The biofragmentable anastomosis ring in elective colon resections.

Methods. Sixty-eight patients underwent elective colon resection and ìntraperitoneal anastomosis wìth thè biofragmentable anastomosis ring (BAR). Results. Anastomotic dehiscence occurred in 3 patients (4.4%). Two of them had an end-to-end ileocolostomy using a 31 mm BAR. The anastomosis failure was due to ischaemic lesion of thè small bowel dose to thè ileocolostomy, probably caused by a mismatch between thè size of small bowel and that of thè BAR. Another patient experienced anastomosis dehiscence probably due to a faecal impaction into thè BAR. Forty-eight patients (70.5%) experienced troublesome constipation and evacuated after thè sixth postoperative day. A bowel obstruction proximal to thè BAR was documented in 4 cases who have been treated conservatively. Condmions. The low rate of major complications justify thè use of thè BAR in elective colon surgery, but thè surgeon must be aware of tedious postoperative obstructive episodes frequently encountered in this series

Mutations in the SPAST gene causing hereditary spastic paraplegia arerelated to global topological alterations in brain functional networks

Aim: Our aim was to describe the rearrangements of the brain activity related to genetic mutations in the SPAST gene. Methods: Ten SPG4 patients and ten controls underwent a 5 min resting state magnetoencephalography recording and neurological examination. A beamformer algorithm reconstructed the activity of 90 brain areas. The phase lag index was used to estimate synchrony between brain areas. The minimum spanning tree was used to estimate topological metrics such as the leaf fraction (a measure of network integration) and the degree divergence (a measure of the resilience of the network against pathological events). The betweenness centrality (a measure to estimate the centrality of the brain areas) was used to estimate the centrality of each brain area. Results: Our results showed topological rearrangements in the beta band. Specifically, the degree divergence was lower in patients as compared to controls and this parameter related to clinical disability. No differences appeared in leaf fraction nor in betweenness centrality. Conclusion: Mutations in the SPAST gene are related to a reorganization of the brain topology

Probing background ionization: Positive streamers with varying pulse repetition rate and with a radioactive admixture

Positive streamers need a source of free electrons ahead of them to propagate. A streamer can supply these electrons by itself through photo-ionization, or the electrons can be present due to external background ionization. Here we investigate the effects of background ionization on streamer propagation and morphology by changing the gas composition and the repetition rate of the voltage pulses, and by adding a small amount of radioactive Krypton 85. We find that the general morphology of a positive streamer discharge in high purity nitrogen depends on background ionization: at lower background ionization levels the streamers branch more and have a more feather-like appearance. This is observed both when varying the repetition rate and when adding Krypton 85, though side branches are longer with the radioactive admixture. But velocities and minimal diameters of streamers are virtually independent of the background ionization level. In air, the inception cloud breaks up into streamers at a smaller radius when the repetition rate and therefore the background ionization level is higher. When measuring the effects of the pulse repetition rate and of the radioactive admixture on the discharge morphology, we found that our estimates of background ionization levels are consistent with these observations; this gives confidence in the estimates. Streamer channels generally do not follow the paths of previous discharge channels for repetition rates of up to 10 Hz. We estimate the effect of recombination and diffusion of ions and free electrons from the previous discharge and conclude that the old trail has largely disappeared at the moment of the next voltage pulse; therefore the next streamers indeed cannot follow the old trail.Comment: 30 pages, 13 figure

Unsupervised Coastal Line Extraction From SAR Images

Historically, the extraction of coastal line has been performed exploiting optical images, but in the last two decades, some approaches working with synthetic aperture radar (SAR) data have been proposed. Recently, these approaches have been gaining interest due to the availability of high-resolution SAR images. In this letter, a technique for coastal line retrieval from multichannel SAR images is presented. The detection problem is faced in the statistical estimation framework, in particular, exploiting Bayesian estimation theory. The proposed technique is able to detect sea boundaries at full resolution and low error rate in a totally unsupervised way. The performance of the method has been tested using high-resolution COSMO-SkyMed data sets acquired on the Bay of Naples, showing the high accuracy of the proposed technique

Statistical Edge Detection in Urban Areas Exploiting SAR Complex Data

The aim of building edge detection is to obtain a map of man-made structure edges of the investigated scene. Different detectors have been developed exploiting synthetic aperture radar (SAR) data, based on the use of the reflectivity difference (working with SAR amplitude images) or of the phase difference (working with SAR interferometric images) between neighboring pixels. In this letter, a novel approach using jointly both the amplitudes and the interferometric phase of two complex SAR images is proposed, based on the hypothesis that information related to building edges can be retrieved in the two data domains. The technique is based on stochastic estimation theory, exploiting, in particular, Markov random fields. Compared to classical amplitude-based edge detectors and to phase-based ones, the proposed method shows an improvement in terms of detection accuracy, false alarm rate, and building shape recovery. The algorithm has been tested and analyzed using simulated data and validated on L-band and X-band real data sets

Edge Detection Using Real and Imaginary Decomposition of SAR Data

The objective of synthetic aperture radar (SAR) edge detection is the identification of contours across the investigated scene, exploiting SAR complex data. Edge detectors available in the literature exploit singularly amplitude and interferometric phase information, looking for reflectivity or height difference between neighboring pixels, respectively. Recently, more performing detectors based on the joint processing of amplitude and interferometric phase data have been presented. In this paper, we propose a novel approach based on the exploitation of real and imaginary parts of single-look complex acquired data. The technique is developed in the framework of stochastic estimation theory, exploiting Markov random fields. Compared to available edge detectors, the technique proposed in this paper shows useful advantages in terms of model complexity, phase artifact robustness, and scenario applicability. Experimental results on both simulated and real TerraSAR-X and COSMO-SkyMed data show the interesting performances and the overall effectiveness of the proposed metho

MUHD: A multi-channel ultrasound prototype for remote heartbeat detection

This paper presents a novel system based on ultrasonic waves that is capable of detecting heartbeat in a contactless fashion. The aim of this work is to design, build and test a prototype that could be effective, simple in its realisation and use and with a low cost of production. The idea is the exploit the displacement of the skin related to cardiac activity, that is possible by using phase difference between a transmitted wave and the waves resulting from the interaction with the subject skin. Nevertheless, this type of procedure is not new in the scientific literature, but in this manuscript the authors contribution mainly consists in the implementation of a multi-channel architecture in order to overcome the well known “null-point” issue. Furthermore, an a-priori regularisation function is used for making the system more robust against noise and artifact. The performance of the prototype has been tested on volunteers and the results are quite close to standard electrocardiography used as reference

WKSR-NLM: An Ultrasound Despeckling Filter Based on Patch Ratio and Statistical Similarity

Ultrasound images are affected by the well known speckle phenomenon, that degrades their perceived quality. In recent years, several denoising approaches have been proposed. Among all, those belonging to the non-local (NL) family have shown interesting performance. The main difference among the proposed NL filters is the metric adopted for measuring the similarity between patches. Within this manuscript, a statistical metric based on the ratio between two patches is presented. Compared to other statistical measurements, the proposed one is able to take into account the texture of the patch, to consider a weighting kernel and to limit the computational burden. A comparative analysis with other despeckling filters is presented. The method provided good balance between noise reduction and details preserving both in case of simulated (by means of Field II software) and real (breast tumor) datasets

An extension of Phase Linearity Measurement for revealing cross frequency coupling among brain areas

Brain areas need to coordinate their activity in order to enable complex behavioral responses. Synchronization is one of the mechanisms neural ensembles use to communicate. While synchronization between signals operating at similar frequencies is fairly straightforward, the estimation of synchronization occurring between different frequencies of oscillations has proven harder to capture. One specifically hard challenge is to estimate cross-frequency synchronization between broadband signals when no a priori hypothesis is available about the frequencies involved in the synchronization

Hand Gesture Signatures Acquisition and Processing by Means of a Novel Ultrasound System

Hand gestures represent a natural way to express concepts and emotions which are peculiar to each culture. Several studies exploit biometric traits, such as fingerprint, iris or face for subject identification purposes. Within this paper, a novel ultrasound system for person identification that exploits hand gestures is presented. The system works as a sonar, measuring the ultrasonic pressure waves scattered by the subject’s hand, and analysing its Doppler information. Further, several transformations for obtaining time/frequency representations of the acquired signal are computed and a deep learning detector is implemented. The proposed system is cheap, reliable, contactless and can be easily integrated with other personal identification approaches allowing different security levels. The performances are evaluated via experimental tests carried out on a group of 25 volunteers. Results are encouraging, showing the promising potential of the system