire and to transmit realtime signals, within 10 m range, to any Bluetooth device (including PDA or cellular phone). The electronics were embedded in the shirt resulting comfortable to wear for patients. Small size MEMS 3-axes accelerometers were also integrated.

Auscultation and observation of foetal heart rate (FHR), through various techniques, has always been of crucial importance to ascertain life and well-being of the foetus. Gynaecologists evaluate several characteristics of FHR signal, but foetal heart rate variability (FHRV) is probably the most important feature of the FHR recording, due to its relationship to the autonomic and central nervous systems, as demonstrated by pharmacological experiments in both foetal sheep and adult humans [1]. However, there is a high inter and intra-observer variability [2] in the interpretation of FHR signals and there are no clear standards for the definition and evaluation of FHR changes. This is particularly true when assessing beat-to-beat variability of the heart rate [1, 3, 4]. In frequency domain, as well as adults, most of literature [1, 5, 6] agrees that three bands can be detected in the FHR power spectrum, a very low frequency band (VLF), a low frequency band (LF) and a high frequency band (HF). However, despite to the spread use of FHRV spectral analysis [7, 8, 9, 10], there is not agreement in definition of its components. Some researcher groups, for example, identify the VLF with the range [0 ??? 0.03] Hz [6], while other authors consider as VLF the range [0 ??? 0.04] Hz [11] or [0 ??? 0.05]Hz [1]. Moreover, some authors introduce also a medium frequency band (MF), corresponding to maternal respiration [12]. Besides, differently from what happens in the adult, there are modifications of the baseline, accelerations and decelerations, which make more difficult or even impossible FHRV definition and identification. Some guidelines in fact state that variability refers to fluctuations in the baseline free from accelerations and decelerations [13]. This is an important limit in clinical routine since variability in correspondence of these FHR alterations has always been regarded as particularly significant in terms of prognostic value [14, 15]. Aim of this work was to propose the computation of FHRV signal as difference between FHR and floatingline, which is an imaginary median line of FHR signal [16, 17] and that hence includes accelerations and decelerations. Further, we characterised floatingline in frequency domain, and, to this purpose, a characterisation of accelerations and decelerations has been necessary, being the literature very poor at this regard. Finally, a procedure to estimate floatingline in time domain was proposed.

L'osservazione della Terra da piattaforme spaziali, integrata con misure in situ e con acquisizione da piattaforme aeree, è una tecnologia di riferimento per il monitoraggio di ampie zone del Territorio con una elevata frequenza spaziale. Queste ca-ratteristiche sono essenziali per investigare, da un lato, l'effetto di modifiche indotte da cambiamenti climatici, dall'altro la presenza di situazioni che siano precursori di cambiamenti, in un'ottica di previsione ed allerta. Nel presente lavoro vengono presentati alcuni esempi applicativi in questo scenario.

Reliable land cover mapping of agricultural areas require high resolution remote sensing and robust classification techniques. In this paper, we propose the integration of spectral information with spatial information using the traditional statistical supervised classifier “Maximum Likelihood” and a geostatistical tool, “Indicator Kriging” algorithm, for the development of land cover maps by supervised classification from remotely sensed data at medium and high spatial resolution. The proposed method showed better results in classes’ discrimination with smoother resulting maps than the ones produced using only spectral information. Two different satellites imagery were analyzed: a Landsat TM5 image at medium spatial resolution acquired during 2006 and an Ikonos II image at higher spatial resolution acquired during 2008. The better performance of the “combined” approach compared to the traditional Maximum Likelihood technique was confirmed by confusion matrix. The overall accuracy increases from 76.16% to 85.96% for LandsatTM image and from 71.56% to 80.25% for the IKONOS image.

A classification system able to evaluate the performances of a transition radiation detector prototype for electrons/hadrons discrimination is presented. It is based both on a layered feed-forward neural network trained using back-propagation and a likehood ratio technique. The information fed into the classification system consists of the number of hits detected by each multiwires proportional chamber of the detector. The best results are obtained by the neural network approach that successfully identifies 4.0 GeV/ c electrons with an hadron contamination of about 4x10 -3 at 98% acceptance efficiency.

This study extends a previous research concerning intervertebral motion registration by means of 2D dynamic fluoroscopy to obtain a more comprehensive 3D description of vertebral kinematics. The problem of estimating the 3D rigid pose of a CT volume of a vertebra from its 2D X-ray fluoroscopy projection is addressed. 2D-3D registration is obtained maximising a measure of similarity between Digitally Reconstructed Radiographs (obtained from the CT volume) and real fluoroscopic projection. X-ray energy correction was performed. To assess the method a calibration model was realised a sheep dry vertebra was rigidly fixed to a frame of reference including metallic markers. Accurate measurement of 3D orientation was obtained via single-camera calibration of the markers and held as true 3D vertebra position; then, vertebra 3D pose was estimated and results compared. Error analysis revealed accuracy of the order of 0.1 degree for the rotation angles of about 1 mm for displacements parallel to the fluoroscopic plane, and of order of 10 mm for the orthogonal displacement.

Analysis of dynamic videofluoroscopic can provide spine kinematic data with an acceptable low X-ray dose. Estimation of the kinematics relies on accurate recognition of vertebrae positions and rotations on each radiological frame. In previous works we presented a procedure for automatic tracking of vertebra motion by smoothed gradient operators and template matching in fluoroscopic image sequences. A limitation to the accurate estimation of the kinematics by automatic tracking of vertebrae motion, independently by the specific methodology employed (e.g. manual marking, corner or edge automatic detection, etc.), is mainly due to noise: low-dose X-ray image sequences exhibit severe signal-dependent noise that should be reduced, while preserving anatomical edges and structures. Noise in low-dose X-ray images originates from various sources, however quantum noise is by far the more dominant noise in low-dose X-ray images and other sources can be neglected. Signal degraded by quantum noise is commonly modeled by a Poisson distribution, but it is possible to approximate it as additive zero-mean Gaussian noise with signal-dependent variance. In this work we propose a digital spatial filter for reducing noise in low-dose X-ray images. The proposed filter is based on averaging of only similar pixels (whose grey level is contained within ±3σ) instead of spatial averaging of all neighbouring pixels. The effectiveness of the filter performance was evaluated by fluoroscopic image sequence processing, comparing the results of the automatic vertebra tracking on filtered and unfiltered images.

Monitoring foetal health is important to appropriately plan pregnancy management and delivery. Cardiotocography (CTG) is one of the most employed diagnostic techniques. Because CTG interpretation still lacks of complete reliability, new methods of interpretation and parameters are necessary to further support physicians’ decisions. To this aim, indexes related to variability of foetal heart rate (FHRV) are particularly studied. Frequency components of FHRV and their modifications can be analysed by applying a time-frequency approach, which allows for a distinct understanding of the spectral components related to foetal reactions to internal and external stimuli and their change over time. Being uterine contractions (UC) strong stimuli for the foetus and his autonomic nervous system (ANS), it is worth exploring the FHRV response to UC. This study analysed modifications of FHRV frequency characteristics with respect to 108 UC (relative to 35 healthy foetuses). Results showed a statistically significant (t-test, p < 0.01) power increase of the FHRV in both LF and HF bands in correspondence of the contractions. Moreover, we observed a shift to higher values of the maximum frequency contained in the signal corresponding to the power increase. Such modifications of the FHRV power spectrum can be a sign of ANS reaction and therefore represent additional, objective information about foetal reactivity and health during labour.

We consider fully connected neural networks near saturation, trained by a modified Edinburgh algorithm, with sign constraints on the synaptic couplings. We study the domains of attraction of the stored patterns for both the balanced and the unbalanced case (excess of positive over negative constraints). A comparison with the dilute network is also included.

We investigate the retrieval properties of fully connected saturated neural networks trained by the Edinburgh algorithm with correlated patterns {ξi}. We evaluate the effect of the correlation on the overlap between {ξi} and the network configuration after one time step and on the basins of attraction. We also show that the introduction of the thermal noise does not change the domains of attraction of the correlated memories.

In the context of the use of remote sensed data for monitoring land cover it is very important to develop methodologies to obtain reliable maps. In order to achieve this objective a possible approach is to combine both "spectral" and "spatial" features to characterizing each ground class. In this paper we propose the integration of a spectral classifier for remote sensed data at medium resolution, based on a traditional statistical supervised classifier as "Maximum Likelihood", with the spatial information provided by a geostatistical tool, as "Indicator Kriging" algorithm. Using this combined approach, better results in land cover class discrimination have been obtained and the resulting maps look more homogenous than in the case with the spectral information only.