To realize the coordinated and sustainable development of hydropower projects and regional society, comprehensively evaluating hydropower projects’ influence is critical. Usually, hydropower project development has an impact on environmental geology and social and regional cultural development. Based on comprehensive consideration of complicated geological conditions, fragile ecological environment, resettlement of reservoir area, and other factors of future hydropower development in each country, we have constructed a comprehensive evaluation index system of hydropower projects, including 4 first-level indicators of social economy, environment, safety, (...) and fairness, which contain 26 second-level indicators. To solve the problem that existing models cannot evaluate dynamic nonlinear optimization, a projection pursuit model is constructed by using rough set reduction theory to simplify the index. Then, an accelerated genetic algorithm based on real number coding is used to solve the model and empirical study is carried out with the Y hydropower station as a sample. The evaluation results show that the evaluation index system and assessment model constructed in our paper effectively reduce the subjectivity of index weight. Applying our model to the social impact assessment of related international hydropower projects can not only comprehensively analyze the social impact of hydropower projects but also identify important social influencing factors and effectively analyze the social impact level of each dimension. Furthermore, SIA assessment can be conducive to project decision-making, avoiding social risks and social stability. (shrink)

In the target article by Kolbe and de Melo-Martin (2023), the authors discussed several shortcomings of major instruments of moral distress, including the Moral Distress Scale (MDS) (Corley et al....

The formation control issue for a group of underactuated unmanned surface vehicles is discussed in the paper, and a staged finite-time control strategy for the USVs is proposed. Firstly, we try to steer each USV to its own starting point in the formation for a limited time, under the initial condition that each of these vehicles is parked at random. To deal with the nonholonomic behavior of the system, the dynamics of the USV is transformed into cascade systems. Then, the (...) finite-time controller is designed for each vehicle based on homogeneity theory. After each USV reaches its own starting point with desired orientation, the model of the vehicle is decomposed into two subsystems under the Serret-Frenet frame. In order to maintain the formation pattern, two finite-time distributed controllers are developed for the surge subsystem and the yaw subsystem, respectively. The settling time for the staged control strategy is limited. Numerical simulations are carried out to illustrate the effectiveness of the proposed formation control strategy. (shrink)

In this study, we focus on the problem of information expiration when using the traditional collaborative filtering algorithm and propose a new collaborative filtering algorithm by integrating the time factor. This algorithm considers information influence attenuation over time, introduces an information retention period based on the information half-value period, and proposes a time-weighted function, which is applied to the nearest neighbor selection and score prediction to assign different time weights to the scores. In addition, to further improve the quality of (...) the nearest neighbor selection and alleviate the problem of data sparsity, a method of calculating users’ sentiment tendency by analysis of user review features is proposed to mine users’ attitudes about the reviewed items, which expands the score matrix. The time factor and sentiment tendency are then integrated into the K-means clustering algorithm to select the nearest neighbor. A hybrid collaborative filtering model based on the improved K-means clustering algorithm is then proposed, by combining item-based and user-based collaborative filtering. Finally, the experimental results show that the proposed algorithm can address the time effect and sentiment analysis in recommendations and improve the predictive performance of the model. (shrink)

Cardiovascular disease is a major complication of type 2 diabetes mellitus. In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social (...) information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve analysis was used to evaluate the model performance. Of participants, 272 were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion. (shrink)

Aiming at the high false alarm rate when using single sensor to detect fire in aircraft cabin, a multisensor data fusion method is proposed to detect fire. First, the weights of multiple factors, that is, temperature, smoke concentration, CO concentration, and infrared ray intensity in the event of fire, were calculated by using the improved analytic hierarchy process method on each sensor node of wireless sensor network, and the probability of fire event in the cabin was evaluated by multivariable-weighted fusion (...) method. Second, based on the mutual support among the evaluation data of fire probabilities of each node, the adaptive weight coefficient is assigned to each evaluation value, and the weighted fusion of all evaluation values of each node is conducted to obtain the fire probability. In the end, compared to the threshold of probability, the fire alarm is determined. Comparing the proposed algorithm to the grey fuzzy neural network fusion algorithm and fuzzy logic fusion algorithm in terms of the time consumption for fire detection and sending alarm and the accuracy of fire alarm perspectives, the experiments demonstrate that the proposed fire detection algorithm can detect the fire within 10s and reduce the false alarm rate to less than 0.5%, which verifies the superiority of the algorithm in promptness and accuracy. In the meanwhile, the fault tolerance of the algorithm is proved as well. (shrink)

Background: Aggression is an important risk factor for delinquency and crime in adolescents. Previous studies have indicated that childhood maltreatment plays an important role in the development of aggression. However, whether the effect could be mediated by other factors is still unknown. Evidence suggests that callous-unemotional (CU) traits and self-control may be candidate mediators in the relationship between childhood maltreatment and aggression.Methods: A total of 585 male juvenile delinquents from China were recruited for the present study. We measured self-reported childhood (...) maltreatment, CU traits, self-control, and aggression with the short form of the Childhood Trauma Questionnaire (CTQ-SF), the Inventory of Callous-Unemotional Traits (ICU), the Self-Control Scale (SCS), and the Aggression Questionnaire (AQ), respectively. Furthermore, we constructed multiple mediation models to investigate the mediating effects of CU traits and self-control on the relationship between childhood maltreatment and aggression. Childhood maltreatment and aggression were entered into the model as the independent and dependent variables, respectively, and CU traits and self-control were treated as the mediating variables. In addition, the moderating role of self-control in the relationship between childhood maltreatment and aggression was tested by constructing a moderation model.Results: Correlation analysis showed significant positive correlations among childhood maltreatment, CU... (shrink)

ObjectiveThis study aims to investigate the effectiveness of mindfulness-based cognitive therapy combined with medication therapy in preventing the recurrence of major depressive disorder in convalescent patients.MethodsA total of 130 patients with convalescent MDD were enrolled in this prospective study. Sixty-five patients were assigned to the experimental group and received medication therapy combined with MBCT, and 65 patients were assigned to the control group and treated with medication alone. The recurrence rate and related hormonal changes were compared between the two groups.ResultsAfter (...) 1 year of MBCT intervention, eight patients experienced recurrence in the experimental group, a recurrence rate of 12.31%, and 19 patients experienced recurrence in the control group, a recurrence rate of 29.23%. The Hamilton Depression Rating Scale and the World Health Organization Quality of Life Scale scores in both the experimental and the control groups were significantly improved after treatment. The difference in the HAM-D scores before and after treatment in the experimental group was 16.74 ± 4.54; this was significantly higher than that of the control group. The WHOQOL-BREF scores in the experimental group were significantly improved compared with those of the control group. The differences in the levels of corticotrophin-releasing hormone, adrenocorticotropic hormone, and cortisol before and after treatment in the experimental group and the control group were statistically significant. The difference in CRH before and after treatment in the experimental group was 16.8 ± 7.2, which was higher than that of the control group. The intervention with MBCT had a significant impact on the recurrence of MDD [β = 1.206, P = 0.039, 95% CI = 0.0790–1.229]. The difference in the HAM-D scores also had a significant impact on the recurrence of MDD.ConclusionCompared with medication therapy alone, the use of MBCT combined with medication therapy can effectively prevent the recurrence of MDD in convalescent patients. (shrink)

BackgroundPsychological resilience may reduce the impact of psychological distress to some extent. We aimed to investigate the mental health status of the public during the outbreak of coronavirus disease 2019 and explore the level and related factors of anxiety and depression.MethodsFrom February 8 to March 9, 2020, 3,180 public completed the Zung’s Self-Rating Anxiety Scale for anxiety, Zung’s Self-Rating Depression Scale for depression, the Connor–Davidson resilience scale for psychological resilience, and the Simplified Coping Style Questionnaire for the attitudes and coping (...) styles.ResultsThe number of people with depressive symptoms was 1,303. The number of people with anxiety symptoms was 1,184. The depressed group and anxiety group had less education, more unmarried and younger age, as well as had significant different in SDS total score, SAS total score, CD-RISC total score, and SCSQ score. The binary logistic regression showed that female, strength, and the subscales of active coping style in SCSQ remained protective factors and passive coping style and higher SAS score were risk factors for depression. Optimism in CD-RISC was a protective factor, and passive coping styles and higher SDS score were risk factors for anxiety.LimitationsThis study adopted a cross-sectional design and used self-report questionnaires.ConclusionThe mental health of the public, especially females, the younger and less educational populations, and unmarried individuals, should be given more attention. Individuals with high level of mental resilience and active coping styles would have lower levels of anxiety and depression during the outbreak of COVID-19. (shrink)

Although similar environmental issues are present across the globe, residents of different countries vary in the extent to which they are concerned about and act upon these issues. Drawing on data from the 2010 Environment module of the International Social Survey Programme, this study tests the structural comparability of environmental attitudes across 32 countries and examines how pro-environmental behaviours are linked to relevant attitudes. A confirmatory factor analysis from structural equation modelling helps identify three latent constructs of environmental attitudes: willingness (...) to sacrifice, biospheric orientation and environmental scepticism. Further regression analyses reveal that the linkages between pro-environmental behaviours and the constructs of environmental attitudes converge in some countries but are less consistent in others. The findings help pinpoint signs of global convergence and national disparities, which merit more extensive analyses amid the recent surge in the availability of diverse empirical data from around the world. (shrink)

The trend to implement the monitoring system with a wireless sensor network has been becoming urgent due to guaranteed flight safety and the passengers comfortability in travel. In this paper, a new dynamic routing algorithm is proposed to prolong the lifetime of the monitoring system with a distributed network based on the K-coverage method, and filter algorithm to be used for data fusion. Finally, the simulation results validate the effectiveness of the proposed approach.

In this paper, we propose to incorporate the local attention in WaveNet-CTC to improve the performance of Tibetan speech recognition in multitask learning. With an increase in task number, such as simultaneous Tibetan speech content recognition, dialect identification, and speaker recognition, the accuracy rate of a single WaveNet-CTC decreases on speech recognition. Inspired by the attention mechanism, we introduce the local attention to automatically tune the weights of feature frames in a window and pay different attention on context information for (...) multitask learning. The experimental results show that our method improves the accuracies of speech recognition for all Tibetan dialects in three-task learning, compared with the baseline model. Furthermore, our method significantly improves the accuracy for low-resource dialect by 5.11% against the specific-dialect model. (shrink)

Based on the existing financial system risk models, a set of time-lag financial system risk models is established considering the influence brought by time-lag factors on the financial risk system, and the dynamical behavior of this system is analyzed by using chaos theory. Through Matlab simulation, the bifurcation diagram and phase diagram of time-lag risk intensity and control intensity are plotted. The analysis shows that this kind of time-lag financial system risk model has complex dynamic behavior, different motion states will (...) appear when different parameter values are selected, and the time-lag risk intensity parameter also has a very strong influence on the system motion. To ensure the operation of the financial system in a stable state, measures with certain delay effects must be taken to control the risk and to choose the appropriate time-lag control intensity, and too much or too little time-lag control intensity is not conducive to the benign operation of the system. (shrink)

The target article by David Alfandre et al. offers a new ethical framework to guide COVID-19 contingency surge planning and response, and applies this ethical framework to three case example...

This study aims to examine the neural correlates of cognitive shifting during the Dimensional Change Card Sort Task task with functional near-infrared spectroscopy. Altogether 49 children completed the DCCS tasks, and 25 children passing all items were classified into the Switch group. Twenty children committing more than one perseverative errors were grouped into the Perseverate group. The Switch group had Brodmann Area 9 and 10 activated in the pre-switch period and BA 6, 9, 10, 40, and 44 in the post-switch (...) period. In contrast, the Perseverate group had BA 9 and 10 activated in the pre-switch period and BA 8, 9, 10 in the post-switch period. The general linear model results afford strong support to the “V-shape curve” hypothesis by identifying a significant decrease–increase cycle in BA 9 and 44, the neural correlations of cognitive shifting. (shrink)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

Aiming at the oscillation suppression of spacecraft with large flexible appendages, we propose a control strategy using H∞ control. The weighting functions are designed for the specific flexible modes of the spacecraft and the frequency of harmonic interference in its operating environment. Taking into account the structural uncertainty of systematic modeling and the comprehensive performance requirements of system bandwidth constraint and attitude stability, the H∞ comprehensive performance matrix is constructed. A space telescope with a large flexible solar array is presented (...) as an illustrative example, and a control design that meets the requirement for pointing accuracy is proposed. The simulation results show that the designed controller satisfies the requirements of attitude stability and high pointing accuracy and has effectively suppressed the disturbance of endemic frequency. The design scheme and selection method of the weight function shown in this paper can be a reference for the controller design for oscillation suppression of this type of spacecraft with flexible structures. (shrink)

In the realistic world, various individuals have distinct personalities, preferences, and attitudes toward new information and behavior acceptance, called population heterogeneity. It is seldom taken into account and theoretically analyzed in information propagation on a weighted network. Therefore, we divide individuals into fashionable and conservative individuals according to their passion degree and willingness for novel behaviors acceptance. Then, we build two behavior adoption threshold models corresponding to fashionable and conservative individuals on the weighted network to explore the effect of population (...) heterogeneity on information propagation. Next, a partition theory based on edge weight and population heterogeneity is proposed to qualitatively analyze the information propagation mechanism. The theoretical analyses and simulation results show that fashionable individuals promote information propagation and behavior adoption. More importantly, the crossover phenomena of phase transition appear. When the fraction of fashionable individuals is relatively large, the increasing pattern of the final adoption size shows a second-order continuous phase transition. In comparison, the increasing pattern alters to first-order discontinuous phase transition with the decrease of the fraction of fashionable individuals. Moreover, reducing weight distribution heterogeneity promotes information propagation and slightly accelerates the change of the phase transition pattern from the first-order discontinuous to the second-order continuous. Besides, increasing the degree distribution heterogeneity accelerates the change of the phase transition pattern. Finally, our theoretical analyses coincide well with the simulation results. (shrink)

When there is no immediate response after a proposal and normally the silence is longer than 0.2 s, the proposer would take subsequent actions to pursue a preferred response or mobilize at least an articulated one from the recipient. These actions modulate the prior deontic stance embedded in the original proposal into four trends as follows: maintaining the prior deontic stance with a self-repair or by seeking confirmation; making the prior deontic stance more tentative by making a revised other-attentiveness proposal, (...) providing an account, pursuing with a tag question, or requesting with an intimate address term; making the prior deontic stance more decisive by making a further arrangement, closing the local sequence, or providing a candidate unwillingness account ; and canceling the prior deontic stance by doing a counter-like action. Additionally, these trends inherently embody a decisive-to-tentative gradient. This study would penetrate into the phenomena occurring in Mandarin mundane talk with the methodology of Conversation Analysis to uncover the underflow of deontic stance. (shrink)

In the long 20th century, modern China experienced perhaps the world’s most radical and systematic secularization process and the decimation of traditional religious and ritual cultures. This article seeks to account for this experience by engaging with postcolonial theory, a body of discourse seldom found relevant to China Studies. The article attempts a two-pronged critique of both state secularization and some aspects of existing Postcolonial Studies/theory. It shows the many ways in which nationalist elites in modern China unwittingly absorbed Western (...) Orientalist discourse even as their words and actions were ostensibly anti-colonial, and much of the article examines the consequences of this native Orientalism upon Chinese religiosities. Finally, the article suggests that one cannot discuss governmentality in modern China without understanding how it is intertwined with a sovereign power that is both archaic and, at the same time, has experienced renewal and expansion in modernity. (shrink)

The target article (Nelson et al. 2023) offers a valuable contribution to the “paradox of experience,” which was illustrated by using examples about access to unproven medical products and disabili...

Objective: To systematically analyze the effects of art therapy on the levels of depression, anxiety, blood glucose, and glycated hemoglobin in diabetic patients.Methods: We searched Cochrane Library, PubMed, Embase, and ClinicalTrials.gov databases from inception to January 24, 2021. The language of publication was limited to English. Randomized controlled trials that used art therapy to improve mental disorders in diabetic patients were involved. After selection of eligible studies, data were extracted, including the first author's full-name, year of publication, the first author's (...) country of residence, number of intervention and control groups, the mean age of participants, method of intervention, duration of follow-up, and outcome measures. Assessment of quality of the included studies and data extraction were independently carried out by two researchers. RevMan 5.3 software was used to perform statistical analysis.Results: A total of 396 samples from five studies were included, and the eligible studies were RCTs with a parallel design. Methods of art therapy included music therapy and painting therapy. The results showed that compared with the control group, art therapy could positively affect the levels of depression [standardized mean difference, −1.36; 95% confidence interval, ; P < 0.00001] and blood glucose in diabetic patients [mean difference, −0.90; 95% CI, ; P < 0.0001], while it had no influence on the levels of anxiety [SMD, −0.31; 95% CI, ; P = 0.32] and glycated hemoglobin [MD, 0.22; 95% CI, ; P = 0.07].Conclusion: Art therapy may have significant effects on the levels of depression and blood glucose for diabetic patients. (shrink)

Studies have shown that teachers’ wellbeing has a positive effect on teachers’ learning quality and learners’ performance. Nevertheless, teaching is a stressful and exhausting profession at all academic level with special difficulties about the nature of language education. Tension and fear are still classic challenges in learning, though the concepts such as hope and optimism are core issues in assisting teachers to feel happy during instruction and work longer. The present review makes efforts to provide the most current confirmation on (...) the interface of hope and optimism with educational issues since they are progressively documented as significant emotional capitals for educational success, job growth, and presentation. It is worth mentioning that the current review of research can benefit educational administrations, and other stakeholders and officials in the educational community to contemplate the functions of constructive emotions in the process of learning to decrease and even diminish stress and apprehension that consequently lead to flourishing. (shrink)

This study explored the differentiated neural correlates of mental rotation in preschoolers with high and low working memory capacity using functional near-infrared spectroscopy. Altogether 38 Chinese preschoolers completed the Working Memory Capacity test, the Mental Rotation, and its Control tasks. They were divided into High-WMC and Low-WMC groups based on the WMC scores. The behavioral and fNIRS results indicated that: there were no significant differences in MR task performance between the High-WMC and Low-WMC group ; the Low-WMC group activated BA6, (...) BA8, BA 9, and BA 44, whereas the High-WMC group activated BA8, BA10 and BA 44 during mental rotation; significant differences were found in the activation of BA44 and BA9 between the High-WMC and Low-WMC groups during mental rotation; and the High-WMC and Low-WMC groups differed significantly in the activation of BA 9 and BA10 during the control tasks, indicating that both areas might be responsible for the group differences in working memory. (shrink)

Along with urban development globally, the NIMBY crisis has been a complex social problem, which requires urgent remedial action. The inevitable management of Municipal Solid Waste has been one of the toughest risk management tasks in the worldwide modernization process. At present, certain fuzzy and unstructured results and methods have been formed for MSW-NIMBY crisis response, mainly focusing on the sociology and politics which scatter in complex and sensitive reports and news. Aiming at enhancing the effectiveness of data mining from (...) specific sparse text of MSW-NIMBY crisis, an improved knowledge extraction method is developed. Through rule-based text mining and complex network analysis, the Entity Relationship network of MSW-NIMBY crisis is reconstructed. Meanwhile, a novel transitivity for relationship between entities in semantic analysis is proposed to improve the feasibility and accuracy of information extraction. Characteristics and regularity of MSW-NIMBY crisis evolution and experience of crisis governance could be identified effectively. Results show that knowledge integration and ER transitivity can enhance knowledge recognition and major other factors, which could help formulate the governance strategies of NIMBY crisis from academic texts. (shrink)

This article examines the struggles over space in rural southeastern coastal China, where the market economy has brought newfound prosperity to local communities. Instead of reinvesting all of their wealth into furthering industrial growth, local residents wish to also plow their money into building tombs for their deceased, ancestor halls, deity temples, Daoist and Buddhist temples, Christian churches, and holding extravagant rituals and festivals. These investments into the divine and celestial realms are not met with approval by the local government, (...) who regards them as “wasteful” and “backwards”. However, the local residents have some of their own ruses and strategies in this spatial struggle. (shrink)

Given a target area and a location-aware social network, the location-aware influence maximization problem aims to find a set of seed users such that the information spread from these users will reach the most users within the target area. We show that the problem is NP-hard and present an approximate algorithm framework, namely, TarIM-SF, which leverages on a popular sampling method as well as spatial filtering model working on arbitrary polygons. Besides, for the large-scale network we also present a coarsening (...) strategy to further improve the efficiency. We theoretically show that our approximate algorithm can provide a guarantee on the seed quality. Experimental study over three real-world social networks verified the seed quality of our framework, and the coarsening-based algorithm can provide superior efficiency. (shrink)

The target article by Lynch et al. offers approaches for improving trial availability and Expanded Access for non-pandemic diseases based on the analysis of the COVID-19 experience in the US...

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, pathogenesis, diagnosis, (...) prevention, and treatment. We emphasize CIDO development relevant to COVID-19. (shrink)

Current COVID-19 pandemic and previous SARS/MERS outbreaks have caused a series of major crises to global public health. We must integrate the large and exponentially growing amount of heterogeneous coronavirus data to better understand coronaviruses and associated disease mechanisms, in the interest of developing effective and safe vaccines and drugs. Ontologies have emerged to play an important role in standard knowledge and data representation, integration, sharing, and analysis. We have initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO). (...) As an Open Biomedical Ontology (OBO) library ontology, CIDO is an open source and interoperable with other existing OBO ontologies. In this article, the general architecture and the design patterns of the CIDO are introduced, CIDO representation of coronaviruses, phenotypes, anti-coronavirus drugs and medical devices (e.g. ventilators) are illustrated, and an application of CIDO implemented to identify repurposable drug candidates for effective and safe COVID-19 treatment is presented. (shrink)

The global spread of the novel coronavirus is affected by the spread of related misinformation—the so-called COVID-19 Infodemic—that makes populations more vulnerable to the disease through resistance to mitigation efforts. Here, we analyze the prevalence and diffusion of links to low-credibility content about the pandemic across two major social media platforms, Twitter and Facebook. We characterize cross-platform similarities and differences in popular sources, diffusion patterns, influencers, coordination, and automation. Comparing the two platforms, we find divergence among the prevalence of popular (...) low-credibility sources and suspicious videos. A minority of accounts and pages exert a strong influence on each platform. These misinformation “superspreaders” are often associated with the low-credibility sources and tend to be verified by the platforms. On both platforms, there is evidence of coordinated sharing of Infodemic content. The overt nature of this manipulation points to the need for societal-level solutions in addition to mitigation strategies within the platforms. However, we highlight limits imposed by inconsistent data-access policies on our capability to study harmful manipulations of information ecosystems. (shrink)