Visual Dependency and Dizziness after Vestibular Neuritis

Symptomatic recovery after acute vestibular neuritis (VN) is variable, with around 50% of patients reporting long term vestibular symptoms; hence, it is essential to identify factors related to poor clinical outcome. Here we investigated whether excessive reliance on visual input for spatial orientation (visual dependence) was associated with long term vestibular symptoms following acute VN. Twenty-eight patients with VN and 25 normal control subjects were included. Patients were enrolled at least 6 months after acute illness. Recovery status was not a criterion for study entry, allowing recruitment of patients with a full range of persistent symptoms. We measured visual dependence with a laptop-based Rod-and-Disk Test and severity of symptoms with the Dizziness Handicap Inventory (DHI). The third of patients showing the worst clinical outcomes (mean DHI score 36–80) had significantly greater visual dependence than normal subjects (6.35° error vs. 3.39° respectively, p = 0.03). Asymptomatic patients and those with minor residual symptoms did not differ from controls. Visual dependence was associated with high levels of persistent vestibular symptoms after acute VN. Over-reliance on visual information for spatial orientation is one characteristic of poorly recovered vestibular neuritis patients. The finding may be clinically useful given that visual dependence may be modified through rehabilitation desensitization techniques

Hypergraph model of social tagging networks

The past few years have witnessed the great success of a new family of paradigms, so-called folksonomy, which allows users to freely associate tags to resources and efficiently manage them. In order to uncover the underlying structures and user behaviors in folksonomy, in this paper, we propose an evolutionary hypergrah model to explain the emerging statistical properties. The present model introduces a novel mechanism that one can not only assign tags to resources, but also retrieve resources via collaborative tags. We then compare the model with a real-world dataset: \emph{Del.icio.us}. Indeed, the present model shows considerable agreement with the empirical data in following aspects: power-law hyperdegree distributions, negtive correlation between clustering coefficients and hyperdegrees, and small average distances. Furthermore, the model indicates that most tagging behaviors are motivated by labeling tags to resources, and tags play a significant role in effectively retrieving interesting resources and making acquaintance with congenial friends. The proposed model may shed some light on the in-depth understanding of the structure and function of folksonomy.Comment: 7 pages,7 figures, 32 reference

A framework for deriving semantic web services

Web service-based development represents an emerging approach for the development of distributed information systems. Web services have been mainly applied by software practitioners as a means to modularize system functionality that can be offered across a network (e.g., intranet and/or the Internet). Although web services have been predominantly developed as a technical solution for integrating software systems, there is a more business-oriented aspect that developers and enterprises need to deal with in order to benefit from the full potential of web services in an electronic market. This ‘ignored’ aspect is the representation of the semantics underlying the services themselves as well as the ‘things’ that the services manage. Currently languages like the Web Services Description Language (WSDL) provide the syntactic means to describe web services, but lack in providing a semantic underpinning. In order to harvest all the benefits of web services technology, a framework has been developed for deriving business semantics from syntactic descriptions of web services. The benefits of such a framework are two-fold. Firstly, the framework provides a way to gradually construct domain ontologies from previously defined technical services. Secondly, the framework enables the migration of syntactically defined web services toward semantic web services. The study follows a design research approach which (1) identifies the problem area and its relevance from an industrial case study and previous research, (2) develops the framework as a design artifact and (3) evaluates the application of the framework through a relevant scenario

DMPP-4: Candidate sub-Neptune mass planets orbiting a naked-eye star

We present radial velocity measurements of the very bright ($V\sim5.7$) nearby F star, DMPP-4 (HD 184960). The anomalously low Ca II H&K emission suggests mass loss from planets orbiting a low activity host star. Periodic radial velocity variability with $\sim 10$ ms$^{-1}$ amplitude is found to persist over a $>4$ year timescale. Although the non-simultaneous photometric variability in four TESS sectors supports the view of an inactive star, we identify periodic photometric signals and also find spectroscopic evidence for stellar activity. We used a posterior sampling algorithm that includes the number of Keplerian signals, $N_\textrm{p}$, as a free parameter to test and compare (1) purely Keplerian models (2) a Keplerian model with linear activity correlation and (3) Keplerian models with Gaussian processes. A preferred model, with one Keplerian and quasi-periodic Gaussian process indicates a planet with a period of $P_\textrm{b} = 3.4982^{+0.0015}_{-0.0027}$ d and corresponding minimum mass of $m_\textrm{b}\,\textrm{sin}\,i = 12.2^{+1.8}_{-1.9}$ M$_\oplus$. Without further high time resolution observations over a longer timescale, we cannot definitively rule out the purely Keplerian model with 2 candidates planets with $P_\textrm{b} = 2.4570^{+0.0026}_{-0.0462}$ d, minimum mass $m_\textrm{b}\,\textrm{sin}\,i = 8.0^{+1.1}_{-1.5}$ M$_\oplus$ and $P_\textrm{c} = 5.4196^{+0.6766}_{-0.0030}$ d and corresponding minimum mass of $m_\textrm{b}\,\textrm{sin}\,i = 12.2^{+1.4}_{-1.6}$ M$_\oplus$. The candidate planets lie in the region below the lower-envelope of the Neptune Desert. Continued mass loss may originate from the highly irradiated planets or from an as yet undetected body in the system.Comment: 19 pages, 11 figures. Accepted for publication in MNRA

Brainwaves and Sound Synchronization in a Dance Performance

In a previous work (Lucchiari and Folgieri, 2015) we considered communication among young people. New digital-natives do not communicate in a traditional way, but they choose different means and ways. It is not a surprising conclusion that a large part of digital-natives considers obsolete both Web sites\u2019 structure and Internet navigation modes, learning instruments and paradigms and communication tools, choosing, instead, fast and immediate media like mobile phone communication, social networking and so on (Croitoru et al. 2011). Notwithstanding we could think they lack of communication skills, actually, they communicate with each other much more than ever done, using not only the verbal language, but also images, videos, sounds, and especially emotions. We named this phenomenon telepatheia or, better, sympateia, meaning that they seem to keep in contact independently by the mean. Of course, on our intention, this does not mean that we are observing a new organic evolution, but surely a kind of evolution can be traced: an era in which human and machines are evolving, influencing one each other, determining a specific kind of communication strongly influenced and related to technology. In this paper, starting from our previous studies and from our concept of \u201csympateia\u201d, we performed a new experiment related to brain rhythms synchronization. Through our experiment, described in the following chapter, We want to explore the communication mechanisms of telepathy (in the ancient Greek assumption of \u201ctelepatia\u201d\uf020that is [tele]=\u201ddistance\u201d and [pateia]=\u201demotion, feeling\u201d). This does not mean that we are trying to make humans telepathic, but we aim to deeply understand communication mechanisms among humans through human-computer interaction BCI devices. This means to change the point of view of brain and Information Technology researches, stressing the point of view of self-understanding of the own brain

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects

Genetic and biochemical analyses of chromosome and plasmid gene homologues encoding ICL and ArCP domains in Vibrioanguillarum strain 775

Anguibactin, the siderophore produced by Vibrio anguillarum 775 is synthesized from 2,3-dihydroxybenzoic acid (DHBA), cysteine and hydroxyhistamine via a nonribosomal peptide synthetase (NRPS) mechanism. Most of the genes encoding anguibactin biosynthetic proteins are harbored by the pJM1 plasmid. In this work we report the identification of a homologue of the plasmid-encoded angB on the chromosome of strain 775. The product of both genes harbor an isochorismate lyase (ICL) domain that converts isochorismic acid to 2,3-dihydro-2,3-dihydroxybenzoic acid, one of the steps of DHBA synthesis. We show in this work that both ICL domains are functional in the production of DHBA in V. anguillarum as well as in E. coli. Substitution by alanine of the aspartic acid residue in the active site of both ICL domains completely abolishes their isochorismate lyase activity in vivo. The two proteins also carry an aryl carrier protein (ArCP) domain. In contrast with the ICL domains only the plasmid encoded ArCP can participate in anguibactin production as determined by complementation analyses and site-directed mutagenesis in the active site of the plasmid encoded protein, S248A. The site-directed mutants, D37A in the ICL domain and S248A in the ArCP domain of the plasmid encoded AngB were also tested in vitro and clearly show the importance of each residue for the domain function and that each domain operates independently.

Good Friends, Bad News - Affect and Virality in Twitter

The link between affect, defined as the capacity for sentimental arousal on the part of a message, and virality, defined as the probability that it be sent along, is of significant theoretical and practical importance, e.g. for viral marketing. A quantitative study of emailing of articles from the NY Times finds a strong link between positive affect and virality, and, based on psychological theories it is concluded that this relation is universally valid. The conclusion appears to be in contrast with classic theory of diffusion in news media emphasizing negative affect as promoting propagation. In this paper we explore the apparent paradox in a quantitative analysis of information diffusion on Twitter. Twitter is interesting in this context as it has been shown to present both the characteristics social and news media. The basic measure of virality in Twitter is the probability of retweet. Twitter is different from email in that retweeting does not depend on pre-existing social relations, but often occur among strangers, thus in this respect Twitter may be more similar to traditional news media. We therefore hypothesize that negative news content is more likely to be retweeted, while for non-news tweets positive sentiments support virality. To test the hypothesis we analyze three corpora: A complete sample of tweets about the COP15 climate summit, a random sample of tweets, and a general text corpus including news. The latter allows us to train a classifier that can distinguish tweets that carry news and non-news information. We present evidence that negative sentiment enhances virality in the news segment, but not in the non-news segment. We conclude that the relation between affect and virality is more complex than expected based on the findings of Berger and Milkman (2010), in short 'if you want to be cited: Sweet talk your friends or serve bad news to the public'.Comment: 14 pages, 1 table. Submitted to The 2011 International Workshop on Social Computing, Network, and Services (SocialComNet 2011

Bias in data-driven artificial intelligence systems - An introductory survey

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues

Bias in data-driven artificial intelligence systems—An introductory survey

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues