174 research outputs found

    ERiSA: building emotionally realistic social game-agents companions

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    We propose an integrated framework for social and emotional game-agents to enhance their believability and quality of interaction, in particular by allowing an agent to forge social relations and make appropriate use of social signals. The framework is modular including sensing, interpretation, behaviour generation, and game components. We propose a generic formulation of action selection rules based on observed social and emotional signals, the agent’s personality, and the social relation between agent and player. The rules are formulated such that its variables can easily be obtained from real data. We illustrate and evaluate our framework using a simple social game called The Smile Game

    TEACH (Train to Enable/Achieve Culturally Sensitive Healthcare)

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    Personnel from diverse ethnic and demographic backgrounds come together in both civilian and military healthcare systems, facing diagnoses that at one level are equalizers: coronary disease is coronary disease, breast cancer is breast cancer. Yet the expression of disease in individuals from different backgrounds, individual patient experience of disease as a particular illness, and interactions between patients and providers occurring in any given disease scenario, all vary enormously depending on the fortuity of the equation of "which patient happens to arrive in whose exam room." Previously, providers' absorption of lessons-learned depended on learning as an apprentice would when exposed over time to multiple populations. As a result, and because providers are often thrown into situations where communications falter through inadequate direct patient experience, diversity in medicine remains a training challenge. The questions then become: Can simulation and virtual training environments (VTEs) be deployed to short-track and standardize this sort of random-walk problem? Can we overcome the unevenness of training caused by some providers obtaining the valuable exposure to diverse populations, whereas others are left to "sink or swim"? This paper summarizes developing a computer-based VTE called TEACH (Training to Enable/Achieve Culturally Sensitive Healthcare). TEACH was developed to enhance healthcare providers' skills in delivering culturally sensitive care to African-American women with breast cancer. With an authoring system under development to ensure extensibility, TEACH allows users to role-play in clinical oncology settings with virtual characters who interact on the basis of different combinations of African American sub-cultural beliefs regarding breast cancer. The paper reports on the roll-out and evaluation of the degree to which these interactions allow providers to acquire, practice, and refine culturally appropriate communication skills and to achieve cultural and individual personalization of healthcare in their clinical practices

    Use of Radiomics Combined With Machine Learning Method in the Recurrence Patterns After Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma: A Preliminary Study

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    Objective: To analyze the recurrence patterns and reasons in patients with nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiotherapy (IMRT) and to investigate the feasibility of radiomics for analysis of radioresistance.Methods: We analyzed 306 NPC patients treated with IMRT from Jul-2009 to Aug-2016, 20 of whom developed with recurrence. For the NPCs with recurrence, CT, MR, or PET/CT images of recurrent disease were registered with the primary planning CT for dosimetry analysis. The recurrences were defined as in-field, marginal or out-of-field, according to dose-volume histogram (DVH) of the recurrence volume. To explore the predictive power of radiomics for NPCs with in-field recurrences (NPC-IFR), 16 NPCs with non-progression disease (NPC-NPD) were used for comparison. For these NPC-IFRs and NPC-NPDs, 1117 radiomic features were quantified from the tumor region using pre-treatment spectral attenuated inversion-recovery T2-weighted (SPAIR T2W) magnetic resonance imaging (MRI). Intraclass correlation coefficients (ICC) and Pearson correlation coefficient (PCC) was calculated to identify influential feature subset. Kruskal-Wallis test and receiver operating characteristic (ROC) analysis were employed to assess the capability of each feature on NPC-IFR prediction. Principal component analysis (PCA) was performed for feature reduction. Artificial neural network (ANN), k-nearest neighbor (KNN), and support vector machine (SVM) models were trained and validated by using stratified 10-fold cross validation.Results: The median follow up was 26.5 (range 8–65) months. 9/20 (45%) occurred in the primary tumor, 8/20 (40%) occurred in regional lymph nodes, and 3/20 (15%) patients developed a primary and regional failure. Dosimetric and target volume analysis of the recurrence indicated that there were 18 in-field, and 1 marginal as well as 1 out-of-field recurrence. With pre-therapeutic SPAIR T2W MRI images available, 11 NPC-IFRs (11 of 18 NPC-IFRs who had available pre-therapeutic MRI) and 16 NPC-NPDs were subsequently employed for radiomic analysis. Results showed that NPC-IFRs vs. NPC-NPDs could be differentiated by 8 features (AUCs: 0.727–0.835). The classification models showed potential in prediction of NPC-IFR with higher accuracies (ANN: 0.812, KNN: 0.775, SVM: 0.732).Conclusion: In-field and high-dose region relapse were the main recurrence patterns which may be due to the radioresistance. After integration in the clinical workflow, radiomic analysis can be served as imaging biomarkers to facilitate early salvage for NPC patients who are at risk of in-field recurrence

    Adult Neural Stem Cell Regulation by Small Non-coding RNAs: Physiological Significance and Pathological Implications

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    The adult neurogenic niches are complex multicellular systems, receiving regulatory input from a multitude of intracellular, juxtacrine, and paracrine signals and biological pathways. Within the niches, adult neural stem cells (aNSCs) generate astrocytic and neuronal progeny, with the latter predominating in physiological conditions. The new neurons generated from this neurogenic process are functionally linked to memory, cognition, and mood regulation, while much less is known about the functional contribution of aNSC-derived newborn astrocytes and adult-born oligodendrocytes. Accumulating evidence suggests that the deregulation of aNSCs and their progeny can impact, or can be impacted by, aging and several brain pathologies, including neurodevelopmental and mood disorders, neurodegenerative diseases, and also by insults, such as epileptic seizures, stroke, or traumatic brain injury. Hence, understanding the regulatory underpinnings of aNSC activation, differentiation, and fate commitment could help identify novel therapeutic avenues for a series of pathological conditions. Over the last two decades, small non-coding RNAs (sncRNAs) have emerged as key regulators of NSC fate determination in the adult neurogenic niches. In this review, we synthesize prior knowledge on how sncRNAs, such as microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs), may impact NSC fate determination in the adult brain and we critically assess the functional significance of these events. We discuss the concepts that emerge from these examples and how they could be used to provide a framework for considering aNSC (de)regulation in the pathogenesis and treatment of neurological diseases

    Video games as a source of extramural English:Finnish university students’ perspective

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    Abstract. This thesis examines how video games as an entertaining pastime activity may function as a source of extramural English language learning for Finnish players. Previous research about video games and learning has been primarily focused on identifying learning principles deeply rooted in the design of video games. This study examines video games in their immediate sociocultural context, as a form of popular culture comprised of complex communities and activities. The study applied qualitative research methods. The data for this study comes from ten semi-structured interview sessions with Finnish university students of English who were active gamers during their early formal education and listed playing video games as a pastime activity. The interview required informants to give information about their experiences and opinions in relation to video games and English second language learning. The results of the thesis show that the informants consider video games as a significant, effective, and versatile source of additional language learning. Additionally, the results show that the learning experiences described by the informants often realize the characteristics of modern sociocultural learning theories and approaches.Tiivistelmä. Tässä opinnäytetyössä tutkitaan, miten englanninkielisten videopelien pelaaminen voi edistää suomenkielisten pelaajien kouluajan ulkopuolista oppimista. Aikaisempi tutkimus pelien ja oppimisen suhteesta on keskittynyt pitkälti pelien oppimiselle olennaisten toimintaperiaatteiden kartoittamiseen. Tässä tutkimuksessa tarkastellaan pelejä ja oppimista irrottamatta niitä sosiokulttuurisesta viitekehyksestään populaarikulttuurin muotona, joka koostuu monitahoisista yhteisöistä ja aktiviteeteistä. Tutkimusmenetelmä on laadullinen. Tutkimusaineisto koostuu teemahaastatteluista, jonka kymmenen haastateltavaa ovat äidinkielenään suomea puhuvia englannin kielen yliopisto-opiskelijoita. Kaikki haastateltavat harrastivat videopelejä peruskoulun aikana. Haastattelussa osallistujia pyydettiin kertomaan kokemuksistaan ja mielipiteistään englannin kielen oppimisesta videopelien kautta. Tutkimus osoittaa, että haastateltaville videopelit ovat olleet merkittävä, hyvin toimiva ja monipuolinen kanava englannin kielen oppimisessa. Lisäksi tutkimuksessa todetaan, että haastateltavien kuvauksien perusteella pelien kautta tapahtuva oppiminen myötäilee nykyaikaisten sosiokulttuuristen oppimiskäsitysten malleja

    A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey

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    The growing interest in the Metaverse has generated momentum for members of academia and industry to innovate toward realizing the Metaverse world. The Metaverse is a unique, continuous, and shared virtual world where humans embody a digital form within an online platform. Through a digital avatar, Metaverse users should have a perceptual presence within the environment and can interact and control the virtual world around them. Thus, a human-centric design is a crucial element of the Metaverse. The human users are not only the central entity but also the source of multi-sensory data that can be used to enrich the Metaverse ecosystem. In this survey, we study the potential applications of Brain-Computer Interface (BCI) technologies that can enhance the experience of Metaverse users. By directly communicating with the human brain, the most complex organ in the human body, BCI technologies hold the potential for the most intuitive human-machine system operating at the speed of thought. BCI technologies can enable various innovative applications for the Metaverse through this neural pathway, such as user cognitive state monitoring, digital avatar control, virtual interactions, and imagined speech communications. This survey first outlines the fundamental background of the Metaverse and BCI technologies. We then discuss the current challenges of the Metaverse that can potentially be addressed by BCI, such as motion sickness when users experience virtual environments or the negative emotional states of users in immersive virtual applications. After that, we propose and discuss a new research direction called Human Digital Twin, in which digital twins can create an intelligent and interactable avatar from the user's brain signals. We also present the challenges and potential solutions in synchronizing and communicating between virtual and physical entities in the Metaverse

    Characterization of the Lotus Japonicus nuclear pore NUP107-160 subcomplex in plant-microbe symbiosis

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    An architecture for emotional facial expressions as social signals

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