•Long-range airborne transmission in the restaurant is fully supported.•Fomite and close contact routes in the Guangzhou restaurant outbreak are ruled out.•Diners and staffs spent 20% of their time ...on close contact in the restaurant.•Diners and staffs spent 90% of their time touching surfaces in the restaurant.•Almost no close contact happened between diners from different tables.
Background: Coronavirus disease 2019 (COVID-19) is primarily a respiratory disease that has become a global pandemic. Close contact plays an important role in infection spread, while fomite may also be a possible transmission route. Research during the COVID-19 pandemic has identified long-range airborne transmission as one of the important transmission routes although lack solid evidence.
Methods: We examined video data related to a restaurant associated COVID-19 outbreak in Guangzhou. We observed more than 40,000 surface touches and 13,000 episodes of close contacts in the restaurant during the entire lunch duration. These data allowed us to analyse infection risk via both the fomite and close contact routes.
Results: There is no significant correlation between the infection risk via both fomite and close contact routes among those who were not family members of the index case. We can thus rule out virus transmission via fomite contact and interpersonal close contact routes in the Guangzhou restaurant outbreak. The absence of a fomite route agrees with the COVID-19 literature.
Conclusions: These results provide indirect evidence for the long-range airborne route dominating SARS-CoV-2 transmission in the restaurant. We note that the restaurant was poorly ventilated, allowing for increasing airborne SARS-CoV-2 concentration.
A survey of multimodal sentiment analysis Soleymani, Mohammad; Garcia, David; Jou, Brendan ...
Image and vision computing,
September 2017, 2017-09-00, Letnik:
65
Journal Article
Recenzirano
Sentiment analysis aims to automatically uncover the underlying attitude that we hold towards an entity. The aggregation of these sentiment over a population represents opinion polling and has ...numerous applications. Current text-based sentiment analysis rely on the construction of dictionaries and machine learning models that learn sentiment from large text corpora. Sentiment analysis from text is currently widely used for customer satisfaction assessment and brand perception analysis, among others. With the proliferation of social media, multimodal sentiment analysis is set to bring new opportunities with the arrival of complementary data streams for improving and going beyond text-based sentiment analysis. Since sentiment can be detected through affective traces it leaves, such as facial and vocal displays, multimodal sentiment analysis offers promising avenues for analyzing facial and vocal expressions in addition to the transcript or textual content. These approaches leverage emotion recognition and context inference to determine the underlying polarity and scope of an individual's sentiment. In this survey, we define sentiment and the problem of multimodal sentiment analysis and review recent developments in multimodal sentiment analysis in different domains, including spoken reviews, images, video blogs, human–machine and human–human interactions. Challenges and opportunities of this emerging field are also discussed leading to our thesis that multimodal sentiment analysis holds a significant untapped potential.
Display omitted
•Sentiment and sentiment analysis are defined.•Current work on multimodal sentiment analysis is reviewed and summarized.•Challenges and opportunities in multimodal sentiment analysis are discussed.
Burial elaborations are a human behaviour that, in recent contexts can inform on social diversification, belief systems, and the introduction of new practices resulting from migration or cultural ...transmission. The study of mortuary practices in Mainland and Island Southeast Asia has revealed complex and diverse treatments of the deceased. This paper contributes to this topic with the description of three new burials excavated in Tron Bon Lei (Alor Island, Indonesia) dated to 7.5, 10, and 12 kya cal BP. In addition to the bioskeletal profiles and palaeohealth observations, we propose the adoption of archaeothanatological methods to characterise burial types in the region. Through the analysis of skeletal element representation, body position, articulation, and grave associations, we provide an example of a holistic approach to mortuary treatments in the Lesser Sunda Islands. Our results provide significant new data for understanding the evolution and diversification of burial practices in Southeast Asia, contributing to a growing body of literature describing prehistoric socio-cultural behaviour in this region.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Conceptual scientific and medical advances have led to a recent realization that there may be no single, one-size-fits-all diet and that differential human responses to dietary inputs may rather be ...driven by unique and quantifiable host and microbiome features. Integration of these person-specific host and microbiome readouts into actionable modules may complement traditional food measurement approaches in devising diets that are of benefit to the individual. Although many host-derived factors are hardwired and difficult to modulate, the microbiome may be more readily reshaped by environmental factors such as dietary exposures and is increasingly recognized to potentially impact human physiology by participating in digestion, the absorption of nutrients, shaping of the mucosal immune response and the synthesis or modulation of a plethora of potentially bioactive compounds. Thus, diet-induced microbiota alterations may be harnessed in order to induce changes in host physiology, including disease development and progression. However, major limitations in 'big-data' processing and analysis still limit our interpretive and translational capabilities concerning these person-specific host, microbiome and diet interactions. In this Review, we describe the latest advances in understanding diet-microbiota interactions, the individuality of gut microbiota composition and how this knowledge could be harnessed for personalized nutrition strategies to improve human health.
Despite the fact that buildings are designed for occupants in principle, evidence suggests buildings are often uncomfortable compared to the requirements of standards; difficult to control by ...occupants; and, operated inefficiently with regards to occupants’ preferences and presence. Meanwhile, practitioners –architects, engineers, technology companies, building managers and operators, and policymakers – lack the knowledge, tools, and precedent to design and operate buildings optimally considering the complex and diverse nature of occupants. Building on the success of IEA EBC Annex 66 (“Definition and simulation of occupant behavior in buildings”; 2013–2017), a follow-up IEA EBC Annex 79 (“Occupant-centric building design and operation”; 2018–2023) has been developed to address gaps in knowledge, practice, and technology. Annex 79 involves international researchers from diverse disciplines like engineering, architecture, computer science, psychology, and sociology. Annex 79 and this review paper have four main areas of focus: (1) multi-domain environmental exposure, building interfaces, and human behavior; (2) data-driven occupant modeling strategies and digital tools; (3) occupant-centric building design; and (4) occupant-centric building operation. The objective of this paper is to succinctly report on the leading research of the above topics and articulate the most pressing research needs – planned to be addressed by Annex 79 and beyond.
•Challenges and priorities in occupant-centric building design and operation.•Multi-domain occupant exposure, building interfaces, and human behavior.•Strategies and digital tools for data-driven occupant modeling.•Simulation-aided occupant-centric building design for comfort and energy.•Occupant-centric building controls and operations to adapt to occupants.
Response times (RT) distributions are routinely used by psychologists and neuroscientists in the assessment and modeling of human behavior and cognition. The statistical properties of RT ...distributions are valuable in uncovering unobservable psychological mechanisms. A potentially important statistical aspect of RT distributions is their entropy. However, to date, no valid measure of entropy on RT distributions has been developed, mainly because available extensions of discrete entropy measures to continuous distributions were fraught with problems and inconsistencies. The present work takes advantage of the cumulative residual entropy (CRE) function—a well-known differential entropy measure that can circumvent those problems. Applications of the CRE to RT distributions are presented along with concrete examples and simulations. In addition, a novel measure of instantaneous CRE is developed that captures the rate of entropy reduction (or information gain) from a stimulus as a function of processing time. Taken together, the new measures of entropy in RT distributions proposed here allow for stronger statistical inferences, as well as motivated theoretical interpretations of psychological constructs such as mental effort and processing efficiency.
Results of several studies have suggested that smartphone addiction has negative effects on mental health and well-being. To contribute to knowledge on this topic, our study had two aims. One was to ...investigate the relationship between risk of smartphone addiction and satisfaction with life mediated by stress and academic performance. The other aim was to explore whether satisfaction with life mediated by stress and academic performance facilitates smartphone addiction. To identify test subjects, systematic random sampling was implemented. A total of 300 university students completed an online survey questionnaire that was posted to the student information system. The survey questionnaire collected demographic information and responses to scales including the Smartphone Addiction Scale - Short Version, the Perceived Stress Scale, and the Satisfaction with Life Scale. Data analyses included Pearson correlations between the main variables and multivariate analysis of variances. The results showed that smartphone addiction risk was positively related to perceived stress, but the latter was negatively related to satisfaction with life. Additionally, a smartphone addiction risk was negatively related to academic performance, but the latter was positively related to satisfaction with life.
•Stress mediates the relationship between smartphone addiction and satisfaction with life.•Academic performance mediates the relationship b/w smartphone addiction & satisfaction with life.•There is a zero order correlation between smartphone addiction and satisfaction with life.
Human behavior analysis from big multimedia data has become a trending research area with applications to various domains such as surveillance, medical, sports, and entertainment. Facial expression ...analysis is one of the most prominent clues to determine the behavior of an individual, however, it is very challenging due to variations in face poses, illuminations, and different facial tones. In this paper, we analyze human behavior using facial expressions by considering some famous TV-series videos. Firstly, we detect faces using Viola-jones algorithm followed by tracking through Kanade-Lucas-Tomasi (KLT) algorithm. Secondly, we use histogram of oriented gradients (HOG) features with support vector machine (SVM) classifier for facial recognition. Next, we recognize facial expressions using the proposed light-weight convolutional neural network (CNN). We utilize data augmentation techniques to overcome the issue of appearance of faces from different views and lightening conditions in video data. Finally, we predict human behaviors using an occurrence matrix acquired from facial recognition and expressions. The subjective and objective experimental evaluations prove better performance for both facial expression recognition and human behavior understanding.
We explored the frequency and indices of smartphone addiction in a group of King Saud University students and investigated whether there were differences in smartphone addiction based on gender, ...social status, educational level, monthly income and hours of daily use. We developed a questionnaire probing smartphone addiction consisting of five dimensions: 1) overuse of smartphone, 2) the psychological-social dimension, 3) the health dimension, 4) preoccupation with smartphones, and 5) the technological dimension. After being validated, the questionnaire was administered to 416 students, both male and female, at King Saud University. Results revealed that addiction percentage among participants was 48%. The order of smartphone addiction indices were as follows: overuse of smartphone, the technological dimension, the psychological-social dimension, preoccupation with smartphones, and the health dimension. Significant gender differences were found in the degree of addiction on the whole questionnaire and all of its dimensions with the exception of the technological dimension in favor of males. Significant differences by social status were found in favor of the unmarried. Bachelor degree students were found to have the highest degree of addiction. Significant differences by hours of daily use were also detected in favor of participants using the smartphone for more than 4 h a day. As to the monthly income dimension, significant differences were found on the health dimension in favor of participants with lower monthly income.
•The addiction percentage among participants was 48%.•There are Significant gender and social status differences were found in the degree of addiction.•There are significant differences due to monthly income were found in the degree of addiction.•Bachelor degree students were found to have the highest degree of addiction.•There are significant differences due to hours of daily use were found in degree of addiction.
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