Exploring personality-targeted UI design in online social participation systems

We present a theoretical foundation and empirical findings demonstrating the effectiveness of personality-targeted design. Much like a medical treatment applied to a person based on his specific genetic profile, we argue that theory-driven, personality-targeted UI design can be more effective than design applied to the entire population. The empirical exploration focused on two settings, two populations and two personality traits: Study 1 shows that users' extroversion level moderates the relationship between the UI cue of audience size and users' contribution. Study 2 demonstrates that the effectiveness of social anchors in encouraging online contributions depends on users' level of emotional stability. Taken together, the findings demonstrate the potential and robustness of the interactionist approach to UI design. The findings contribute to the HCI community, and in particular to designers of social systems, by providing guidelines to targeted design that can increase online participation. Copyright © 2013 ACM

Trends in Isolation and Antimicrobial Susceptibility of Enteropathogenic Bacteria in 2011-2019 at a Korean Tertiary Care Hospital

Background: Trends in the isolation of enteropathogenic bacteria may differ depending on environmental sanitation. This study aimed to determine trends in the isolation and antimicrobial resistance patterns of enteropathogenic bacteria between 2011 and 2019. Methods: A retrospective analysis was performed using data from stool cultures of Salmonella spp., Shigella spp., Plesiomonas shigelloides, Yersinia spp., Vibrio spp., and Campylobacter spp. The sample was collected at Severance Hospital between 2011 and 2019. Antimicrobial susceptibility testing was performed using the disk diffusion method for nontyphoidal Salmonella (NTS) and Campylobacter spp. following CLSI guideline. Results: The number of specimens for stool culture significantly increased from 13,412 during 1969-1978 to 48,476 over the past nine years, whereas the ratio of positive specimens significantly decreased from 1,732 (12.9%) to 449 (0.9%). The proportion of Salmonella Typhi decreased from 472 (93.6%) in 1969-1978 to 4 (1.5%) in 2011-2019, whereas the proportion of NTS increased from 14 (2.8%) to 261 (96.7%). The proportion of Shigella among all enteropathogenic bacteria was 1,039 (60.0%) from 1969-1978, while only 7 (1.6%) were isolated from 2011-2019. Campylobacter is the second most prevalent organisms, which were isolated 132 (29.4%). The susceptibility rate to ampicillin and cotrimoxazole were 51.1% and 85.2%, respectively, for NTS isolated from 2016 -2019. The ciprofloxacin susceptibility rate was 15.8% for Campylobacter from 2016-2019. Conclusion: The number of isolates of Salmonella Typhi and Shigella significantly decreased, while the proportion of NTS and Campylobacter increased. Continuous monitoring of ciprofloxacin-resistant Campylobacter isolates is necessary.open석

Selection Model of Subcontractor Relationships by Using Discriminant Analysis

Subcontractors usually handle some parts of special works in construction projects. The development of the subcontractor’s relationship is one of the main issues to ensure the project's success. Many existing models were proposed for evaluating the subcontractor prequalification and performance, but a selection model of subcontractor relationships was still neglected for supporting the decision-making of the main contractor. Currently, main contractors use only their experience and personal preference to choose the type of subcontractor relationships. These practices can reduce the opportunities for finding a suitable subcontractor who could add more value to future explorative work. Moreover, if they mismatch the relationship type with the subcontractor, the main contractors will work with a poor-performance subcontractor. Thus, this wrong selection has hindered the benefit of a long-term relationship subcontractor. This study developed a selection model of subcontractor relationships to solve the problem. The methodology of this research collected data from the primary contractor's assessment of 15 projects, with 93 subcontractors based on factors influencing the current relationship type. Then, the selection model of subcontractor relationships was developed by using discriminant analysis. As a result, time control in planning, work quality, cooperation, and trust factors that influenced the outcome of the model development, were able to classify subcontractors into short-term or long-term relationships. The finding result was also validated and shown at an acceptable level. Therefore, the model development could support the decision-making of the main contractor in choosing the type of subcontractor relationship

Systems Biology Graphical Notation: Activity Flow language Level 1

Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialized notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Descriptions, the Entity Relationships and the Activity Flows. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage ranging from textbooks and teaching in high schools to peer reviewed articles in scientific journals. The first level of the SBGN Activity Flow language has been publicly released. Shared by the communities of biochemists, genomic scientists, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signaling pathways, metabolic networks and gene regulatory maps

The Effect of Dispositional Resistance to Change on Perceived Ease of Use

The introduction of new information systems often involves user resistance due to the changes associated with adopting new technologies. Therefore, it is important to understand how individuals’ resistance to change influences their perceptions of new technologies. Personality traits are commonly used in the psychology literature to explain human beliefs and behavior across different domains, and recently see a growing interest in the IS literature as an explanatory tool in the domain of technology related behavior. Research in social psychology has found Resistance to Change (RTC) to be a fundamental personality trait that influences individuals’ beliefs and behavior in situations involving change. In the present study we explore the relationship between RTC and Perceived Ease of Use, using a survey of 170 users of a digital library system. The preliminary findings suggest that RTC is a significant determinant of perceived ease of use. Implications of the findings are discussed

Trusting Social Location Technologies and Interactions

Social networks provide rich opportunities to interact with friends and other members. While research on motivations and interaction design help explain what makes online communities successful, the influence of trust on social location technologies and interactions that integrate online and off-line activities remains unclear. Drawing from research on information systems, social psychology, and social networks, we identify the drivers of users’ trust in social location artifacts and other subscribers. We will test our hypotheses on Facebook’s Places application by connecting surveys to actual usage data. We expect trust in the artifact to depend on usability, situation normality, perceived critical mass, and referrals from trusted sources. We also hypothesize that trust beliefs toward other users—split into friends and everyone else—will depend on instinctive feelings of trust, rationalizations that others won’t do harm, and structural assurances. Implications for theory and practice as well as limitations and future work are discussed

Using Artificial Neural Network for Selecting Type of Subcontractor Relationships in Construction Project

Since some subcontractors could perform their professional skills faster and less expensive, many main contractors have adapted those companies to help their construction works and gained more profits. After the relationship between main contractor and subcontractor was consistently developed by many construction projects, main contractors would be willing to define a potential subcontractor who could ensure a good productivity in the future. Previously, main contractors were experienced by wrong selection of subcontractor in relationship development. Thus, it could cause some controversies between main contractor and subcontractor and hinder benefits with a right subcontractor for a long run business. To minimize the problem of main contractor, this paper used an artificial neural network as a tool for determining the subcontractor in relationship development. As the result, the artificial neural network provided higher accuracy in training and validating data and it could give main contractor more confident in decision making for selecting type of subcontractor relationships