University of Ioannina

About: University of Ioannina is a education organization based out in Ioannina, Greece. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 7654 authors who have published 20594 publications receiving 671560 citations. The organization is also known as: Panepistimio Ioanninon.

Synthesis and characterization of γ-Fe2O3/carbon hybrids and their application in removal of hexavalent chromium ions from aqueous solutions.

Abstract: Magnetic Fe2O3/carbon hybrids were prepared in a two-step process. First, acetic acid vapor interacted with iron cations dispersed on the surface of a nanocasted ordered mesoporous carbon (CMK-3). In the second step, the primarily created iron acetate species underwent pyrolysis and transformed to magnetic iron oxide nanoparticles. X-ray diffraction, Fourier-transform infrared, and Raman spectroscopies were used for the chemical and structural characterization of the hybrids, while surface area measurements, thermal analysis, and transmission electron microscopy were employed to determine their physical, surface, and textural properties. These results revealed the preservation of the host carbon structure, which was homogenously and controllably loaded (up to 27 wt %) with nanosized (ca. 20 nm) iron oxides inside the mesoporous system. Mossbauer spectroscopy and magnetic measurements at low temperatures confirmed the formation of γ-Fe2O3 nanoparticles exhibiting superparamagnetic behavior. The kinetic stu...

Content-Based Routing of Path Queries in Peer-to-Peer Systems

Abstract: Peer-to-peer (P2P) systems are gaining increasing popularity as a scalable means to share data among a large number of autonomous nodes. In this paper, we consider the case in which the nodes in a P2P system store XML documents. We propose a fully decentralized approach to the problem of routing path queries among the nodes of a P2P system based on maintaining specialized data structures, called filters that efficiently summarize the content, i.e., the documents, of one or more node. Our proposed filters, called multi-level Bloom filters, are based on extending Bloom filters so that they maintain information about the structure of the documents. In addition, we advocate building a hierarchical organization of nodes by clustering together nodes with similar content. Similarity between nodes is related to the similarity between the corresponding filters. We also present an efficient method for update propagation. Our experimental results show that multi-level Bloom filters outperform the classical Bloom filters in routing path queries. Furthermore, the content-based hierarchical grouping of nodes increases recall, that is, the number of documents that are retrieved.

Narrow band imaging to differentiate neoplastic and non-neoplastic colorectal polyps in real time: a meta-analysis of diagnostic operating characteristics

Abstract: Purpose Many studies have reported on the use of narrow band imaging (NBI) colonoscopy to differentiate neoplastic from non-neoplastic colorectal polyps. It has potential to replace pathological diagnosis of diminutive polyps. We aimed to perform a systematic review and meta-analysis on the real-time diagnostic operating characteristics of NBI colonoscopy. Methods We searched PubMed, SCOPUS and Cochrane databases and abstracts. We used a two-level bivariate meta-analysis following a random effects model to summarise the data and fit hierarchical summary receiver-operating characteristic (HSROC) curves. The area under the HSROC curve serves as an indicator of the diagnostic test strength. We calculated summary sensitivity, specificity and negative predictive value (NPV). We assessed agreement of surveillance interval recommendations based on endoscopic diagnosis compared to pathology. Results For NBI diagnosis of colorectal polyps, the area under the HSROC curve was 0.92 (95% CI 0.90 to 0.94), based on 28 studies involving 6280 polyps in 4053 patients. The overall sensitivity was 91.0% (95% CI 87.6% to 93.5%) and specificity was 82.6% (95% CI 79.0% to 85.7%). In eight studies (n=2146 polyps) that used high-confidence diagnostic predictions, sensitivity was 93.8% and specificity was 83.3%. The NPVs exceeded 90% when 60% or less of all polyps were neoplastic. Surveillance intervals based on endoscopic diagnosis agreed with those based on pathology in 92.6% of patients (95% CI 87.9% to 96.3%). Conclusions NBI diagnosis of colorectal polyps is highly accurate—the area under the HSROC curve exceeds 0.90. High-confidence predictions provide >90% sensitivity and NPV. It shows high potential for real-time endoscopic diagnosis.