How Twitter is studied in the medical professions: a classification of Twitter papers indexed in PubMed

Background: Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. // Objective: This paper aims to identify published work relating to Twitter indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Limiting the study to papers indexed by PubMed ensures the work provides a reproducible benchmark. // Methods: Papers, indexed by PubMed, on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper’s title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain and aspect. // Results: As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focussed on Twitter (the others referring to it tangentially). The early Twitter focussed papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that researchers are starting to use knowledge discovery methods and data mining techniques to understand vast quantities of tweets: the study of Twitter is becoming quantitative research. // Conclusions: This work is to the best of our knowledge the first overview study of medical related research based on Twitter and related microblogging. We have used five dimensions to categorise published medical related research on Twitter. This classification provides a framework within which researchers studying development and use of Twitter within medical related research, and those undertaking comparative studies of research relating to Twitter in the area of medicine and beyond, can position and ground their work.

A Linguistic Analysis of Spanglish: Relating Language to Identity.

According to the 2000 census, 35.3 million Hispanics live in the United States. This number comprises 12.5% of the overall population rendering the Latino community the largest minority in the United States. The Mexican community is not only the largest Hispanic group but also the fastest growing: from 1990 to 2000, the Mexican population grew 52.9% increasing from 13.5 million to 20.6 million (U.S. Department of Commerce News, 2001). The influx of Mexican immigrants coupled with the expansion of their community within the United States has created an unparalleled situation of language contact. Language is synonymous with identity (cf. Granger, 2004, and works cited within). To the extent that this is true, Spanish is synonymous with being Mexican and by extension, Chicano. With the advent of amnesty programs such as Immigration Reform and Control Act (IRCA), which naturalized millions of Mexican migrants, what was once a temporal migratory population has become increasingly permanent (Durand et al., 1999). In an effort to conserve Mexican traditions and identity, the struggle to preserve the mother tongue while at the same time acculturate to mainstream Americana has resulted in a variant of Spanglish that has received little attention. This paper will examine the variant of Spanglish seen in the greater Los Angeles area and liken it to the bi-national identity under which these Mexican Americans thrive.

Phylogenetic relationships and infrageneric classification of Epidendrum subgenus Amphiglottium (Laeliinae, Orchidaceae)

Epidendrum L. is the largest genus of Orchidaceae in the Neotropical region; it has an impressive morphological diversification, which imposes difficulties in delimitation of both infrageneric and interspecific boundaries. In this study, we review infrageneric boundaries within the subgenus Amphiglottium and try to contribute to the understanding of morphological diversification and taxa delimitation within this group. We tested the monophyly of the subgenus Amphiglottium sect. Amphiglottium, expanding previous phylogenetic investigations and reevaluated previous infrageneric classifications proposed. Sequence data from the trnL-trnF region were analyzed with both parsimony and maximum likelihood criteria. AFLP markers were also obtained and analyzed with phylogenetic and principal coordinate analyses. Additionally, we obtained chromosome numbers for representative species within the group. The results strengthen the monophyly of the subgenus Amphiglottium but do not support the current classification system proposed by previous authors. Only section Tuberculata comprises a well-supported monophyletic group, with sections Carinata and Integra not supported. Instead of morphology, biogeographical and ecological patterns are reflected in the phylogenetic signal in this group. This study also confirms the large variability of chromosome numbers for the subgenus Amphiglottium (numbers ranging from 2n = 24 to 2n = 240), suggesting that polyploidy and hybridization are probably important mechanisms of speciation within the group.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

SESAME: Finding Ways Of Promoting SME Adaptation To Flood Risk

Small and medium-sized companies and other enterprises (SMEs) around the world are exposed to flood risk and many of the 4.5 million in the UK are at risk. As SMEs represent almost half of total business turnover in the UK, their protection is a vital part of the drive for greater climate change resilience. However, few have measures in place to ensure the continuity of their activities during a flood and its aftermath. The SESAME project aims to develop tools that encourage businesses to discover ways of becoming more resilient to floods and to appreciate how much better off they will be once they have adapted to the ongoing risk. By taking some of the mystery out of flooding and flood risk, it aims to make it susceptible to the same business acumen that enables the UK’s SMEs to deal with the many other challenges they face. In this paper we will report on the different aspects of the research in the project Understanding behaviour Changing behaviour Modelling impacts Economic impacts Through the above the project will advise government, local authorities and other public bodies on how to improve their responses to floods and will enable them to recommend ways to improve the guidelines provided to SMEs in flood risk areas.

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

Early administration of inhaled nitric oxide to children with acute respiratory distress syndrome and its effects on oxygenation and ventilator settings: prospective preliminary report of ten patients

Aim. To establish a protocol for the early introduction of inhaled nitric oxide (iNO) therapy in children with acute respiratory distress syndrome (ARDS) and to assess its acute and sustained effects on oxygenation and ventilator settings.Patients and Methods. Ten children with ARDS, aged 1 to 132 months (median, 11 months), with arterial saturation of oxygen <88% while receiving a fraction of inspired oxygen (FiO(2)) to>0.6 and a positive end-expiratory pressure of greater than or equal to 10 cm H2O were included in the study. The acute response to iNO was assessed in a 4-hour dose-response test, and positive response was defined as an increase in the PaO2/FiO(2) ratio of 10 mmHg above baseline values. Conventional therapy was not changed during the test. In the following days, patients who had shown positive response continued to receive the lowest iNO dose. Hemodynamics, PaO2/FiO(2), oxygenation index, gas exchange, and methemoglobin levels were obtained when needed. Inhaled nitric oxide withdrawal followed predetermined rules.Results. At the end of the 4-hour test, all the children showed significant improvement in the PaO2/FiO(2) ratio (63.6%) and the oxygenation index (44.9%) compared with the baseline values. Prolonged treatment was associated with improvement in oxygenation, so that FiO(2) and peak inspiratory pressure could be quickly and significantly reduced., No toxicity from methemoglobin or nitrogen dioxide was observed.Conclusion. Administration of iNO to children is safe. iNO causes rapid and sustained improvement in oxygenation without adverse effects. Ventilator settings can safely be reduced during iNO treatment.

Classification of normal swallowing and oropharyngeal dysphagia using wavelet

Oropharyngeal dysphagia is characterized by any alteration in swallowing dynamics which may lead to malnutrition and aspiration pneumonia. Early diagnosis is crucial for the prognosis of patients with dysphagia, and the best method for swallowing dynamics assessment is swallowing videofluoroscopy, an exam performed with X-rays. Because it exposes patients to radiation, videofluoroscopy should not be performed frequently nor should it be prolonged. This study presents a non-invasive method for the pre-diagnosis of dysphagia based on the analysis of the swallowing acoustics, where the discrete wavelet transform plays an important role to increase sensitivity and specificity in the identification of dysphagic patients. (C) 2008 Elsevier B.V. All rights reserved.

The plethysm technique applied to the classification of nuclear states

A short summary of the theory of symmetric group and symmetric functions needed to follow the theory of Schur functions and plethysms is presented. One then defines plethysm, gives its properties and presents a procedure for its calculation. Finally, some aplications in atomic physics and nuclear structure are given.

Two-way regionalized classification of multivariate datasets and its application to the assessment of hydrodynamic dispersion

Zones of mixing between shallow groundwaters of different composition were unravelled by two-way regionalized classification, a technique based on correspondence analysis (CA), cluster analysis (ClA) and discriminant analysis (DA), aided by gridding, map-overlay and contouring tools. The shallow groundwaters are from a granitoid plutonite in the Funda o region (central Portugal). Correspondence analysis detected three natural clusters in the working dataset: 1, weathering; 2, domestic effluents; 3, fertilizers. Cluster analysis set an alternative distribution of the samples by the three clusters. Group memberships obtained by correspondence analysis and by cluster analysis were optimized by discriminant analysis, gridded memberships as follows: codes 1, 2 or 3 were used when classification by correspondence analysis and cluster analysis produced the same results; code 0 when the grid node was first assigned to cluster 1 and then to cluster 2 or vice versa (mixing between weathering and effluents); code 4 in the other cases (mixing between agriculture and the other influences). Code-3 areas were systematically surrounded by code-4 areas, an observation attributed to hydrodynamic dispersion. Accordingly, the extent of code-4 areas in two orthogonal directions was assumed proportional to the longitudinal and transverse dispersivities of local soils. The results (0.7-16.8 and 0.4-4.3 m, respectively) are acceptable at the macroscopic scale. The ratios between longitudinal and transverse dispersivities (1.2-11.1) are also in agreement with results obtained by other studies.

Acute and sustained effects of early administration of inhaled nitric oxide to children with acute respiratory distress syndrome

OBJECTIVE: To determine the acute and sustained effects of early inhaled nitric oxide on some oxygenation indexes and ventilator settings and to compare inhaled nitric oxide administration and conventional therapy on mortality rate, length of stay in intensive care, and duration of mechanical ventilation in children with acute respiratory distress syndrome. DESIGN: Observational study. SETTING: Pediatric intensive care unit at a university-affiliated hospital. PATIENTS: Children with acute respiratory distress syndrome, aged between 1 month and 12 yrs. INTERVENTIONS: Two groups were studied: an inhaled nitric oxide group (iNOG, n = 18) composed of patients prospectively enrolled from November 2000 to November 2002, and a conventional therapy group (CTG, n = 21) consisting of historical control patients admitted from August 1998 to August 2000. MEASUREMENTS AND MAIN RESULTS: Therapy with inhaled nitric oxide was introduced as early as 1.5 hrs after acute respiratory distress syndrome diagnosis with acute improvements in Pao(2)/Fio(2) ratio (83.7%) and oxygenation index (46.7%). Study groups were of similar ages, gender, primary diagnoses, pediatric risk of mortality score, and mean airway pressure. Pao(2)/Fio(2) ratio was lower (CTG, 116.9 +/- 34.5; iNOG, 62.5 +/- 12.8, p <.0001) and oxygenation index higher (CTG, 15.2 [range, 7.2-32.2]; iNOG, 24.3 [range, 16.3-70.4], p <.0001) in the iNOG. Prolonged treatment was associated with improved oxygenation, so that Fio(2) and peak inspiratory pressure could be quickly and significantly reduced. Mortality rate for inhaled nitric oxide-patients was lower (CTG, ten of 21, 47.6%; iNOG, three of 18, 16.6%, p <.001). There was no difference in intensive care stay (CTG, 10 days [range, 2-49]; iNOG, 12 [range, 6-26], p >.05) or duration of mechanical ventilation (TCG, 9 days [range, 2-47]; iNOG, 10 [range, 4-25], p >.05). CONCLUSIONS: Early treatment with inhaled nitric oxide causes acute and sustained improvement in oxygenation, with earlier reduction of ventilator settings, which might contribute to reduce the mortality rate in children with acute respiratory distress syndrome. Length of stay in intensive care and duration of mechanical ventilation are not changed. Prospective trials of inhaled nitric oxide early in the setting of acute lung injury in children are needed.

Draft amendments to the standard external trade statistics classification of East Caribbean Common Market Countries

Includes bibliography

Development of a CAD system for automatic classification of microcalcifications based on FPGA

This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.