Irritable bowel syndrome in Iranian young adults: A survey among medical students

A cross-sectional study on medical students at the Golestan University of Medical Sciences in Iran was conducted to determine the prevalence of IBS and to assess the symptom subgroups based on the predominant bowel habit. A vaild self report questionnaries based on ROM II criteria was administered to all the medical students. Comparison between groups was assessed using the Chi-square and Fishers Exatct analytical tests. Of 708 questionnaires, 513 complete responses were received (response rate of 87.4%). Fifty (10.6%) subjects reported symptoms consistent with the diagnosis of IBS, predominantly in women. Forty (77.4%) and three (7.1%) were of the constipation-predominant and diarrhea-predominant subgroups, respectively. Six (12.2%) subjects fell into the non-specific IBS subgroup. The mean age of the IBS group was 22.6±2 years. IBS rate was higher in married students (15.2%) than singles (9.7%). There were no significant differences regarding sex, age, marital status and place of residence in the IBS and non-IBS groups. 57.1% (n = 28) of the medical students had consulted their healthcare practitioner for their symptoms. Hospitalization and endoscopic procedures were reported in 3 (6.1%) of cases. Self-medication was reported in 55.1% (n = 27) of subjects. Based on this study, the prevalence of IBS in young Iranian population are higher than previously expected that deserves greater care and further investigation

Structured Query Translation in Peer to Peer Database Sharing Systems

This paper presents a query translation mechanism between heterogeneous peers in Peer to Peer Database Sharing Systems (PDSSs). A PDSS combines a database management system with P2P functionalities. The local databases on peers are called peer databases. In a PDSS, each peer chooses its own data model and schema and maintains data independently without any global coordinator. One of the problems in such a system is translating queries between peers, taking into account both the schema and data heterogeneity. Query translation is the problem of rewriting a query posed in terms of one peer schema to a query in terms of another peer schema. This paper proposes a query translation mechanism between peers where peers are acquainted in data sharing systems through data-level mappings for sharing data

Internalization among Technology Entrepreneurs: Looking to the Future While Grounded in the Past

The dynamic knowledge creation process, traditionally described and applied in the context of large firms, is receiving growing attention in entrepreneurship research as a model to identify ways to decrease mortality rates in the valley of death, the stage of entrepreneurship infamously known for the high percentage of startup failures. Prior innovation literature associates entrepreneurship activities with the socialization phase of Nonaka’s dynamic theory of knowledge creation (also known as the SECI model). However, linguistic analysis of interviews with entrepreneurs indicates that internalization (i.e., the creation of tacit knowledge from explicit assets) plays an important role in new ventures activities. In this study, we distinguish between internalization in the current venture from internalization during the entrepreneur’s prior employment. We find a strong relationship between references to the past and internalization that is mediated by negative emotions, which may have motivated the entrepreneur to leave prior employment and launch a new venture. We also find a strong relationship between an entrepreneur’s references to the past and the number of employees in the venture, indicative of the importance of an entrepreneur’s prior knowledge internalization to the current venture. This research contributes to the growing field of entrepreneurial knowledge management by extending the role of the entrepreneur’s past knowledge creation activities to those of her/his new venture. It underscores the common tagline that we can learn more from our failures (negative emotions)

Secure Mobile Automation of Ecological Momentary Assessments (EMA) For Structured Querying

The ubiquitous nature of mobile devices like smartphones and tablets make them ideal platforms for engaging users in Ecological Momentary Assessments (EMA). In EMA, participants are repeatedly assessed frequently (daily or multiple times per day) through a set of questionnaires. Fluctuations in psychological states, such as cognition and eect can be recorded in real time using mobile devices. EMA results can further be coupled with other physiological sensor data procured through wearables and smartphones, to validate and correlate patient experiences and responses to certain treatments and medications. This can be useful for health care organizations which are interested in the impact of their treatment techniques on patient populations. In this paper, we present an EMA platform developed using Android mobile devices. The collected results are shown and techniques used to query the data are demonstrated. The platform is flexible and can scale up to perform data mining algorithms for sentiment analysis based on the stimulus to a medication or treatment over a prolonged period of time

A tool for speech act classification using interactive machine learning

In this Demo, we introduce a tool that provides a GUI interface to a previously designed to Speech Act Classifier. The tool also provides features to manually annotate data by human and evaluate and improve the automated classifier. We describe the interface and evaluate our model with results from two human judges and Computer

Intelligent networked navigation of mobile robots with collision avoidance

A major part of mobile robotics research is focused on the navigation of a team of networked mobile robots in indoor and/or outdoor environments. The navigation is indeed an important module as it allows necessary control operations for mobile robots. In addition, this module empowers robots to maneuver efficiently and effectively. In most cases, this task requires an accurate mathematical model of the environment, path, and trajectory of robots. The fuzzy logic-based robot navigation strategy proved its power when mathematical models of robots and their operating environments are unknown precisely. In this paper, we propose a full-fledged robot navigation strategy where a team of mobile robots navigates along a predefined set of waypoints in an indoor environment while avoiding a collision. The proposed navigation system consists of two parts that are currently being developed. The first part of the navigation system described in this paper is the fuzzy logic control, which determines appropriate actuator commands for the robots' actuators. The second part is the Petri-net model. While the former part is employed to avoid obstacles and reaching waypoints, the latter one illustrates a collision avoidance strategy among multiple robots. A part of theoretical results presented in this paper is backed up by computer simulations

Visual Development Process for Automatic Generation of Digital Games Narrative Content

Users of Natural Language Generation systems are required to have sophisticated linguistic and sometimes even programming knowledge, which has hindered the adoption of this technology by individuals outside the computational linguistics research community. We have designed and implemented a visual environment for creating and modifying NLG templates which requires no programming ability and minimum linguistic knowledge. It allows specifying templates with any number of variables and dependencies between them. Internally, i