An approximation algorithm for the maximum cut problem and its experimental analysis

AbstractAn approximation algorithm for the maximum cut problem is designed and analyzed; its performance is experimentally compared with that of a neural algorithm and that of Goemans and Williamson's algorithm. Although the guaranteed quality of our algorithm in the worst-case analysis is poor, we give experimental evidence that its average behavior is better than that of Goemans and Williamson's algorithm

Human herpesvirus 6: An emerging pathogen.

Infections with human herpesvirus 6 (HHV-6), a beta-herpesvirus of which two variant groups (A and B) are recognized, is very common, approaching 100% in seroprevalence. Primary infection with HHV-6B causes roseola infantum or exanthem subitum, a common childhood disease that resolves spontaneously. After primary infection, the virus replicates in the salivary glands and is shed in saliva, the recognized route of transmission for variant B strains; it remains latent in lymphocytes and monocytes and persists at low levels in cells and tissues. Not usually associated with disease in the immunocompetent, HHV-6 infection is a major cause of opportunistic viral infections in the immunosuppressed, typically AIDS patients and transplant recipients, in whom HHV-6 infection/reactivation may culminate in rejection of transplanted organs and death. Other opportunistic viruses, human cytomegalovirus and HHV-7, also infect or reactivate in persons at risk. Another disease whose pathogenesis may be correlated with HHV-6 is multiple sclerosis. Data in favor of and against the correlation are discussed

Intrinsic Dimension Estimation: Relevant Techniques and a Benchmark Framework

When dealing with datasets comprising high-dimensional points, it is usually advantageous to discover some data structure. A fundamental information needed to this aim is the minimum number of parameters required to describe the data while minimizing the information loss. This number, usually called intrinsic dimension, can be interpreted as the dimension of the manifold from which the input data are supposed to be drawn. Due to its usefulness in many theoretical and practical problems, in the last decades the concept of intrinsic dimension has gained considerable attention in the scientific community, motivating the large number of intrinsic dimensionality estimators proposed in the literature. However, the problem is still open since most techniques cannot efficiently deal with datasets drawn from manifolds of high intrinsic dimension and nonlinearly embedded in higher dimensional spaces. This paper surveys some of the most interesting, widespread used, and advanced state-of-the-art methodologies. Unfortunately, since no benchmark database exists in this research field, an objective comparison among different techniques is not possible. Consequently, we suggest a benchmark framework and apply it to comparatively evaluate relevant state-of-the-art estimators

Precise eye localization through a general-to-specific model definition

We present a method for precise eye localization that uses two Support Vector Machines trained on properly selected Haar wavelet coefficients. The evaluation of our technique on many standard databases exhibits very good performance. Furthermore, we study the strong correlation between the eye localization error and the face recognition rate

Lung nodules detection and classification

Image processing techniques and Computer Aided Diagnosis (CAD) systems have proved to be effective for the improvement of radiologists' diagnosis. In this paper an automatic system detecting lung nodules from Postero Anterior Chest Radiographs is presented. The system extracts a set of candidate regions by applying to the radiograph three different and consecutive multi-scale schemes. The comparison of the results obtained with those presented in the literature show the efficacy of our multi-scale framework. Learning systems using as input different sets of features have been experimented for candidates classification, showing that Support Vector Machines (SVMs) can be successfully applied for this task

Intrinsic Dimension Estimation: Relevant Techniques and a Benchmark Framework

When dealing with datasets comprising high-dimensional points, it is usually advantageous to discover some data structure. A fundamental information needed to this aim is the minimum number of parameters required to describe the data while minimizing the information loss. This number, usually called intrinsic dimension, can be interpreted as the dimension of the manifold from which the input data are supposed to be drawn. Due to its usefulness in many theoretical and practical problems, in the last decades the concept of intrinsic dimension has gained considerable attention in the scientific community, motivating the large number of intrinsic dimensionality estimators proposed in the literature. However, the problem is still open since most techniques cannot efficiently deal with datasets drawn from manifolds of high intrinsic dimension and nonlinearly embedded in higher dimensional spaces. This paper surveys some of the most interesting, widespread used, and advanced state-of-the-art methodologies. Unfortunately, since no benchmark database exists in this research field, an objective comparison among different techniques is not possible. Consequently, we suggest a benchmark framework and apply it to comparatively evaluate relevant stateof-the-art estimators

Automatic Segmentation of Mouse Images

Genetic engineering has enabled the generation of organisms where molecular reactions in response to patho-physiological events can be measured in real-time by means of molecular imaging. This novel technology with the generation of reporter cell systems, that is cells engineered to express a bioluminescent protein in response to selected stimuli, had a major impact in pharmacological research. The recent generation of reporter mice, where the activity of a specific drug can be studied systematically, hold the promise to strengthen preclinical studies, providing a very rapid and comprehensive view on drug pharmacokinetics and activity in whole organisms. To date, a major limitation to the use of in vivo imaging for pharmaco-toxicological purposes resides in the limited throughput of the methodology: even if up to 100 animals can be reasonably processed in a day by some imaging techniques, the analysis of the data, including the identification and quantification of signals belonging to different mouse body areas, requires time and trained personnel, to manually identify specific body areas where drug effects can be measured. For this reason, we have developed an algorithm to automatically identify (segment) the body areas of a given reporter mouse. Automatic segmentation is obtained by combining classical image processing and pattern recognition techniques. The algorithm has been tested on more than 1000 mouse images differing for sex, pose and lighting conditions, and acquired by devices of different companies. Our algorithm, not only increases processivity (the whole dataset analyzed by a trained scientist in a week was processed overnight by our software), but also provides more accurate results. In conclusion, automatic systems may outperform current manual image analysis, allowing to obtain a detailed comprehension of real-time molecular processes in living animals with a standardized, rapid, and cost-effective approach. This work was supported by EC. (STREP EWA LSHM-CT-2005-518245) NIH (RO1AG027713) to A.M

The structure of Herpesvirus Fusion Glycoprotein B-Bilayer Complex reveals the protein-membrane and lateral protein-protein interaction

Glycoprotein B (gB) is a key component of the complex herpesvirus fusion machinery. We studied membrane interaction of two gB ectodomain forms and present an electron cryotomography structure of the gB-bilayer complex. The two forms differed in presence or absence of the membrane proximal region (MPR) but showed an overall similar trimeric shape. The presence of the MPR impeded interaction with liposomes. In contrast, the MPR-lacking form interacted efficiently with liposomes. Lateral interaction resulted in coat formation on the membranes. The structure revealed that interaction of gB with membranes was mediated by the fusion loops and limited to the outer membrane leaflet. The observed intrinsic propensity of gB to cluster on membranes indicates an additional role of gB in driving the fusion process forward beyond the transient fusion pore opening and subsequently leading to fusion pore expansion

Inner tegument protein pUL37 of herpes simplex virus type 1 is involved in directing capsids to the trans-Golgi network for envelopment

Secondary envelopment of herpes simplex virus type 1 has been demonstrated as taking place at the trans-Golgi network (TGN). The inner tegument proteins pUL36 and pUL37 and the envelope glycoproteins gD and gE are known to be important for secondary envelopment. We compared the cellular localizations of capsids from a virus mutant lacking the UL37 gene with those of a virus mutant lacking the genes encoding gD and gE. Although wild-type capsids accumulated at the TGN, capsids of the pUL37− mutant were distributed throughout the cytoplasm and showed no association with TGN-derived vesicles. This was in contrast to capsids from a gD−gE− mutant, which accumulated in the vicinity of TGN vesicles, but did not colocalize with them, suggesting that they were transported to the TGN but were unable to undergo envelopment. We conclude that the inner tegument protein pUL37 is required for directing capsids to the TGN, where secondary envelopment occurs