Concept: Word processor
The choice of an efficient document preparation system is an important decision for any academic researcher. To assist the research community, we report a software usability study in which 40 researchers across different disciplines prepared scholarly texts with either Microsoft Word or LaTeX. The probe texts included simple continuous text, text with tables and subheadings, and complex text with several mathematical equations. We show that LaTeX users were slower than Word users, wrote less text in the same amount of time, and produced more typesetting, orthographical, grammatical, and formatting errors. On most measures, expert LaTeX users performed even worse than novice Word users. LaTeX users, however, more often report enjoying using their respective software. We conclude that even experienced LaTeX users may suffer a loss in productivity when LaTeX is used, relative to other document preparation systems. Individuals, institutions, and journals should carefully consider the ramifications of this finding when choosing document preparation strategies, or requiring them of authors.
Objectives: The International Classification of Diseases and Related Health Problems, 10th Revision, Thai Modification (ICD-10-TM) ontology is a knowledge base created from the Thai modification of the World Health Organization International Classification of Diseases and Related Health Problems, 10th Revision. The objectives of this research were to develop the ICD-10-TM ontology as a knowledge base for use in a semi-automated ICD coding system and to test the usability of this system. Methods: ICD concepts and relations were identified from a tabular list and alphabetical indexes. An ICD-10-TM ontology was defined in the resource description framework (RDF), notation-3 (N3) format. All ICD-10-TM contents available as Microsoft Word documents were transformed into N3 format using Python scripts. Final RDF files were validated by ICD experts. The ontology was implemented as a knowledge base by using a novel semi-automated ICD coding system. Evaluation of usability was performed by a survey of forty volunteer users. Results: The ICD-10-TM ontology consists of two main knowledge bases (a tabular list knowledge base and an index knowledge base) containing a total of 309,985 concepts and 162,092 relations. The tabular list knowledge base can be divided into an upper level ontology, which defines hierarchical relationships between 22 ICD chapters, and a lower level ontology which defines relations between chapters, blocks, categories, rubrics and basic elements (include, exclude, synonym etc.) of the ICD tabular list. The index knowledge base describes relations between keywords, modifiers in general format and a table format of the ICD index. In this research, the creation of an ICD index ontology revealed interesting findings on problems with the current ICD index structure. One problem with the current structure is that it defines conditions that complicate pregnancy and perinatal conditions on the same hierarchical level as organ system diseases. This could mislead a coding algorithm into a wrong selection of ICD code. To prevent these coding errors by an algorithm, the ICD-10-TM index structure was modified by raising conditions complicating pregnancy and perinatal conditions into a higher hierarchical level of the index knowledge base. The modified ICD-10-TM ontology was implemented as a knowledge base in semi-automated ICD-10-TM coding software. A survey of users of the software revealed a high percentage of correct results obtained from ontology searches (>95%) and user satisfaction on the usability of the ontology. Conclusion: The ICD-10-TM ontology is the first ICD-10 ontology with a comprehensive description of all concepts and relations in an ICD-10-TM tabular list and alphabetical index. A researcher developing an automated ICD coding system should be aware of The ICD index structure and the complexity of coding processes. These coding systems are not a word matching process. ICD-10 ontology should be used as a knowledge base in The ICD coding software. It can be used to facilitate successful implementation of ICD in developing countries, especially in those countries which do not have an adequate number of competent ICD coders.
Inexpensive software applications designed to teach reading, writing, mathematics, and other academic areas have become increasingly popular. Although previous research has demonstrated the potential efficacy of such applications, there is a paucity of research that compares applications instruction (AI) with traditional teacher-directed instruction (TDI), and the relative effectiveness and efficiency of these instructional approaches remains largely unknown. This study used an alternating treatment design to compare academic engagement and outcomes (i.e., word identification and reading fluency) during an AI condition and a TDI condition for four students with learning disabilities (LD) attending a charter school. Instructional conditions (i.e., TDI, AI) were randomly alternated 7 times each, for a total of 14 instructional sessions. Results indicated that both approaches fostered high levels of engagement although students were more engaged during AI. With regard to academic performance, visual and quantitative analysis suggest that TDI was more effective than AI in terms of passage fluency and word identification. Students completed social validity rating scales to examine instructional preference. Results indicated that both approaches, TDI and AI, were popular with the students.
Twitter is a widely used social medium. However, its application in promoting health behaviors is understudied.
Electronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another.
SUMMARY: Numerous metagenomics projects have produced tremendous amounts of sequencing data. Aligning these sequences to reference genomes is an essential analysis in metagenomics studies. Large-scale alignment data call for intuitive and efficient visualization tool. However, current tools such as various genome browsers are highly specialized to handle intraspecies mapping results. They are not suitable for alignment data in metagenomics, which are often interspecies alignments. We have developed a web browser-based desktop application for interactively visualizing alignment data of metagenomic sequences. This viewer is easy to use on all computer systems with modern web browsers and requires no software installation. AVAILABILITY: http://weizhongli-lab.org/mgaviewer CONTACT: email@example.com.
Advances in mobile telecommunication, improved mobile internet and affordability have led to a significant increase in smartphone use within medicine. The capability of instant messaging, photography, videography, word processing, drawing and internet access allow significant potential in this small portable device. Smartphone use within medicine has grown tremendously worldwide given its affordability, improved internet and capabilities.
Emotional scenes and faces have shown to capture and bind visual resources at early sensory processing stages, i.e. in early visual cortex. However, emotional words have led to mixed results. In the current study ERPs were assessed simultaneously with steady-state visual evoked potentials (SSVEPs) to measure attention effects on early visual activity in emotional word processing. Neutral and negative words were flickered at 12.14 Hz whilst participants performed a Lexical Decision Task.
This study examined emotional modulation of word processing, showing that the recognition potential (RP), an ERP index of word recognition, could be modulated by different emotional states. In the experiment, participants were instructed to compete with pseudo-competitors, and via manipulation of the outcome of this competition, they were situated in neutral, highly positive, slightly positive, highly negative or slightly negative emotional states. They were subsequently asked to judge whether the referent of a word following a series of meaningless character segmentations was an animal or not. The emotional induction task and the word recognition task were alternated. Results showed that 1) compared with the neutral emotion condition, the peak latency of the RP under different emotional states was earlier and its mean amplitude was smaller, 2) there was no significant difference between RPs elicited under positive and negative emotional states in either the mean amplitude or latency, and 3) the RP was not affected by different degrees of positive emotional states. However, compared to slightly negative emotional states, the mean amplitude of the RP was smaller and its latency was shorter in highly negative emotional states over the left hemisphere but not over the right hemisphere. The results suggest that emotional states influence word processing.
This study aimed to develop and assess a method to measure word recognition abilities using a smartphone application (App) connected to an audiometer.