Does emotion influence the use of auto-suggest during smartphone typing?

Typing based interfaces are common across many mobile applications, especially messaging apps. To reduce the difficulty of typing using keyboard applications on smartphones, smartwatches with restricted space, several techniques, such as auto-complete, auto-suggest, are implemented. Although helpful, these techniques do add more cognitive load on the user. Hence beyond the importance to improve the word recommendations, it is useful to understand the pattern of use of auto-suggestions during typing. Among several factors that may influence use of auto-suggest, the role of emotion has been mostly overlooked, often due to the difficulty of unobtrusively inferring emotion. With advances in affective computing, and ability to infer user's emotional states accurately, it is imperative to investigate how auto-suggest can be guided by emotion aware decisions. In this work, we investigate correlations between user emotion and usage of auto-suggest i.e. whether users prefer to use auto-suggest in specific emotion states. We developed an Android keyboard application, which records auto-suggest usage and collects emotion self-reports from users in a 3-week in-the-wild study. Analysis of the dataset reveals relationship between user reported emotion state and use of auto-suggest. We used the data to train personalized models for predicting use of auto-suggest in specific emotion state. The model can predict use of auto-suggest with an average accuracy (AUCROC) of 82% showing the feasibility of emotion-aware auto-suggestion

Acute muscle dystonia resulting from medication error: a case report

Acute Muscle Dystonia (AMD) due to medication error is rarely reported in the literature. We are reporting a case of adverse drug reaction due to a single dose of haloperidol. Patient was free from any psychiatric illness and still he developed AMD with use of haloperidol because of medication error. The patient recovered completely from AMD symptoms in one hour after receiving the treatment. This case report intends to improve the awareness among clinicians to be cautious while writing the prescriptions

Emotion detection from touch interactions during text entry on smartphones

There are different modes of interaction with a software keyboard on a smartphone, such as typing and swyping. Patterns of such touch interactions on a keyboard may reflect emotions of a user. Since users may switch between different touch modalities while using a keyboard, therefore, automatic detection of emotion from touch patterns must consider both modalities in combination to detect the pattern. In this paper, we focus on identifying different features of touch interactions with a smartphone keyboard that lead to a personalized model for inferring user emotion. Since distinguishing typing and swyping activity is important to record the correct features, we designed a technique to correctly identify the modality. The ground truth labels for user emotion are collected directly from the user by periodically collecting self-reports. We jointly model typing and swyping features and correlate them with user provided self-reports to build a personalized machine learning model, which detects four emotion states (happy, sad, stressed, relaxed). We combine these design choices into an Android application TouchSense and evaluate the same in a 3-week in-the-wild study involving 22 participants. Our key evaluation results and post-study participant assessment demonstrate that it is possible to predict these emotion states with an average accuracy (AUCROC) of 73% (std dev. 6%, maximum 87%) combining these two touch interactions only

Comparison of Indian package inserts in public and private sector: an urgent need for self regulation

Background: Package inserts are the authentic source of information for the new molecules in the market. Incomplete and incorrect product information may promote irrational prescribing and may have serious consequences. Hence, our aim was to analyse and compare the information supplied in the package insert according to the section 6.2 and section 6.3 of schedule D of Drugs and Cosmetic Act, 1940 in public (government) and private (non-government) sector.Methods: Package inserts of allopathic drugs which were supplied by government from drug store of tertiary care centre and hospital and from pharmacies on request were collected. A total of 270 package inserts in English were collected that is 38 from government hospital and 232 from the pharmacies nearby the hospital. The package inserts were analysed for the presentation of completeness of the information as per section 6.2 and 6.3.Results: The presentation of information on analysing 233 package inserts (28 government and 205 non government) was not uniform and it was difficult to locate and retrieve information easily due to lack of common layout and heading. Moreover, the package inserts were of variable shape and size with different font size which made it inconvenient for analysing as well as for reference. Posology and method of administration was incomplete in 3% package insert in non- government cases whereas in government supply it was 7%. Use of drug in pregnancy and lactation was deficient in 11% and 14% packages inserts of non-government sources and government sources respectively. Instructions for use were lacking in 25% and 29% package inserts of government and non-government sources respectively.Conclusions: The need of the hour is to further refine contents of the circulated package inserts to make them complete, reliable and up to date. This can be a step forward for ethical and effective dissemination of healthcare services in our growing society

The SunPy Project: Open Source Development and Status of the Version 1.0 Core Package

The goal of the SunPy project is to facilitate and promote the use and development of community-led, free, and open source data analysis software for solar physics based on the scientific Python environment. The project achieves this goal by developing and maintaining the sunpy core package and supporting an ecosystem of affiliated packages. This paper describes the first official stable release (version 1.0) of the core package, as well as the project organization and infrastructure. This paper concludes with a discussion of the future of the SunPy project

Comparison of nebivolol and atenolol on blood pressure, blood sugar, and lipid profile in patients of essential hypertension

Background: Nebivolol is a third-generation β-blocker, with highest β1 selectivity and nitric-oxide-derived vasodilatation. It also exhibits antiproliferative and antioxidant property that has beneficial metabolic profile compared to second-generation β blockers like atenolol. This study was planned to study the comparative effects of nebivolol and atenolol on metabolic parameters in patients with essential hypertension. Materials and Methods: A prospective, randomized, parallel, open-label clinical study was carried out on patients with essential hypertension. The patients were randomly assigned to receive tablet atenolol (Group A) and nebivolol (Group B) for a period of 24 weeks. Investigations were carried out at baseline and at the end of study period, that is, 24 weeks. Out of 69 patients, 60 completed the study and the data was analyzed using student′s t-test. P < 0.05 was considered statistically significant. Results: Atenolol and nebivolol both showed significant (P < 0.001) antihypertensive action after 24 weeks. Mean blood sugar and lipid profile were found to be significantly (P < 0.001) elevated after 24 weeks of treatment with atenolol but not with nebivolol. Heart rate was significantly (P < 0.001) decreased in both groups at 24 weeks. Conclusion: In view of metabolic adverse effects of atenolol, nebivolol is the better choice whenever β-blockers have to be used in essential hypertension

Comparison of efficacy, safety and cost-effectiveness of rupatadine and olopatadine in patients of chronic spontaneous urticaria: A randomized, double-blind, comparative, parallel group trial

Objective: To compare efficacy, safety and cost-effectiveness of rupatadine and olopatadine in patients of chronic spontaneous urticaria. Materials and Methods: A 6-week, single-centered, randomized, double blind, parallel group comparative clinical study was conducted on patients with chronic spontaneous urticaria. Following inclusion and exclusion criteria, 60 patients were recruited and were randomized to two treatment groups and received the respective drugs for 6 weeks. At follow-up, parameters assessed were mean total symptom score (MTSS) calculated by adding the mean number of wheals (MNW) and the mean pruritus score (MPS), number of wheals, size of wheal, scale for interference of wheals with sleep (SIWS). Results: Both the drugs significantly reduced the MTSS, number of wheals, size of wheal, scale for interference of wheals with sleep, but olopatadine was found to be superior. In olopatadine group, there was significantly higher reduction in MTSS (p = 0.01), Number of wheals (P < 0.05), Size of wheals (p < 0.05), Scale for intensity of erythema (p < 0.05) and change in eosinopils count (p = 0.015) than that of rupatadine. Incidence of adverse effects was found to be less in olopatadine group when compared with rupatadine group. Cost effectiveness ratio was less in olopatadine group as compared to rupatadine group throughout the treatment. Conclusions: Olopatadine is a better choice in chronic spontaneous urticaria in comparison to rupatadine due to its better efficacy, safety and cost effectiveness profile