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Bone marrow fibrosis is a critical component of primary myelofibrosis in which normal bone marrow tissue and blood-forming cells are gradually replaced with scar tissue. The specific cellular and molecular mechanisms that cause bone marrow fibrosis are not understood. A recent study using state-of-the-art techniques, including in vivo lineage tracing, provides evidence that Gli1+ cells are the cells responsible for fibrotic disease in the bone marrow. Strikingly, genetic depletion of Gli1+ cells rescues bone marrow failure and abolishes myelofibrosis. This work introduces a new central cellular target for bone marrow fibrosis. The knowledge that emerges from this research will be important for the treatment of several malignant and nonmalignant disorders.

Traumatic spinal cord injury is a devastating condition that leads to significant neurological deficits and reduced quality of life. Therapeutic interventions after spinal cord lesions are designed to address multiple aspects of the secondary damage. However, the lack of detailed knowledge about the cellular and molecular changes that occur after spinal cord injury restricts the design of effective treatments. Li and colleagues using a rat model of spinal cord injury and in vivo microscopy reveal that pericytes play a key role in the regulation of capillary tone and blood flow in the spinal cord below the site of the lesion. Strikingly, inhibition of specific proteins expressed by pericytes after spinal cord injury diminished hypoxia and improved motor function and locomotion of the injured rats. This work highlights a novel central cellular population that might be pharmacologically targeted in patients with spinal cord trauma. The emerging knowledge from this research may provide new approaches for the treatment of spinal cord injury.

Motivated by the ever increasing difficulties faced by laypeople in retrieving and digesting valid and relevant information to make health-centred decisions, the CLEF eHealth lab series has offered shared tasks to the community in the fields of Information Extraction (IE), management, and Information Retrieval (IR) since 2013. These tasks have attracted large participation and led to statistically significant improvements in processing quality. In 2021, CLEF eHealth is calling for participants to contribute to the following two tasks: Task 1 on IE focuses on IE from noisy text. Participants will identify and classify Named Entities in written ultrasonography reports, containing misspellings and inconsistencies, from a major public hospital in Argentina. Identified entities will then have to be classified, which can be very challenging as it requires to handle lexical variations. Task 2 is a novel extension of the most popular and established task on consumer health search (CHS), aiming at retrieving relevant, understandable, and credible information for patients and their next-of-kins. In this paper we describe recent advances in the fields of IE and IR, and the subsequent offerings of this years CLEF eHealth lab challenges.

In this paper, we provide an overview of the ninth annual edition of the CLEF eHealth evaluation lab. CLEF eHealth 2021 continues our evaluation resource building efforts around the easing and support of patients, their next-of-kins, health care professionals, and health scientists in understanding, accessing, and authoring electronic health information in a multilingual setting. The 2021 lab offered two tasks: Task 1 on multilingual Information Extraction (IE), this year extending to a corpus of Spanish radiology reports; and Task 2 on Consumer Health Search (CHS) that builds on the previous year’s Information Retrieval (IR) tasks. In total, 11 teams took part in these tasks (7 in Task 1 on IE and 4 in Task 2 on IR). Herein, we describe the resources created for these tasks and the evaluation methodology adopted, and we provide a brief summary of the participants of this year’s challenges as well as the results obtained. As in previous years, the organizers have made data, tools, and more specific overview papers associated with the lab tasks available for future research and development.

In recent years, deep learning models have been successfully applied to Information Retrieval (IR), mainly for assessing the topical relevance of documents with respect to queries. However, relevance is a multidimensional concept, which can be assessed based on several criteria, depending on the document type, the domain considered, the search task performed, etc. Given that recent advancements in deep neural networks enable several learning tasks to be solved simultaneously, in this paper we examine the possibility of modeling multidimensional relevance by jointly solving a retrieval task, to learn topical relevance, and a classification task, to learn additional relevance dimensions. To instantiate and evaluate the proposed model, we consider three query-independent relevance dimensions beyond topicality, i.e., readability, trustworthiness, and credibility. The reported findings show that the proposed joint modeling can improve the performance of the retrieval task.

In this paper, we provide an overview of the eight annual edition of the Conference and Labs of the Evaluation Forum (CLEF) eHealth evaluation lab. The Conference and Labs of the Evaluation Forum (CLEF) eHealth 2020 continues our development of evaluation tasks and resources since 2012 to address laypeople’s difficulties to retrieve and digest valid and relevant information in their preferred language to make health-centred decisions. This year’s lab advertised two tasks. Task 1 on Information Extraction (IE) was new and focused on automatic clinical coding of diagnosis and procedure the tenth revision of the International Statistical Classification of Diseases and Related Health Problems (ICD10) codes as well as finding the corresponding evidence text snippets for clinical case documents in Spanish. Task 2 on Information Retrieval (IR) was a novel extension of the most popular and established task in the Conference and Labs of the Evaluation Forum (CLEF) eHealth on Consumer Health Search (CHS). In total 55 submissions were made to these tasks. Herein, we describe the resources created for the two tasks and evaluation methodology adopted. We also summarize lab submissions and results. As in previous years, the organizers have made data and tools associated with the lab tasks available for future research anddevelopment. The ongoing substantial community interest in the tasks and their resources has led to the Conference and Labs of the Evaluation Forum (CLEF) eHealth maturing as a primary venue for all interdisciplinary actors of the ecosystem for producing, processing, and consuming electronic healthinformation.

A growing attention has been recently devoted to the impact of the underwater noise field generated by shipping activities on the marine fauna. A key aspect for the quantification of such impact is a proper model of the source levels radiated from the vessels. At a first level of approximation, simplified formulations based on a small number of macro-parameters describing the ship characteristics are needed to quantify the emission and, accordingly, assess the noise impact and evaluate strategies for its control. In fact, a few models of this kind are available in literature, mainly based on measurements and databases developed for military purposes. Most of these models have been tuned on old ships: this poses the question whether they are still applicable to modern commercial vessels. In the present work, spectra of a series of measurements of underwater noise emitted by commercial vessels measured in the framework of two EU FP7 projects (SILENV: www.silenv.eu and AQUO: www.aquo.eu) are analyzed and compared with the results obtained applying the available literature models. The analysis is carried out for noise emitted both at design and off-design conditions. In such conditions, the models are also compared with a proposed spectral parametrization. Focusing on the off-design conditions, a detailed narrow band analysis of a complete set of noise spectra is presented for a ship equipped with a controllable pitch propeller (CPP). The spectral peculiarities of such a propulsion plant, when operated at constant revolutions per minute (RPM) are highlighted. Results of the suggested parametrization applied to the same ship are presented together with the data of other CPP ships and a critical analysis is carried out discussing the limits of the existing predictive models.

With the development of Web 2.0 technologies, people have gone from being mere content users to content generators. In this context, the evaluation of the quality of (potential) information available online has become a crucial issue. Nowadays, one of the biggest online resources that users rely on as a knowledge base is Wikipedia. The collaborative aspect at the basis of Wikipedia can let to the possible creation of low-quality articles or even misinformation if the process of monitoring the generation and the revision of articles is not performed in a precise and timely way. For this reason, in this paper, the problem of automatically evaluating the quality of Wikipedia contents is considered, by proposing a supervised approach based on Machine Learning to perform the classification of articles on qualitative bases. With respect to prior literature, a wider set of features connected to Wikipedia articles has been taken into account, as well as previously unconsidered aspects connected to the generation of a labeled dataset to train the model, and the use of Gradient Boosting, which produced encouraging results.

Nowadays, electricity is the most widely used kind of energy, which is composed by a mix of traditional fossil sources and renewable energies. The use of renewable energies is increasingly incentivized at present, but, due to their characteristics connected for example to climatic conditions, they can be subject to temporary unavailability. Production plants, in order to function properly, and to guarantee a standard level of energy, must cope flexibly with this problem. In this article, we aim at presenting the main technologies and solutions that are connected to the considered problem, and we introduce the architecture of a flexible affiliation system that can optimize the use of electricity distribution networks efficiently, reducing energy waste.

This paper describe SWAMP, a prototype Autonomous Surface Vehicle (ASV) representing the base for the design and development of an innovative class of reliable modular reconfigurable lightweight ASVs for extremely shallow water applications. The design of SWAMP-class ASVs is based on a holistic approach involving different aspects of robotics such as the use of soft materials, the mechanical design of innovative propulsion system integrated with the vessel hull, the adoption of modular mechanical and computing architecture able to support multi-agent distributed GNC systems.

The Social Web represents nowadays the principal means to support and foster social interactions among people through Web 2.0 technologies. Individuals interact in virtual communities to pursue mutual interests or goals, by exchanging multiple kinds of contents (i.e., textual, acoustic, visual), the so-called User-Generated Content (UGC). In this context, the SeCredISData Special Session is especially devoted at discussing the implications that the analysis of big social data has in tackling open issues related to society from different perspectives. On one side, there is the need to push forward the research on emotion and sentiment, and the investigation of affective cognitive models and their possible integration into intelligent systems. On the other side, it is urgent to address the issue of on-line information credibility assessment, in an era where trusted intermediaries have disappeared and people must rely only on their cognitive capacities to judge information. The Special Session is therefore aimed at promoting the development of models and applications able to tackle these issues.

Recent ICTs paradigms such as cloud computing, data outsourcing, digital data markets, and the spread of multiple social media based on Web 2.0 technologies, facilitate the exchange of large data and information flows among a myriad of interconnected devices and users, for different aims and purposes. This complex scenario underlies the development of on-line ecosystems of interacting entities, where the concepts of community, self-organization, evolution and knowledge are fundamental.While the benefits connected to such kind of ecosystems are intuitive also to the everyday man, no lunch comes for free, and such a complex and interconnected scenario entails a number of issues connected to both data and information generation and diffusion that should be carefully addressed. For example, in the data sharing context, genuine data could be manipulated, tampered with, accessed without permission, breached, or improperly disclosed; in the Social Web context, low-quality data and/or misinformation could be diffused. With respect to the above-mentioned issues, in this paper we survey some of the possible approaches proposed in the literature for ensuring adequate data protection, with particular reference to data confidentiality, and for assessing information credibility in complex on-line environments. We also provide a conclusive discussion aimed at illustrating the importance of relating these concepts.

The prediction of propeller induced pressure fluctuations and underwater radiated noise is a subject of great and increasing interest in marine engineering. Nevertheless, the full-scale prediction of these negative effects, even though based on dedicated model scale tests represents still a challenging task. This is due to different phenomena, among which scale effects on cavitation and ship wake, confined environment and near field effects in model tests play an important role; the analysis of these problems is made difficult by the rather limited amount of available data from sea trials and to the complexities of the phenomena, most of which related to cavitation on the propeller blades, that are present in the measurements carried out in cavitation tunnels, depressurized towing tanks or circulating channels. In the present work, the subject has been studied with reference to a four blades conventional CP propeller of a coastal tanker. Cavitation tunnel tests have been carried out in two rather different facilities, at UNIGE cavitation tunnel and at SSPA large cavitation tunnel. Results from model scale tests processed with different treatments are then compared with full scale measurements performed by SSPA on the same propeller in terms of cavitation extension and radiated noise. The analysis is aimed at assessing the effectiveness of different experimental setups, testing procedures and scaling laws.

In a ubiquitous scenario, people are typically confronted with context evolution and changing influences. This may create new needs and may condition the user perception of what is relevant information. Over the years, different approaches have been proposed to design personalized Recommender Systems (RS), but state-of-the-art approaches mostly assume a fixed representation of a user profile; the dynamicity of the user's interests (and the way of expressing them) while interacting with the environment is not considered. Aim of this work is to predict a user's preferences in the tourism domain, to provide personalized and context-aware recommendations. Therefore, we define a user profile model which expresses in a formal way the user's opinions with respect to a particular entity. In particular, the proposed approach formally models the user generated content (UGC) connected to a group of reviews (written by expert users) for each entity, and compares it with a (positive and negative) statistical language model representing the target user profile associated with that entity. The effectiveness of the approach is illustrated on a real-case scenario.

Nowadays, review sites are more and more confronted with the spread of misinformation, i.e., opinion spam, which aims at promoting or damaging some target businesses, by misleading either human readers, or automated opinion mining and sentiment analysis systems. For this reason, in the last years, several data-driven approaches have been proposed to assess the credibility of user-generated content diffused through social media in the form of on-line reviews. Distinct approaches often consider different subsets of characteristics, i.e., features, connected to both reviews and reviewers, as well as to the network structure linking distinct entities on the review-site in exam. This article aims at providing an analysis of the main review- and reviewer-centric features that have been proposed up to now in the literature to detect fake reviews, in particular from those approaches that employ supervised machine learning techniques. These solutions provide in general better results with respect to purely unsupervised approaches, which are often based on graph-based methods that consider relational ties in review sites. Furthermore, this work proposes and evaluates some additional new features that can be suitable to classify genuine and fake reviews. For this purpose, a supervised classifier based on Random Forests have been implemented, by considering both well-known and new features, and a large-scale labeled dataset from which all these features have been extracted. The good results obtained show the effectiveness of new features to detect in particular singleton fake reviews, and in general the utility of this study.

The Social Web supports and fosters social interactions by means of different social media, which allow the spread of the so called User-Generated Content (UGC). In this context, characterized by the absence of trusted third parties that verify the reliability of the sources and the believability of the content generated, the issue of assessing the credibility of the information diffused by means of social media is receiving increasing attention. In the literature, this issue has been mainly tackled as a classification problem; information is categorized into genuine and fake, usually by implementing or applying classifiers that consider multiple kinds of features (mainly textual and non-textual) to be evaluated in terms of credibility. In this article, unlike prior research, textual features are considered separately with respect to other kinds of features during the classification process. In particular, an Ensemble Method that combines the results produced by two text classifiers and the ones returned by another classifier acting on non-textual features is proposed. This allows to have better results with respect to the use of a single classifier on multiple features together. The effectiveness of the Ensemble Method has been assessed in the context of review sites, by means of a labeled dataset gathered from the Yelp.com site, where on-line reviews are already classified as recommended and not recommended.

Innovative contribution to aggregated search.Innovative contribution to the definition of interfaces for visualizing search results.Graph-based visualization of multimedia search results.Multimodal access to media objects.User based evaluation. Nowadays, together with the increasing spread of the content available online, users' information needs have become more complex. To fulfill them, users strongly rely on Web search engines, but traditional ways of presenting search results are often unsatisfactory. In fact, Web pages carry information that exists in multiple media formats, such as text, audio, image and video objects. Vertical search engines and medium-specific search services do not provide users with an integrated view of search results. Furthermore, multiple media objects are in most of the cases highly semantically interlinked, but the connections between them are not sufficiently exploited to provide a further exploration of the retrieved objects. To address these issues, in this paper we propose a graph-based approach aimed at providing users with the possibility to dynamically visualize and explore a search result space built over a repository of multimedia documents containing interconnected multiple media objects. To do this, we represent the search result space via a graph-based data model, where both the retrieved multimedia documents and connected relevant media objects are considered. Media objects, among them, are connected via different kinds of similarity relationships, which depend on the low-level features and metadata taken into consideration to access the media objects. The approach and the connected visualization and exploration interface have been implemented and tested on a publicly available dataset, and they have been evaluated by means of a usability test.

With the expression social collaboration we refer to the processes of helping multiple people to interact and share information in order to achieve common goals. Nowadays, collaboration and social dissemination of information are facilitated by the Internet and Social Network Services (SNS). The reliance of social collaboration on SNS might seem surprising given the differences between their group-centric and individual-centric views. In particular, social collaboration services focus on group activities, identifying groups and collaboration spaces in which messages are explicitly directed at the group and the group activity feed is seen the same way by everyone. In contrast, social networking services generally focus on single personalized activities, sharing messages in a more-or-less undirected way and receiving messages from many sources into a single personalized activity feed.

In the field of multi-application personalization, several techniques have been proposed to support user modeling for user data management across different applications. Many of them are based on data reconciliation techniques often implying the concepts of static ontologies and generic user data models. None of them have sufficiently investigated two main issues related to user modeling: (1) profile definition in order to allow every application to build their own view of users while promoting the sharing of these profiles and (2) profile evolution over time in order to avoid data inconsistency and the subsequent loss of income for web-site users and companies. In this paper, we conduct work and propose separated solutions for every issue. We propose a flexible user modeling system, not imposing any fixed user model whom different applications should conform to, but based on the concept of mapping among applications (and mapping functions among their user attributes). We focus in particular on the management of user profile data propagation, as a way to reduce the amount of inconsistent user profile information over several applications. A second goal of this paper is to illustrate, in this context, the benefit obtained by the integration of a Semantic Layer that can help application designers to automatically identify potential user attribute mappings between applications. This paper so illustrates a work-in-progress work where two complementary approaches are integrated to improve a main goal: managing multi-application user profiles in a semi-automatic manner. Copyright is held by the International World Wide Web Conference Committee (IW3C2).

Peer-to-peer (P2P) systems represent nowadays a large portion of Internet traffic, and are fundamental data sources. In a pure P2P system, since no peer has the power or responsibility to monitor and restrain others behaviours, there is no method to verify the trustworthiness of shared resources, and malicious peers can spread untrustworthy data objects to the system. Furthermore, data descriptions are often simple features directly connected to data or annotations based on heterogeneous schemas, a fact that makes difficult to obtain a single coherent trust value on a resource. This chapter describes techniques where the combination of Semantic Web and peer-to-peer technologies is used for expressing the knowledge shared by peers in a well-defined and formal way. Finally, dealing with Semantic-based P2P networks, the chapter suggests a research effort in this direction, where the association between cluster-based overlay networks and reputation systems based on numerical approaches seems to be promising. © 2009, IGI Global.

Purpose The true incidence of pulmonary embolism (PE) in critically ill adult patients receiving antithrombotic prophylaxis is unknown, as well as the impact on the outcome. The aim of this study was to assess the incidence of PE in a surgical and medical intensive care unit and to evaluate the presence of risk factors that could be helpful in identifying patients at higher risk of missed diagnosis. Materials and Methods We retrospectively reviewed the autopsies and clinical data of all patients who died in our intensive care unit from 1996 to 2007. All patients received prophylaxis with subcutaneous low–molecular weight heparin. Results Among the 600 autopsies, the clinical diagnosis of PE was confirmed in 13 patients (true positives) and not confirmed in 20 patients; in 73 patients, the PE was discovered only at the autopsy (false negatives [FNs]). The overall incidence of PE in our patients was 14.3%. Pulmonary embolism was considered the cause of death in 45% of FNs and 77% of true positives. Among all comorbidities, only a recent abdominal surgery and the presence of acute renal failure were associated with a higher risk of missed diagnosis. In the FN group, there was a significantly higher frequency of cases of septic shock. Conclusions Despite thromboprophylaxis, critically ill patients remain at risk for PE; and because of the difficulty in diagnosing it clinically, the death certificate diagnosis of PE underestimates the problem.

PURPOSE: Because the use of IgM and IgA enriched polyclonal intravenous immunoglobulins (eIg) is a standard of care in critically ill patients admitted to our intensive care unit (ICU) with the diagnosis of severe sepsis or septic shock, we investigated if the delay from the onset of severe sepsis and septic shock and their administration could influence the outcome. MATERIALS AND METHODS: The medical records of all patients with severe sepsis or septic shock admitted to our ICU from July 2004 through October 2009 and treated with eIg (Pentaglobin®; Biotest, Dreieich, Germany) were retrospectively examined. RESULTS: A total of 129 adult patients with severe sepsis or septic shock were considered eligible. Thirty-two percent of patients died during the ICU stay. Survivors were given eIg significantly earlier than nonsurvivors (23 vs 63 hours, P < .05). The delay in the administration of eIg and the Simplified Acute Physiology Score II were the only variables that entered stepwise a propensity score-adjusted logistic model. The delay in the administration of eIg was a significant predictor of the odds of dying during the ICU stay (odds ratio for 1 hour of delay, 1.007; P < .01; 99% confidence interval from 1.001 to 1.010) and proved to be independent from the Simplified Acute Physiology Score II and other variables. CONCLUSIONS: The efficacy of eIg, being maximal in early phases of severe sepsis and/or septic shock, is probably time dependent.

We undertook a prospective observational cohort study in intensive care unit (ICU) patients requiring mechanical ventilation for four days or more to evaluate normal and abnormal bacterial carriage on admission detected by surveillance cultures of throat and rectum. We assessed the importance of surveillance and diagnostic cultures for the early detection of resistance to third generation cephalosporins employed as the parenteral component of the selective decontamination of the digestive tract. Finally, we sought the risk factors of abnormal carriage on admission to the ICU. During the 58-month study 621 patients were included: 186 patients (30%) carried abnormal flora including methicillin-resistant Staphylococcus aureus (MRSA) and aerobic Gram negative bacilli (AGNB) on admission to the ICU. Both MRSA and AGNB carriers were more commonly present in the hospital group of patients than in patients referred from the community (P

The design of composite applications by combining existing services with known semantics is an ongoing topic in current research. Several studies are aimed at providing service description models and standards, service discovery and matching etc. However, service composition in distributed dynamic environments such as P2P ecosystems has received little attention from research communities. In this paper we present a design framework for composing services, taking in particular into account different ways of building peercommunities based on network or services characteristics.

Background: During winter 2009 we treated with prolonged corticosteroid infusion eight consecutive patients affected by H1N1-virus infection and severe pneumonia. The most severe patient was a previously healthy 30-year-old man admitted to hospital because of bilateral pneumonia and severe acute respiratory failure. Method: H1N1-virus infection was detected by broncho-alveolar lavage performed on day 1. After some days following admission the patient was still in a life-threatening state, not responding to oseltamivir, protective mechanical ventilation and veno-arterial extracorporeal membrane oxygenation (ECMO). Results: The addition of methylprednisolone infusion at a stress dose (1 mg/kg/24 h) as rescue therapy significantly and rapidly improved the clinical condition. Weaning from ECMO and invasive mechanical ventilation was possible within a relatively few days. Conclusion: According to the literature reports more than 34% of H1N1-virus severe infections were treated with corticosteroids. This report and our experience may suggest a possible life-saving use of corticosteroids at a stress dose in severely ill patients with an H1N1-virus infection that is not responding to the most advanced treatments.

Between June 1988 and May 1991 88 orthotopic liver transplants and 1 liver and pancreas transplant were performed at the Liver Transplantation Department of the Ospedale Maggiore of Milan. All the patients underwent mycological surveillance and received antifungal prophylaxis with oral amphotericin B (6000 mg/day) or oral or intravenous fluconazole (200 mg/day) from the time of their transplant. The incidence of Candida colonization was 67%. Fluconazole was superior to oral amphotericin B in the treatment of C. albicans colonization (9/9 vs 6/15), but less effective in the treatment of colonization by other Candida spp. (0/3 vs 3/3). Deep-seated candidiasis developed in 5 patients, caused by C. albicans in 4 cases and C. krusei in 1. C. albicans infection resolved rapidly with fluconazole in 2 subjects, with intravenous amphotericin B alone in 1, and with amphotericin B plus flucytosine in the other. On the contrary, C. krusei infection did not respond to treatment with amphotericin B combined with flucytosine. Aspergillosis was diagnosed in 11 patients, of whom 4 died from invasive aspergillosis, despite 15 and 26 days of amphotericin B treatment in 2. In another patient invasive aspergillosis, diagnosed a few hours before retransplantation, improved with liposomal amphotericin B, but this man died from cytomegalovirus infection one month later. Aspergillosis was eradicated by itraconazole in 4 other patients and by topical amphotericin B in 2 whose infection was localized to surgical wound.

We discuss how the notion of gradual information disclosure can be incorporated into basic social computing protocols, such as reputation-based service selection. Our technique links the decrease in anonymity a subject is ready to endure (e.g., by disclosing the values of some of her attributes) to the weight her views will carry in the final outcome of the protocol. © 2009 IEEE.

Aim, patients, and methods To compare retrospectively the outcomes of patients with severe traumatic brain injury (Injury Severity Score, ISS total Z15; the Abbreviated ISS-head, aISShead Z9) admitted to our Intensive Care Unit by helicopter (helicopter emergency medical service, HEMS group= 89) with those transported by ambulance (GROUND group= 105) from January 2002 to December 2007. Results The groups were comparable for age, Glasgow Coma Scale, ISS total, and aISShead. The preadmission time of the HEMS group was significantly longer as compared with the GROUND group, but the interval from admission to definitive care was significantly shorter. In the prehospital phase, HEMS patients were more aggressively treated, as indicated by a significantly greater number of procedures performed (i.e. tracheal intubation and positioning of intravenous lines) and larger volumes of fluids infused. The overall mortality was lower in the HEMS than in the GROUND patients (21 vs. 25% respectively, P< 0.05). The survival with or without only minor neurological disabilities was higher in the HEMS than in the GROUND group (54 vs. 44% respectively, P< 0.05); among the survivors, the rate of severe neurological disabilities was lower in the HEMS than in the GROUND group (25 vs. 31%, P < 0.05). Conclusion In our experience, aggressive early treatment of patients with severe traumatic brain injury was associated with a better outcome likely because of the prevention of secondary brain injury and a shorter interval elapsing from the trauma to definitive care despite more time spent on the scene by the intervening team. European Journal of Emergency Medicine 16:312–317 c 2009 Wolters Kluwer Health | Lippincott Williams & Wilkins.

The design of composite applications by combining existing services with known semantics is an ongoing topic in current research. Several studies are aimed at providing service description models and standards, service discovery and matching etc. However, service composition in distributed dynamic environments such as P2P has received little attention from the research communities. In this paper we present a design framework for composing services, taking in particular into account different ways for building peer-communities based on network or services characteristics. © 2008 IEEE.

Organizations and enterprises have developed complex data and information exchange systems that are now vital for their daily operations. Currently available systems, however, face a major challenge. On todays global information infrastructure, data semantics is more and more context- and time-dependent, and cannot be fixed once and for all at design time. Identifying emerging relationships among previously unrelated information items (e.g., during data interchange) may dramatically increase their business value. This chapter introduce and discuss the notion of Emergent Semantics (ES), where both the representation of semantics and the discovery of the proper interpretation of symbols are seen as the result of a selforganizing process performed by distributed agents, exchanging symbols and adaptively developing the proper interpretation via multi-party cooperation and conflict resolution. Emergent data semantics is dynamically dependent on the collective behaviour of large communities of agents, which may have different and even conflicting interests and agendas. This is a research paradigm interpreting semantics from a pragmatic prospective. The chapter introduce this notion providing a discussion on the principles, research area and current state of the art. © 2008 Springer-Verlag Berlin Heidelberg.

Objective: To test the effects of positive expiratory pressure onthe leakage of fluid around cuffs of different tracheal tubes, inmechanically ventilated patients and in a benchtop model.Design: Randomized clinical trial and experimental in vitrostudy.Setting: Intensive care unit of a university hospital.Patients: Forty patients recovering in the intensive care unitwere ventilated in volume-controlled mode. Twenty patients wererandomly intubated with Hi-Lo tubes (HL group), whereas theremaining 20 subjects were intubated with SealGuard tubes (SGgroup).Interventions: Immediately after intubation and cuff inflationwith 30 cm H2O, Evans blue was applied onto the cephalic surfaceof the tracheal tube cuff. A 5-cm H2O positive expiratory pressurewas used during the first 5 hrs of stay, and thereafter it wasremoved. Bronchoscopy verified whether the dye leaked aroundthe cuff. The experiment lasted 12 hrs. Leakage was also testedin vitro with the same tracheal tubes with incremental level ofpositive expiratory pressure.Measurements and Main Results: At 1 hr, 5 hrs, and thereafterhourly until 12 hrs, bronchoscopy was used to test the presenceof dye on the trachea caudal to the cuff. At the fifth hour, twopatients of the HL group failed the test. One hour after positiveexpiratory pressure removal, all subjects in group HL exhibited adyed lower trachea. On the other hand, one patient in group SGpresented a leak at the eighth hour, and at the 12th hour three ofthem were still sealed. In vitro, the same level of positive expiratorypressure delayed the passage of dye around the cuff; after30 mins positive expiratory pressure was removed, and in 10 minsall dye leaked only in the Hi-Lo tube.Conclusions: We found that 5 cm H2O positive expiratorypressure was effective in delaying the passage of fluid around thecuffs of tracheal tubes both in vivo and in vitro. The SealGuardtube proved to be more resistant to leakage than Hi-Lo

We outline the architecture of a modular Trust Layer that can be superimposed to generic semantic Web-style metadata generation facilities. Also, we propose an experimental setting to generate and validate trust assertions on classification metadata generated by different tools (including our ClassBuilder) after a process of metadata standardization. Our experimentation is aimed at validating the role of our Trust Layer as a non-intrusive, user-centered quality improver for automatically generated metadata. © 2006 Springer-Verlag Berlin Heidelberg

We describe a case of a severely mentally disabled patient diagnosed as suffering from Guillain-Barre syndrome and treated with repeated plasma exchange. However, the abrupt onset of a cardiovascular collapse prompted a more in-depth diagnostic workup which demonstrated that the neurologic symptoms were likely to be ascribed to poisoning with heavy metals from a large number of ingested coins and other metallic items.

To evaluate the symptoms, the associated lesions, the treatment and the outcome of patients with blunt carotid injury (BCI), we reviewed the records of all patients admitted to our intensive care unit with head trauma between May 1991 and May 1995. A patient's assessment included the commonly used severity scores and cranial computed tomography (CT). Other diagnostic investigations were performed according to the clinical setting. Four patients (2 males, 2 females, age 29 +/- 13 years) out of 145 were diagnosed to have BCI. At admission, the Glasgow Coma Scale (GCS) was > or = 12 in all patients, and was associated with hemiparesis in three of them; the fourth became paretic 48 hours later. No pathological elements were demonstrated at the initial CT scan, whilst subsequent examinations showed signs of ischaemia after a variable interval from admission. In every patient the radiologic investigations demonstrated a thrombotic obstruction of the internal carotid artery (ICA), associated with an intimal dissection in two cases. Three patients were discharged with only minor neurologic symptoms. The fourth patient was referred to our ICU after the development of a massive hemispheric infarction, and died 3 days after admission. Language: en

Database outsourcing is becoming increasingly popular introducing a new paradigm, called database-as-a-service, where an encrypted client's database is stored at an external service provider. Existing proposals for querying encrypted databases are based on the association, with each encrypted tuple, of additional indexing information obtained from the plaintext values of attributes that can be used in the queries. However, the relationship between indexes and data should not open the door to inference and linking attacks that can compromise the protection granted by encryption.

In this paper, we propose a general-purpose Trust Layer that fits and exploits the emerging concept of Social Web. Key features of our proposal are the consideration of several dimensions for trust computation and the exploitation of social interaction dynamics over the Web, through the definition and the evaluation of event patterns and trust rules. Besides presenting our trust model, we discuss a case study on the ACM Digital Library social environment.

The aims of the study were to analyze the clinical and epidemiological characteristics and treatments for patients who developed zygomycosis enrolled in Italy during the European Confederation of Medical Mycology of medical mycology survey. This prospective multicenter study was performed between 2004 and 2007 at 49 italian Departments. 60 cases of zygomycosis were enrolled: the median age was 59.5 years (range 1-87), with a prevalence of males (70%). The majority of cases were immunocompromised patients (42 cases, 70%), mainly hematological malignancies (37). Among non-immunocompromised (18 cases, 30%), the main category was represented by patients with penetrating trauma (7/18, 39%). The most common sites of infection were sinus (35%) with/without CNS involvement, lung alone (25%), skin (20%), but in 11 cases (18%) dissemination was observed. According to EORTC criteria, the diagnosis of zygomycosis was proven in 46 patients (77%) and in most of them it was made in vivo (40/46 patients, 87%); in the remaining 14 cases (23%) the diagnosis was probable. 51 patients received antifungal therapy and in 30 of them surgical debridement was also performed. The most commonly used antifungal drug was liposomal amphotericin B (L-AmB), administered in 44 patients: 36 of these patients (82%) responded to therapy. Altogether an attributable mortality rate of 32% (19/60) was registered, which was reduced to 18% in patients treated with L-AmB (8/44). Zygomycosis is a rare and aggressive filamentous fungal infection, still associated with a high mortality rate. This study indicates an inversion of this trend, with a better prognosis and significantly lower mortality than that reported in the literature. It is possible that new extensive, aggressive diagnostic and therapeutic procedures, such as the use of L-AmB and surgery, have improved the prognosis of these patients.