The static electric polarizability of a particle bound by a finite potential well

In this paper we derive an expression for the static electric polarizability of a particle bound by a finite potential well without the explicit use of the continuum states in our calculations. This will be accomplished by employing the elegant Dalgarno-Lewis perturbative technique.Comment: 14 Pages, 2 Table

Extraction of acoustic sources for multiple arrays based on the ray space transform

In this paper we present a source extraction technique for multiple uniform linear arrays distributed in space. The technique adopts the Ray Space Transform representation of the sound field, which is inherently based on the Plane Wave Decomposition. The Ray Space Transform gives us an intuitive representation of the acoustic field, thus enabling the adoption of geometrically-motivated constraints in the spatial filter design. The proposed approach is semi-blind since it needs as input an estimate of the source positions. We prove the effectiveness of the proposed solution through simulations using both white noise and speech signals

A bizarre foreign body in the appendix: A case report

Foreign bodies are rare causes of appendicitis and, in most cases, ingested foreign bodies pass through the alimentary tract asymptomatically. However, ingested foreign bodies may sometimes remain silent within the appendix for many years without an inflammatory response. Despite the fact that cases of foreign-body-induced appendicitis have been documented, sharp and pointed objects are more likely to cause perforations and abscesses, and present more rapidly after ingestion. Various materials, such as needles and drill bits, as well as organic matter, such as seeds, have been implicated as causes of acute appendicitis. Clinical presentation can vary from hours to years. Blunt foreign bodies are more likely to remain dormant for longer periods and cause appendicitis through obstruction of the appendiceal lumen. We herein describe a patient presenting with a foreign body in his appendix which had been swallowed 15 years previously. The contrast between the large size of the foreign body, the long clinical history without symptoms and the total absence of any histological inflammation was notable. We suggest that an elective laparoscopic appendectomy should be offered to such patients as a possible management optio

Experimental evaluation of a localization algorithm for multiple acoustic sources in reverberating environments

Publication in the conference proceedings of EUSIPCO, Florence, Italy, 200

Always on my mind: Cross-brain associations of mental health symptoms during simultaneous parent-child scanning.

How parents manifest symptoms of anxiety or depression may affect how children learn to modulate their own distress, thereby influencing the children's risk for developing an anxiety or mood disorder. Conversely, children's mental health symptoms may impact parents' experiences of negative emotions. Therefore, mental health symptoms can have bidirectional effects in parent-child relationships, particularly during moments of distress or frustration (e.g., when a parent or child makes a costly mistake). The present study used simultaneous functional magnetic resonance imaging (fMRI) of parent-adolescent dyads to examine how brain activity when responding to each other's costly errors (i.e., dyadic error processing) may be associated with symptoms of anxiety and depression. While undergoing simultaneous fMRI scans, healthy dyads completed a task involving feigned errors that indicated their family member made a costly mistake. Inter-brain, random-effects multivariate modeling revealed that parents who exhibited decreased medial prefrontal cortex and posterior cingulate cortex activation when viewing their child's costly error response had children with more symptoms of depression and anxiety. Adolescents with increased anterior insula activation when viewing a costly error made by their parent had more anxious parents. These results reveal cross-brain associations between mental health symptomatology and brain activity during parent-child dyadic error processing

Vertebral Body Stapling versus Bracing for Patients with High-Risk Moderate Idiopathic Scoliosis.

Purpose. We report a comparison study of vertebral body stapling (VBS) versus a matched bracing cohort for immature patients with moderate (25 to 44°) idiopathic scoliosis (IS). Methods. 42 of 49 consecutive patients (86%) with IS were treated with VBS and followed for a minimum of 2 years. They were compared to 121 braced patients meeting identical inclusion criteria. 52 patients (66 curves) were matched according to age at start of treatment (10.6 years versus 11.1 years, resp. [P = 0.07]) and gender. Results. For thoracic curves 25-34°, VBS had a success rate (defined as curve progressio

MRI analysis for Hippocampus segmentation on a distributed infrastructure

Medical image computing raises new challenges due to the scale and the complexity of the required analyses. Medical image databases are currently available to supply clinical diagnosis. For instance, it is possible to provide diagnostic information based on an imaging biomarker comparing a single case to the reference group (controls or patients with disease). At the same time many sophisticated and computationally intensive algorithms have been implemented to extract useful information from medical images. Many applications would take great advantage by using scientific workflow technology due to its design, rapid implementation and reuse. However this technology requires a distributed computing infrastructure (such as Grid or Cloud) to be executed efficiently. One of the most used workflow manager for medical image processing is the LONI pipeline (LP), a graphical workbench developed by the Laboratory of Neuro Imaging (http://pipeline.loni.usc.edu). In this article we present a general approach to submit and monitor workflows on distributed infrastructures using LONI Pipeline, including European Grid Infrastructure (EGI) and Torque-based batch farm. In this paper we implemented a complete segmentation pipeline in brain magnetic resonance imaging (MRI). It requires time-consuming and data-intensive processing and for which reducing the computing time is crucial to meet clinical practice constraints. The developed approach is based on web services and can be used for any medical imaging application

Two-dimensional beam tracing from visibility diagrams for real-time acoustic rendering

We present an extension of the fast beam-tracing method presented in the work of Antonacci et al. (2008) for the simulation of acoustic propagation in reverberant environments that accounts for diffraction and diffusion. More specifically, we show how visibility maps are suitable for modeling propagation phenomena more complex than specular reflections. We also show how the beam-tree lookup for path tracing can be entirely performed on visibility maps as well. We then contextualize such method to the two different cases of channel (point-to-point) rendering using a headset, and the rendering of a wave field based on arrays of speakers. Finally, we provide some experimental results and comparisons with real data to show the effectiveness and the accuracy of the approach in simulating the soundfield in an environment

Pulmonary Infarction Mimicking An Aspergilloma In A Heart Transplant Recipient

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Room Transfer Function Reconstruction Using Complex-valued Neural Networks and Irregularly Distributed Microphones

Reconstructing the room transfer functions needed to calculate the complex sound field in a room has several important real-world applications. However, an unpractical number of microphones is often required. Recently, in addition to classical signal processing methods, deep learning techniques have been applied to reconstruct the room transfer function starting from a very limited set of measurements at scattered points in the room. In this paper, we employ complex-valued neural networks to estimate room transfer functions in the frequency range of the first room resonances, using a few irregularly distributed microphones. To the best of our knowledge, this is the first time that complex-valued neural networks are used to estimate room transfer functions. To analyze the benefits of applying complex-valued optimization to the considered task, we compare the proposed technique with a state-of-the-art kernel-based signal processing approach for sound field reconstruction, showing that the proposed technique exhibits relevant advantages in terms of phase accuracy and overall quality of the reconstructed sound field. For informative purposes, we also compare the model with a similarly-structured data-driven approach that, however, applies a real-valued neural network to reconstruct only the magnitude of the sound field