Detecting modification of biomedical events using a deep parsing approach

<p>Abstract</p> <p>Background</p> <p>This work describes a system for identifying event mentions in bio-molecular research abstracts that are either speculative (e.g. <it>analysis of IkappaBalpha phosphorylation</it>, where it is not specified whether phosphorylation did or did not occur) or negated (e.g. <it>inhibition of IkappaBalpha phosphorylation</it>, where phosphorylation did <it>not </it>occur). The data comes from a standard dataset created for the BioNLP 2009 Shared Task. The system uses a machine-learning approach, where the features used for classification are a combination of shallow features derived from the words of the sentences and more complex features based on the semantic outputs produced by a deep parser.</p> <p>Method</p> <p>To detect event modification, we use a Maximum Entropy learner with features extracted from the data relative to the trigger words of the events. The shallow features are bag-of-words features based on a small sliding context window of 3-4 tokens on either side of the trigger word. The deep parser features are derived from parses produced by the English Resource Grammar and the <it>RASP </it>parser. The outputs of these parsers are converted into the Minimal Recursion Semantics formalism, and from this, we extract features motivated by linguistics and the data itself. All of these features are combined to create training or test data for the machine learning algorithm.</p> <p>Results</p> <p>Over the test data, our methods produce approximately a 4% absolute increase in F-score for detection of event modification compared to a baseline based only on the shallow bag-of-words features.</p> <p>Conclusions</p> <p>Our results indicate that grammar-based techniques can enhance the accuracy of methods for detecting event modification.</p

The Effects of Twitter Sentiment on Stock Price Returns

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-know micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events

Intraoperative tracheal reconstruction with bovine pericardial patch following iatrogenic rupture

<p>Abstract</p> <p>Introduction</p> <p>Iatrogenic injuries of the membranous trachea have become increasingly common and may trigger a cascade of immediate life-threatening complications.</p> <p>Case presentation</p> <p>A case of a 48-year-old man with an iatrogenic membranous tracheal wall rupture after double-lumen intubation during Ivor Lewis esophagogastrectomy is presented. Tracheal injury was successfully managed surgically with the use of bovine pericardial patch and reinforcement with the gastric conduit which was moved toward the posterior wall of the membranous trachea sealing the wall laceration.</p> <p>Conclusion</p> <p>Our technique was proved to be safe, effective and not technically demanding. Early recognition with prompt surgery is the gold standard of managing such cases, although small tears can be managed conservatively.</p

'Everyday memory' impairments in autism spectrum disorders

‘Everyday memory’ is conceptualised as memory within the context of day-to-day life and, despite its functional relevance, has been little studied in individuals with autism spectrum disorders (ASDs). In the first study of its kind, 94 adolescents with an ASD and 55 without an ASD completed measures of everyday memory from the Rivermead Behavioural Memory Test (RBMT) and a standard word recall task (Children’s Auditory Verbal Learning Test-2: CAVLT-2). The ASD group showed significant impairments on the RBMT, including in prospective memory, alongside impaired performance on the CAVLT-2. Social and communication ability was significantly associated with prospective remembering in an everyday memory context but not with the CAVLT-2. The complex nature of everyday memory and its relevance to ASD is discussed

Towards a greater dialogue on disability between Muslims and Christians

Attitudes to disability and disabled people by Muslims – focusing on attitudes in the Middle East and North Africa - and Christians – focusing on the West (here taken to mean Europe, North America and Australasia) - were examined through a grounded theory literature search, with the study being divided into three phases of reading and analysis. The aims of study were to develop a dialogue on disability between the two cultures, to inform an understanding of the attitudes to disability in the two cultures, and to inform cultural practice in promoting support and equality in both cultures. The study finds that Islam and Christianity have much in common and are a force for good in promoting and developing disability equality in both Muslim and Christian cultures

A Close Eye on the Eagle-Eyed Visual Acuity Hypothesis of Autism

Autism spectrum disorders (ASD) have been associated with sensory hypersensitivity. A recent study reported visual acuity (VA) in ASD in the region reported for birds of prey. The validity of the results was subsequently doubted. This study examined VA in 34 individuals with ASD, 16 with schizophrenia (SCH), and 26 typically developing (TYP). Participants with ASD did not show higher VA than those with SCH and TYP. There were no substantial correlations of VA with clinical severity in ASD or SCH. This study could not confirm the eagle-eyed acuity hypothesis of ASD, or find evidence for a connection of VA and clinical phenotypes. Research needs to further address the origins and circumstances associated with altered sensory or perceptual processing in ASD

FinTech revolution: the impact of management information systems upon relative firm value and risk

The FinTech or ‘financial technology’ revolution has been gaining increasing interest as technologies are fundamentally changing the business of financial services. Consequently, financial technology is playing an increasingly important role in providing relative performance growth to firms. It is also well known that such relative performance can be observed through pairs trading investment. Therefore pairs trading have implications for understanding financial technology performance, yet the relationships between relative firm value and financial technology are not well understood. In this paper we investigate the impact of financial technology upon relative firm value in the banking sector. Firstly, using pairs trade data we show that financial technologies reveal differences in relative operational performance of firms, providing insight on the value of financial technologies. Secondly, we find that contribution of relative firm value growth from financial technologies is dependent on the specific business characteristics of the technology, such as the business application and activity type. Finally, we show that financial technologies impact the operational risk of firms and so firms need to take into account both the value and risk benefits in implementing new technological innovations. This paper will be of interest to academics and industry professionals