9,868 research outputs found
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 . In order to discriminate the
better and worse opinions, we break the symmetry () by
giving a little more preference to the opinion . It is found that
as becomes larger, introducing more complicated pattern of information flow
channels, and as the network size 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 reviewās 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 individualsā 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 peopleās 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 peopleās attachment to a hero (or hero attachment). The current study proposed a consumer model to examine how a hero makes a positive impact on peopleās 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 peopleās 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 peopleās 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 firmsā long-term sustainability in many ways
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
Characteristics of DSSC Panels with Silicone Encapsulant
Dye-sensitized solar cells (DSSC) allow light transmission and the application of various colors that make them especially suitable for building-integrated PV (BIPV) application. In order to apply DSSC modules to windows, the module has to be panelized: a DSSC module should be protected with toughened glass on the entire surface. Up to the present, it seems to be common to use double glazing with DSSC modules, with air gaps between the glass pane and the DSSC modules. Few studies have been conducted on the characteristics of various glazing methods with DSSC modules. This paper proposes a paneling method that uses silicone encapsulant, analyzing the performance through experimentation. Compared to a multilayered DSSC panel with an air gap, the encapsulant-applied panel showed 6% higher light transmittance and 7% higher electrical efficiency. The encapsulant also prevented electrolyte leakage by strengthening the seals in the DSSC module
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