Keyword search in the Deep Web

The Deep Web is constituted by data accessible through Web pages, but not readily indexable by search engines, as they are returned in dynamic pages. In this paper we propose a framework for accessing Deep Web sources, represented as relational tables with so-called ac- cess limitations, with keyword-based queries. We formalize the notion of optimal answer and investigate methods for query processing. To our knowledge, this problem has never been studied in a systematic way

Novel approaches to photon detection and timing for 7-wavelength time domain optical mammography

An 8-channel Silicon Photomultiplier probe and a Time-to-Digital Converter are used to build a higher-throughput, cheaper and compact detection chain for time-resolved optical mammography as compared with conventional PhotoMultiplier Tubes and Time-Correlated Single-Photon Counting boards, still providing comparable performance in the estimation of optical properties, but with higher optical responsivity

Towards next generation time-domain diffuse optics devices

Diffuse Optics is growing in terms of applications ranging from e.g. oximetry, to mammography, molecular imaging, quality assessment of food and pharmaceuticals, wood optics, physics of random media. Time-domain (TD) approaches, although appealing in terms of quantitation and depth sensibility, are presently limited to large fiber-based systems, with limited number of source-detector pairs. We present a miniaturized TD source-detector probe embedding integrated laser sources and single-photon detectors. Some electronics are still external (e.g. power supply, pulse generators, timing electronics), yet full integration on-board using already proven technologies is feasible. The novel devices were successfully validated on heterogeneous phantoms showing performances comparable to large state-of-the-art TD rack-based systems. With an investigation based on simulations we provide numerical evidence that the possibility to stack many TD compact source-detector pairs in a dense, null source-detector distance arrangement could yield on the brain cortex about 1 decade higher contrast as compared to a continuous wave (CW) approach. Further, a 3-fold increase in the maximum depth (down to 6 cm) is estimated, opening accessibility to new organs such as the lung or the heart. Finally, these new technologies show the way towards compact and wearable TD probes with orders of magnitude reduction in size and cost, for a widespread use of TD devices in real life

Online Training of an Opto-Electronic Reservoir Computer

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals. Its analog implementations equal and sometimes outperform other digital algorithms on a series of benchmark tasks. Their performance can be increased by switching from offline to online training method. Here we present the first online trained opto-electronic reservoir computer. The system is tested on a channel equalisation task and the algorithm is executed by an FPGA chip. We report performances close to previous implementations and demonstrate the benefits of online training on a non-stationary task that could not be easily solved using offline methods.info:eu-repo/semantics/publishe

Kidney transplant in diabetic patients: modalities, indications and results

<p>Abstract</p> <p>Background</p> <p>Diabetes is a disease of increasing worldwide prevalence and is the main cause of chronic renal failure. Type 1 diabetic patients with chronic renal failure have the following therapy options: kidney transplant from a living donor, pancreas after kidney transplant, simultaneous pancreas-kidney transplant, or awaiting a deceased donor kidney transplant. For type 2 diabetic patients, only kidney transplant from deceased or living donors are recommended. Patient survival after kidney transplant has been improving for all age ranges in comparison to the dialysis therapy. The main causes of mortality after transplant are cardiovascular and cerebrovascular events, infections and neoplasias. Five-year patient survival for type 2 diabetic patients is lower than the non-diabetics' because they are older and have higher body mass index on the occasion of the transplant and both pre- and posttransplant cardiovascular diseases prevalences. The increased postransplant cardiovascular mortality in these patients is attributed to the presence of well-known risk factors, such as insulin resistance, higher triglycerides values, lower HDL-cholesterol values, abnormalities in fibrinolysis and coagulation and endothelial dysfunction. In type 1 diabetic patients, simultaneous pancreas-kidney transplant is associated with lower prevalence of vascular diseases, including acute myocardial infarction, stroke and amputation in comparison to isolated kidney transplant and dialysis therapy.</p> <p>Conclusion</p> <p>Type 1 and 2 diabetic patients present higher survival rates after transplant in comparison to the dialysis therapy, although the prevalence of cardiovascular events and infectious complications remain higher than in the general population.</p

Preference queries over taxonomic domains

When composing multiple preferences characterizing the most suitable results for a user, several issues may arise. Indeed, preferences can be partially contradictory, suffer from a mismatch with the level of detail of the actual data, and even lack natural properties such as transitivity. In this paper we formally investigate the problem of retrieving the best results complying with multiple preferences expressed in a logic-based language. Data are stored in relational tables with taxonomic domains, which allow the specification of preferences also over values that are more generic than those in the database. In this framework, we introduce two operators that rewrite preferences for enforcing the important properties of transitivity, which guarantees soundness of the result, and specificity, which solves all conflicts among preferences. Although, as we show, these two properties cannot be fully achieved together, we use our operators to identify the only two alternatives that ensure transitivity and minimize the residual conflicts. Building on this finding, we devise a technique, based on an original heuristics, for selecting the best results according to the two possible alternatives. We finally show, with a number of experiments over both synthetic and real-world datasets, the effectiveness and practical feasibility of the overall approach