This study presents an evolutionary game to model interactions among stakeholders with potential conflicts, including the operational enterprise of incineration plant, the local government, and the residents nearby. System dynamics is used to simulate the change of strategic actions corresponding to the three players, in order to seek for the evolutionary stability strategies. A numerical case is proposed to demonstrate the game theory application, in which the impacts of governmental incentive and punishment on the player’s actions are investigated. The results (...) indicated that administrative penalty is effective not only in motivating the enterprises to upgrade treatment facilities for ensuring environmental quality but also in helping the local government and residents to approach dominant strategies. Policy implications are given based on the results to lay out a foundation for the alleviation of the conflicts. (shrink)

In service marketing, AI assistants and self-service technology have become popular. As a result, it is critical to enrich the understanding of whether consumers react differently in the artificial intelligence service context in comparison with the human service context. This study examines the effect of assistant type on consumers’ decision-making. Through three experiments, this research finds that variety seeking will be higher when consumers are making decision in AI service environment. Furthermore, we tested uncertainty as the underlying mechanism. Moreover, we (...) demonstrated that this pattern is moderated by situational involvement. Specifically, in consumption contexts of high involvement, the consumers are less likely to seek variety, and in consumption contexts of low involvement, they prefer more variety. This research offers service providers new insights by revealing how, why, and when the interaction of AI technology influences consumers’ decision-making in service marketing. (shrink)

In the field of natural language processing, the task of sensitive information detection refers to the procedure of identifying sensitive words for given documents. The majority of existing detection methods are based on the sensitive-word tree, which is usually constructed via the common prefixes of different sensitive words from the given corpus. Yet, these traditional methods suffer from a couple of drawbacks, such as poor generalization and low efficiency. For improvement purposes, this paper proposes a novel self-attention-based detection algorithm using (...) the implementation of graph convolutional network. The main contribution is twofold. Firstly, we consider a weighted GCN to better encode word pairs from the given documents and corpus. Secondly, a simple, yet effective, attention mechanism is introduced to further integrate the interaction among candidate words and corpus. Experimental results from the benchmarking dataset of THUC news demonstrate a promising detection performance, compared to existing work. (shrink)

Aiming at the vulnerability of wireless network, this paper proposed a method of WiFi penetration testing based on Kali Linux which is divided into four stages: preparation, information collection, simulation attack, and reporting. By using the methods of monitoring, scanning, capturing, data analysis, password cracking, fake wireless access point spoofing, and other methods, the WiFi network penetration testing with Kali Linux is processed in the simulation environment. The experimental results show that the method of WiFi network penetration testing with Kali (...) Linux has a good effect on improving the security evaluation of WiFi network. (shrink)

Congenital nystagmus in infants and young children can lead to early blindness. Previous neuroimaging studies have demonstrated that EB is accompanied by alterations in brain structure and function. However, the effects of visual impairment and critical developmental periods on brain functional connectivity at rest have been unclear. Here, we used the voxel-wise degree centrality method to explore the underlying functional network brain activity in adolescents with EB. Twenty-one patients with EBs and 21 sighted controls underwent magnetic resonance imaging. Differences between (...) the two groups were assessed using the DC method. Moreover, the support vector machine method was used to differentiate patients with EB patients from the SCs according to DC values. Compared with the SCs, the patients with EB had increased DC values in the bilateral cerebellum_6, cerebellum vermis_4_5, bilateral supplementary motor areas, and left fusiform gyrus; the patients with EB had decreased DC values in the bilateral rectal gyrus and left medial orbital frontal gyrus. The SVM classification of the DC values achieved an overall accuracy of 70.45% and an area under the curve of 0.86 in distinguishing between the patients with EB and the SCs. Our study may reveal the neuromechanism of neuroplasticity in EB; the findings provide an imaging basis for future development of restorative visual therapies and sensory substitution devices, and future assessments of visual rehabilitation efficacy. (shrink)

We investigated whether a pre-change representation is inhibited or weakened under correct change detection. Two arrays of six objects were rapidly presented for change detection in three experiments. After detection, the perceptual identification of degraded stimuli was tested in Experiments 1 and 2. The weakening of a pre-change representation was not observed under correct detection. The repetition priming effect was observed for a pre-change object and the magnitude was equivalent to the effect for a post-change object. Under change blindness, repetition (...) priming for a pre-change representation was observed when detection did not require report of location in Experiment 1 and was not observed when location was required to be reported in Experiment 2. The results of Experiment 3 showed that a pre-change representation was recognized at a higher rate under correct detection than under change blindness, reflecting a stronger rather than a weaker pre-change representation in the former context. (shrink)

Humans can understand thousands of abstract words, even when they do not have clearly perceivable referents. Recent views highlight an important role of social experience in grounding of abstract concepts and sub-kinds of abstract concepts, but empirical work in this area is still in its early stages. In the present study, a picture-word semantic priming paradigm was employed to investigate the contribution effect of social experience that is provided by real-life pictures to social abstract concepts and emotional abstract concepts. Using (...) a lexical decision task, we examined responses to picture-SA word pairs and picture-EA word pairs in social/emotional semantically related and unrelated conditions. All pairs shared either positive or negative valence. The results showed quicker responses to positive SA and EA words that were preceded by related vs. unrelated prime pictures. Specifically, positive SA words were facilitated by the corresponding social scene pictures, whereas positive EA words were facilitated by pictures depict the corresponding facial expressions and gestures. However, such facilitatory effect was not observed in negative picture-SA/EA word conditions. This pattern of results suggests that a facilitatory effect of social experience on abstract concepts varies with different sub-kinds of abstract concepts, that seems to be limited to positive SA concepts. Overall, our findings confirm the crucial role of social experience for abstract concepts and further suggest that not all abstract concepts can benefit from social experience, at least in the semantic priming. (shrink)

ObjectiveType 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.MethodsA total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance (...) imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC.ResultsIn patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model.ConclusionFunctional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM. (shrink)

Judging similarities among objects, events, and experiences is one of the most basic cognitive abilities, allowing us to make predictions and generalizations. The main assumption in similarity judgment is that people selectively attend to salient features of stimuli and judge their similarities on the basis of the common and distinct features of the stimuli. However, it is unclear how people select features from stimuli and how they weigh features. Here, we present a computational method that helps address these questions. Our (...) procedure combines image-processing techniques with a machine-learning algorithm and assesses feature weights that can account for both similarity and categorization judgment data. Our analysis suggests that a small number of local features are particularly important to explain our behavioral data. (shrink)

In 2011, Jiangsu Province set up the guidance fund for sports industry. In 2016, Jiangsu Provincial Finance Department jointly issued the document with Jiangsu Provincial Sports Bureau, which was changed to “Jiangsu Special Fund for Sports Industry Development.” By 2019, Jiangsu Province has funded 1,009 sports industry development projects with a total investment of 796.6 million yuan. The effect of the investment has attracted extensive attention from the government, society, and enterprises. Entrusted by Jiangsu Sports Industry Guidance Center, this research (...) team spent one year on the performance research of 1,009 projects supported by special funds for the development of sports industry, from the construction of evaluation index system to the design, issuance, collection, and processing of questionnaires. Using the methods of literature, questionnaire, expert interview, and mathematical statistics, this paper takes the performance management of the special funds for the development of sports industry in Jiangsu Province as the research object, based on the investigation and analysis of the current situation of the special funds for the development of sports industry in Jiangsu Province. It analyzes the special funds from four aspects: the rate of funds in place, the ratio of funds pulled, the completion rate of project implementation, and the rate of fund prerecovery. Then, this paper expounds the current situation, effectiveness, and problems of the performance management of the special funds for the development of sports industry and puts forward some countermeasures and suggestions for improvement. (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)

This paper proposes a novel robust fixed-time control for the robot manipulator system with uncertainties. Based on the uniform robust exact differentiator algorithm, a robust control term is constructed. Then, a robust fixed-time inverse dynamics control is proposed. For the proposed control method, the fixed-time stability of a closed-loop system with uncertainties is strictly proved. The newly proposed method exhibits the following two attractive features. First, the proposed control scheme extends the existing fixed-time IDC for the robot manipulator system to (...) the robust control scheme. Second, the proposed method is strictly nonsingular rather than the commonly used approximate approach. Simulation result demonstrates the effectiveness of the proposed control scheme. (shrink)

Background Participants' understanding of clinical trials is important in informed consent. However, little is known about what information participants really want to know. Aims To demonstrate the existence of a discrepancy between participants' understanding and their desire to know. Methods The participants in clinical trials at Seoul National University Hospital were surveyed. The survey consisted of 11 statements based on the essential elements of informed consent. The participants gave two responses to each statement on a five-point Likert scale to rate (...) their subjective understanding and desire to know, respectively. Information discrepancy was defined as the difference between these two ratings: if understanding exceeded desire to know for a particular item, it was defined as ‘over-informed’; if desire to know exceeded understanding for a particular item, it was defined as ‘under-informed’. Results Participants reported good understanding of ‘voluntariness’, ‘duration’, ‘study involves research’ and poor understanding of ‘confidentiality’, ‘compensation’, ‘benefits’, ‘procedures’ and ‘risks or discomforts’. For ‘risks or discomforts’, ‘who to contact’, ‘voluntariness’, ‘duration’ and ‘procedures’, participants reported high desire to know compared with ‘confidentiality’, ‘purpose’, ‘study involves research’ and ‘benefits’. The elements ‘study involves research’, ‘voluntariness’, ‘duration’, ‘purpose’ and ‘who to contact’ were over-informed, while ‘compensation’, ‘risks or discomforts’, ‘procedures’, ‘confidentiality’ and ‘benefits’ were under-informed. Participants over 50 years of age, those without a college education and those whose participation was less voluntary were relatively less informed about the clinical trials. Conclusions An information discrepancy was observed between the participants' understanding and their desire to know. By putting more emphasis on under-informed elements, the quality of informed consent could be improved. (shrink)

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)

Facial muscle activities are essential for the appearance and communication of human beings. Therefore, exploring the activation patterns of facial muscles can help understand facial neuromuscular disorders such as Bell’s palsy. Given the irregular shape of the facial muscles as well as their different locations, it should be difficult to detect the activities of whole facial muscles with a few electrodes. In this study, a high-density surface electromyogram system with 90 electrodes was used to record EMG signals of facial muscles (...) in both healthy and Bell’s palsy subjects when they did different facial movements. The electrodes were arranged in rectangular arrays covering the forehead and cheek regions of the face. The muscle activation patterns were shown on maps, which were constructed from the Root Mean Square values of all the 90-channel EMG recordings. The experimental results showed that the activation patterns of facial muscles were distinct during doing different facial movements and the activated muscle regions could be clearly observed. Moreover, two features of the activation patterns, 2D correlation coefficient and Centre of Gravity were extracted to quantify the spatial symmetry and the location of activated muscle regions respectively. Furthermore, the deviation of activated muscle regions on the paralyzed side of a face compared to the healthy side was quantified by calculating the distance between two sides of CGs. The results revealed that corr2 of the activated facial muscle region in Bell’s palsy subjects was significantly lower than that in healthy subjects, while CG distance of activated facial region in Bell’s palsy subjects was significantly higher than that in healthy subjects. The correlation between corr2 of these regions and Bell’s palsy [assessed by the Facial Nerve Grading Scale 2.0] was also significant in Bell’s palsy subjects. The spatial information on activated muscle regions may be useful in the diagnosis and treatment of Bell’s palsy in the future. (shrink)

Let [NB]₁ denote the ideal generated by nonbounding c.e. degrees and NCup the ideal of noncuppable c.e. degrees. We show that both [NB]₁ ∪ NCup and the ideal generated by nonbounding and noncuppable degrees are new, in the sense that they are different from M, [NB]₁ and NCup—the only three known definable ideals so far.

Interpersonal physiological synchrony has been consistently found during collaborative tasks. However, few studies have applied synchrony to predict collaborative learning quality in real classroom. To explore the relationship between interpersonal physiological synchrony and collaborative learning activities, this study collected electrodermal activity and heart rate during naturalistic class sessions and compared the physiological synchrony between independent task and group discussion task. The students were recruited from a renowned university in China. Since each student learn differently and not everyone prefers collaborative learning, (...) participants were sorted into collaboration and independent dyads based on their collaborative behaviors before data analysis. The result showed that, during group discussions, high collaboration pairs produced significantly higher synchrony than low collaboration dyads. Given the equivalent engagement level during independent and collaborative tasks, the difference of physiological synchrony between high and low collaboration dyads was triggered by collaboration quality. Building upon this result, the classification analysis was conducted, indicating that EDA synchrony can identify different levels of collaboration quality. (shrink)

When navigating in a new environment, it is typical for people to resort to external guidance such as GPS, or people. However, in the real world, even though navigators have learned the route, they may still prefer to travel with external guidance. We explored how the availability of feedback and the source of external guidance affect navigation decision-making on experienced routes in the presence of external guidance. In three experiments, participants navigated a simulated route three times and then verbally confirmed (...) that they had learned it. They then travelled the same route again, accompanied with no, correct, or incorrect direction guidance, which latter two were provided by a GPS (Exp.1), a stranger (Exp.2), or a friend (Exp.3). Half of the participants received immediate feedback on their navigation decisions, while the other half without feedback did not know if they had selected the correct directions. Generally, without feedback, participants relied on external guidance, regardless of the direction sources. Results also showed that participants trusted the GPS the most, but performed best with their friends as a direction source. With feedback, participants did not show differences in performance between the correct and incorrect guidance conditions, indicating that feedback plays a critical role in evaluating the reliability of external guidance. Our findings suggest that incorrect guidance without any feedback might disturb navigation decision-making, which was further moderated by the perceived credibility of direction sources. We discuss these results within the context of navigation decision-making theory and consider implications for wayfinding behaviors as a social activity. (shrink)

In the real-world complex product design process, task allocating is an ongoing reactive process where the presence of unexpected design change is usually inevitable. Therefore, reallocating is necessary to respond to design change positively as a procedure to repair the affected task plan. General reallocating literature addressed the reallocating versions with fixed executing time. In this paper, a multi-objective reallocation model is developed with a feasible assumption that the task executing time is controllable. To illustrate this idea, a compressing executing (...) time strategy is proposed in CPD process, where the executing time can be controlled with a non-linear compression cost. When design change occurs during the executing, task-resource reallocating is required to absorb the interference effects. Reallocating implies an increase in design cost and system instability; the proposed method CETS can address this issue effectively. CETS considers three objectives: completing time, stability, and change-adaptation cost. An adaptive multi-objective hybrid genetic algorithm and tabu search is developed to solve this mathematical method. The computational results of specific simulation examples verify the superiority. It shows that CETS is sensitive to design change, and the proposed algorithm AMOGATS can be effective to achieve the allocating by coordinating the objective consistency. (shrink)

Partner selection is the primary aspect of the formation of knowledge collaboration teams. We propose a method of partner selection for KCTs based on a weighted social network analysis method in which the individual knowledge competence and the collaboration performance of candidates are both considered. To select the desired partners, a biobjective 0-1 model is built, integrating the knowledge competence and collaboration performance, which is an NP-hard problem. Then, a multiobjective genetic algorithm is developed to solve the proposed model. Finally, (...) a real-world example is provided to illustrate the applicability of the model, and the MOGA is implemented to search for Pareto solutions of partner selection for KCT in this case. Moreover, some simulation examples are used to test the efficiency of the algorithm. The results suggest that the proposed method can support effective and practical partner selection. (shrink)

Member selection to form an effective collaboration new product development team is crucial for a successful NPD. Existing researches on member selection mostly focus on the individual attributes of candidates. However, under the background of collaboration, knowledge complementarity and collaboration performance among candidates are important but overlooked. In this paper, we propose a multi-objective optimization model for member selection of a Co-NPD team, considering comprehensively the individual knowledge competence, knowledge complementarity, and collaboration performance. Then, to solve the model, an improved (...) adaptive genetic algorithm is developed. Finally, a real case is provided to illustrate the application of the model, and the IAGA is implemented to select the desired team members for optimal team composition. Additionally, the standard generic algorithm and particle swarm optimization are used to compare with the IAGA to further verify the effectiveness of the IAGA. (shrink)