Differentiation in the short- and long-term effects, of smoking on plasma total ghrelin concentrations between mare nonsmokers and habitual smokers

To explore the association between the anorexigenic effects of nicotine and the orexigenic properties of ghrelin, plasma total ghrelin levels were measured in nonsmokers and habitual smokers before and after short-term exposure to cigarette smoke. Thirty-one male smokers and 23 nonsmoking volunteers were matched for age and body mass index. After an overnight fast and abstinence from smoking, they all smoked 2 cigarettes consecutively (same brand, rate of inhalation, and duration of smoking). Total ghrelin concentrations were measured by radioimmunoassay before smoking (baseline), immediately afterward, and 30, 60, and 90 minutes after the second cigarette. Baseline ghrelin levels were not different between smokers and nonsmokers. Smoking did not have an immediate influence on ghrelin concentrations in smokers (analysis of variance for repeated measurements, P = 0.74), whereas there was a progressive decline in nonsmokers, reaching statistical significance at 30 minutes (P = .04) and a nadir at 60 minutes (P = .04) after smoking. Moreover, the area under the curve for the changes of ghrelin over time after smoking was lower in nonsmokers than in smokers (-287.2 +/- 167.1 vs 29.2 +/- 125.3 ng (.) min/L, P = .03). In conclusion, fasting plasma total ghrelin concentrations are not different between male smokers and nonsmokers. Smoking does not provoke any short-term change in ghrelin levels in smokers, but induces a decline in nonsmokers. If the anorectic effect of smoking is ghrelin induced, this effect may be present only in people not habituated to smoke exposure. In habitual smokers, ghrelin suppression by short-term smoking could be blunted as a result of desensitization due to prolonged nicotine exposure. (c) 2007 Elsevier Inc. All rights reserved

4D Reconstruction of Tangible Cultural Heritage Objects from Web-Retrieved Images

The number of digital images that are available online today has reached unprecedented levels. Recent statistics showed that by the end of 2013 there were over 250 billion photographs stored in just one of the major social media sites, with a daily average upload of 300 million photos. These photos, apart from documenting personal lives, often relate to experiences in well-known places of cultural interest, throughout several periods of time. Thus from the viewpoint of Cultural Heritage professionals, they constitute valuable and freely available digital cultural content. Advances in the fields of Photogrammetry and Computer Vision have led to significant breakthroughs such as the Structure from Motion algorithm which creates 3D models of objects using their 2D photographs. The existence of powerful and affordable computational machinery enables the reconstruction not only of single structures such as artefacts, but also of entire cities. This paper presents an overview of our methodology for producing cost-effective 4D – i.e. in space and time – models of Cultural Heritage structures such as monuments and artefacts from 2D data (pictures, video) and semantic information, freely available ‘in the wild’, i.e. in Internet repositories and social media. State-of-the-art methods from Computer Vision, Photogrammetry, 3D Reconstruction and Semantic representation are incorporated in an innovative workflow with the main goal to enable historians, architects, archaeologists, urban planners and other cultural heritage professionals to reconstruct cost-effective views of historical structures out of the billions of free images floating around the web and subsequently interact with those reconstructions

Cloud-based 3D Reconstruction of Cultural Heritage Monuments using Open Access Image Repositories

A large number of photographs of cultural heritage items and monuments is publicly available in various Open Access Image Repositories (OAIR) and social media sites. Metadata inserted by camera, user and host site may help to determine the photograph content, geo-location and date of capture, thus allowing us, with relative success, to localise photos in space and time. Additionally, developments in Photogrammetry and Computer Vision, such as Structure from Motion (SfM), provide a simple and cost-effective method of generating relatively accurate camera orientations and sparse and dense 3D point clouds from 2D images. Our main goal is to provide a software tool able to run on desktop or cluster computers or as a back end of a cloud-based service, enabling historians, architects, archaeologists and the general public to search, download and reconstruct 3D point clouds of historical monuments from hundreds of images from the web in a cost-effective manner. The end products can be further enriched with metadata and published. This paper describes a workflow for searching and retrieving photographs of historical monuments from OAIR, such as Flickr and Picasa, and using them to build dense point clouds using SfM and dense image matching techniques. Computational efficiency is improved by a technique which reduces image matching time by using an image connectivity prior derived from low-resolution versions of the original images. Benchmarks for two large datasets showing the respective efficiency gains are presented

4D reconstruction of the past: The image retrieval and 3D model construction pipeline

One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.Euro-agriwot,European Cooperation in Science and Technology (COST),Geosystems Hellas,Intergraph,Li-Co

4D reconstruction of the past: The image retrieval and 3D model construction pipeline

One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.Euro-agriwot,European Cooperation in Science and Technology (COST),Geosystems Hellas,Intergraph,Li-Co

The SICMA multimedia server and the virtual museum application

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Innovation management software exploiting multiple criteria analysis: The case of innovation centre of Crete

Summarization: Innovation is a critical factor in building an organization’s culture of growth. Provided that it is properly blended with organizational development initiatives and aligned with the organization’s strategy, it supplies a compelling advantage for the growth process. Neglecting to encompass innovation in an organization’s culture could lead to shrinkage and even extinction, in the case of an intensively competitive market. Executive staff must consider innovative technologies and be aware of all growth opportunities. However, this staff is stressed under information overload. A need exists to reduce the information load and filter available technologies according to the specific needs of the organization. In this paper, the authors propose a recommendation approach to match the needs of an organization against existing technologies (innovative products or services). The organization expresses its customized needs by declaring its preferences over a small reference set of indicative technologies. Each technology is characterized by multiple attributes, in a way that the organization ultimately expresses the trade-offs between the attributes’ significance weights. This information is used to create the organization’s profile. The profile guides a recommendation process, according to which available technologies are evaluated against the profile and proposed to the organization in a descending order.Παρουσιάστηκε στο: International Journal of Decision Support System Technolog