Voter model on a directed network: Role of bidirectional opinion exchanges

The voter model with the node update rule is numerically investigated on a directed network. We start from a directed hierarchical tree, and split and rewire each incoming arc at the probability $p$. In order to discriminate the better and worse opinions, we break the $Z_2$ symmetry ($\sigma = \pm 1$) by giving a little more preference to the opinion $\sigma = 1$. It is found that as $p$ becomes larger, introducing more complicated pattern of information flow channels, and as the network size $N$ becomes larger, the system eventually evolves to the state in which more voters agree on the better opinion, even though the voter at the top of the hierarchy keeps the worse opinion. We also find that the pure hierarchical tree makes opinion agreement very fast, while the final absorbing state can easily be influenced by voters at the higher ranks. On the other hand, although the ordering occurs much slower, the existence of complicated pattern of bidirectional information flow allows the system to agree on the better opinion.Comment: 5 pages, 3 figures, Phys. Rev. E (in press

Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks

Changes in Arctic sea ice affect atmospheric circulation, ocean current, and polar ecosystems. There have been unprecedented decreases in the amount of Arctic sea ice due to global warming. In this study, a novel 1-month sea ice concentration (SIC) prediction model is proposed, with eight predictors using a deep-learning approach, convolutional neural networks (CNNs). This monthly SIC prediction model based on CNNs is shown to perform better predictions (mean absolute error - MAE - of 2.28 %, anomaly correlation coefficient - ACC - of 0.98, root-mean-square error - RMSE - of 5.76 %, normalized RMSE - nRMSE - of 16.15 %, and NSE - Nash-Sutcliffe efficiency - of 0.97) than a random-forest-based (RF-based) model (MAE of 2.45 %, ACC of 0.98, RMSE of 6.61 %, nRMSE of 18.64 %, and NSE of 0.96) and the persistence model based on the monthly trend (MAE of 4.31 %, ACC of 0.95, RMSE of 10.54 %, nRMSE of 29.17 %, and NSE of 0.89) through hindcast validations. The spatio-temporal analysis also confirmed the superiority of the CNN model. The CNN model showed good SIC prediction results in extreme cases that recorded unforeseen sea ice plummets in 2007 and 2012 with RMSEs of less than 5.0 %. This study also examined the importance of the input variables through a sensitivity analysis. In both the CNN and RF models, the variables of past SICs were identified as the most sensitive factor in predicting SICs. For both models, the SIC-related variables generally contributed more to predict SICs over ice-covered areas, while other meteorological and oceanographic variables were more sensitive to the prediction of SICs in marginal ice zones. The proposed 1-month SIC prediction model provides valuable information which can be used in various applications, such as Arctic shipping-route planning, management of the fishing industry, and long-term sea ice forecasting and dynamics

Do same-level review ratings have the same level of review helpfulness? The role of information diagnosticity in online reviews

This research examines whether the written contents of online reviews can generate systematic differences in the review’s perceived helpfulness even with identical ratings. In addition, this research explores which underlying psychological mechanism creates the systemic differences related to helpfulness. Specifically, the results from our two experiments demonstrate that, when an online hotel review has a positive rating, written contents containing both positive and negative information is perceived as more helpful than reviews with only positive written content. In contrast, when an online hotel review has a negative rating, written contents that contain only negative information is perceived as more helpful than reviews with written content containing both positive and negative information. Importantly, our study shows that the degree of information diagnosticity in online reviews behaves as an underlying psychological mechanism in the process. Our findings not only contribute to the extant literature but also provide useful insights and practical implications for travel websites

The relationship between needs, motivations and information sharing behaviors on social media: Focus on the self-connection and social connection

Purpose The purpose of this study is to investigate the factors that influence the information sharing behavior of individuals on social media. Furthermore, the study analyzes the effect that individuals’ self-connection to social media has on information sharing through self-efficacy and the effect of social-connection on information sharing through empathy. Design/methodology/approach A survey questionnaire was developed and distributed to social media users from general participants in the Republic of Korea. A total of 824 valid responses were obtained. Hypotheses were tested using structural equation modeling and applying SmartPLS 3.0. Findings The result indicated that individuals are motivated to share information through self-connection and social connection. Furthermore, the mediation analysis revealed that the effect of self-connection on information sharing in social media is mediated by self-efficacy. Also, social connection will increase information sharing not only directly but also indirectly through its positive effect on empathy. Originality/value The authors focused on the basic needs of humans and tried to reveal the relationship between human needs and motivational beliefs, which are self-efficacy and empathy, and information sharing behavior on social media. Through the individual's fundamental needs that social media can satisfy, individuals will gain positive psychological benefits through using social media. This study considered what psychological benefits social media can provide

Strong attachment to heroes: How does it occur and affect people’s self-efficacy and ultimately quality of life?

In spite of increasing evidence on the influence of heroes on the lives of ordinary people, there has been no formal study on the subject in relation to people’s attachment to a hero (or hero attachment). The current study proposed a consumer model to examine how a hero makes a positive impact on people’s lives in terms of their hero attachment, self-efficacy, and life satisfaction. Using observations from a survey, we examined both the direct and indirect effects that the contribution of a hero in people’s fundamental A-R-C (autonomy, relatedness, and competence) need fulfillment has on self-efficacy and ultimately on life satisfaction. We found that the impact of a hero in fulfilling the A-R-C needs has a direct, differential effect on self-efficacy and life satisfaction. More importantly, we found that the fulfillment of A-R-C needs by a hero significantly influences hero attachment, which in turn positively affects life satisfaction through self-efficacy. As the first empirical study on hero attachment in relation to people’s self-efficacy and life satisfaction, the study yields significant theoretical contributions and practical implications for practitioners and policy makers in the areas of public health, education, and quality of life

Rampant exchange of the structure and function of extramembrane domains between membrane and water soluble proteins.

Of the membrane proteins of known structure, we found that a remarkable 67% of the water soluble domains are structurally similar to water soluble proteins of known structure. Moreover, 41% of known water soluble protein structures share a domain with an already known membrane protein structure. We also found that functional residues are frequently conserved between extramembrane domains of membrane and soluble proteins that share structural similarity. These results suggest membrane and soluble proteins readily exchange domains and their attendant functionalities. The exchanges between membrane and soluble proteins are particularly frequent in eukaryotes, indicating that this is an important mechanism for increasing functional complexity. The high level of structural overlap between the two classes of proteins provides an opportunity to employ the extensive information on soluble proteins to illuminate membrane protein structure and function, for which much less is known. To this end, we employed structure guided sequence alignment to elucidate the functions of membrane proteins in the human genome. Our results bridge the gap of fold space between membrane and water soluble proteins and provide a resource for the prediction of membrane protein function. A database of predicted structural and functional relationships for proteins in the human genome is provided at sbi.postech.ac.kr/emdmp

Influence of congruency between ideal self and brand image on Sustainable Happiness

Building on the Sustainable Happiness Model, this study examines how congruency between ideal self-concepts and brand image influences a sense of happiness. The findings show that when the ideal self-image and the ideal social self-image are congruent with brand image, a sense of happiness can be enhanced through brand identification and positive emotions. An additional two-mediation analysis confirms that there are full mediation effects of brand identification and positive emotions between ideal self/ideal social self-brand congruency and happiness. This study contributes to the literature as it reveals the mechanism of how congruency between ideal self-concepts and brand image positively affects happiness. In addition, this study also provides useful insights for business practitioners as previous studies suggest that enhancing consumer well-being helps increase firms’ long-term sustainability in many ways

Double resonance in the infinite-range quantum Ising model

We study quantum resonance behavior of the infinite-range kinetic Ising model at zero temperature. Numerical integration of the time-dependent Schr\"odinger equation in the presence of an external magnetic field in the $z$ direction is performed at various transverse field strengths $g$. It is revealed that two resonance peaks occur when the energy gap matches the external driving frequency at two distinct values of $g$, one below and the other above the quantum phase transition. From the similar observations already made in classical systems with phase transitions, we propose that the double resonance peaks should be a generic feature of continuous transitions, for both quantum and classical many-body systems.Comment: 4 pages, 5 figure

Proprioceptive Sensor-Based Simultaneous Multi-Contact Point Localization and Force Identification for Robotic Arms

In this paper, we propose an algorithm that estimates contact point and force simultaneously. We consider a collaborative robot equipped with proprioceptive sensors, in particular, joint torque sensors (JTSs) and a base force/torque (F/T) sensor. The proposed method has the following advantages. First, fast computation is achieved by proper preprocessing of robot meshes. Second, multi-contact can be identified with the aid of the base F/T sensor, while this is challenging when the robot is equipped with only JTSs. The proposed method is a modification of the standard particle filter to cope with mesh preprocessing and with available sensor data. In simulation validation, for a 7 degree-of-freedom robot, the algorithm runs at 2200Hz with 99.96% success rate for the single-contact case. In terms of the run-time, the proposed method was >=3.5X faster compared to the existing methods. Dual and triple contacts are also reported in the manuscript.Comment: 2023 International Conference on Robotics and Automation (ICRA