Search

Background: Endotracheal intubation for inhalation anaesthesia in pigs is not considered a good anaesthetic method as it is technically difficult because of oral anatomy and the presence of excess tissues in the oropharyngeal region. Moreover, the major limitation of inhalation anaesthesia is that it requires the use of a cumbersome and costly anaesthetic machine, including a suitable breathing system and vaporizer and is the exposure of operating-room personnel to the pollution in the ambient air. Therefore, the present study was undertaken to evaluate the effect of propofol, ketamine and their combination 'Ketofol' as a TIVA in pigs. Methods: The study was conducted in eighteen piglets of either sex. The piglets were randomly divided into three groups with six animals in each group. All the three groups were premedicated with Atropine sulphate @ 0.04 mg/kg body weight and Xylazine Hydrochloride @ 1 mg/kg body weight I.M. and Medazolam @ 0.5 mg/kg body weight I.M. with minimum forcible restraint as preanaesthetic. In group-I, propofol @ 5 mg/kg body weight, in group-II, ketamine @ 5 mg/kg body weight and in group-III, ketofol @ 4 mg/kg body weight was administered intravenously for induction after 15 minutes of pre-anaesthetic administration. Surgical anaesthesia was maintained for 90 minutes in all three groups viz. group-I, group-II and group-III with propofol @ 2.5 mg/kg, ketamine @ 2.5 mg/kg and ketofol @ 2 mg/kg body weight respectively by intermittent bolus injection (IBI) technique. Clinical and cardiopulmonary profiles were evaluated before administration of the anaesthetic agent (0 minutes) then at 15, 30, 60 and 90 minutes during and after administration of anaesthetic agents to evaluate their anaesthetic effect. Result: The study revealed that induction time (IT), duration of analgesia (DOA), duration of recumbency (DOR) and recovery time (RT) interval showed better result in the combination of ketamine and propofol group as compared to propofol and ketamine-induced individual group. The temperature and respiration rate was significantly decreased in all the groups at 30 minutes during TIVA whereas heart rate was significantly increased in all the groups at 15 minutes. The combination of ketamine and propofol group showed a consistent diastolic pressure and systolic pressure during the entire period of anaesthesia. The SPO2 in the ketamineinduced group showed a significant decrease (P<0.01) as compared to the propofol and ketofol group. It was concluded that the anaesthetic drug combinations resulted in smooth and uneventful induction with mild cardiopulmonary depressions and rapid recovery. [ABSTRACT FROM AUTHOR]

AbstractConversational agents are growing in popularity, and as such they must provide a good user experience and meet the needs of the users. Yet, how to measure the user experience in the conversational AI scenario remains an open and urgent question to be solved, which may hinder further empirical studies on human-agent interactions. In fact, there have been very few studies that explore how users perceive interacting with these conversational agents, which is important to ensure their sustainability. Accordingly, in this work, we used a subjective technique by following a measurement approach to develop a standardized measurement instrument/scale called the Conversational Agent Scale for User Experience. In terms of the methodology, we used a mixed-method approach involving an iterative process spanning across six different user studies (three qualitative and three quantitative) at different points of time for the purpose of dimension identification, item generation and subsequent item refinements. As a part of the qualitative studies we conducted a Systematic Literature Review, semi-structured interviews with users of conversational agents, and expert interviews. For the quantitative studies a lab-based experiment was performed for the pre-test, followed by two online surveys as a part of pilot testing and scale development. The qualitative studies initially identified a total of 13 distinct user experience dimensions and 418 measurement items. Finally, the Exploratory Factor Analysis as a part of the main survey resulted in 9 user experience dimensions (practicality perception, proficiency, humanness, sentiment, robustness, etiquette & mannerism, personality, anthropomorphism, and ease of use) and 34 measurement items. This was supplemented by conducting another Confirmatory Factor Analysis for establishing the reliability and validity of the proposed scale, together with checking the model-fit indices. All the 9 dimensions had sufficient validity, and a reasonable level of statistical reliability. Some of the user experience dimensions like humanness, personality, anthropomorphism, and etiquette & mannerism show the uniqueness of the conversational AI scenario from the traditional usage factors used commonly while evaluating graphical user interface-based systems. This work fills the gap of a lack of research on how to classify and measure the conversational experience of users and provides a reference for practitioners and designers in developing these agents and continuously improving the usage experience. [ABSTRACT FROM AUTHOR]

Online food delivery applications (OFDA) are an emerging area of an online-to-offline (O2O) service delivery platform. In times of the COVID-19 pandemic the OFDA apps can help the restaurant and catering industry to thrive by allowing the consumers to order food from the safety of their homes. In this aspect evaluating the end-to-end service quality is an important issue starting right from the interaction with the OFDA apps for searching and ordering food to the last mile consumer experience with the delivery quality and food quality. The initial experience with the OFDA apps is captured through three mobile app attributes: visual design, navigational design, and information design. Consumer satisfaction and loyalty are considered to be the dependent variables in this study. Data is collected using an online questionnaire from 315 university students in India who are actual users of different OFDA apps during the pandemic period. Data analysis is done using a Partial Least Squares – Structural Equation Modeling approach. The findings show that satisfaction is the greatest predictor of loyalty, followed by food quality. Among the mobile app attributes information design has the highest impact on both satisfaction and loyalty, followed by navigational and visual design respectively. Based on the results appropriate theoretical and practical implications are discussed and suggested. [ABSTRACT FROM AUTHOR]

Consumer Internet of Things (CIoT) is an emerging area being represented by a variety of smart consumer electronic (CE) devices. Often times, there are significant security and privacy issues with these devices, which are unknown to the users when they decide to purchase. While existing CE literatures have investigated the technical aspects of securing a device or protecting privacy, what effects these factors have on the purchase decision of the users of CIoT devices is unknown. The current work attempts to solve this gap in CE knowledge by investigating how security affects the purchase decision, what personal factors are relevant in this scenario, and what effects does framing have on the purchase decision. A mixed-method study design is used for data collection combining semi-structured interviews and a stated-choice experiment. An Exploratory Factor Analysis is used for identifying the personal factors. A Multinomial Logit Model approach is used for testing the proposed causal model. Security has the highest effect on purchase decision, followed by price, functionality, and aesthetics & coolness. The effects of framing are also established in relation to gain frames. Based on the results different buyer categories are identified, and the research implications are discussed from a CE community perspective. [ABSTRACT FROM AUTHOR]

Drawing on social exchange theory, this research examines how inclusive leaders foster innovative work behavior and creativity in employees. Data were collected in two steps from the 320 employees working in Chinese R&D organizations to draw the result for this research. The findings indicate a positive impact of inclusive leadership on innovative work behavior and creativity. In addition, intrinsic motivation mediates this relationship. The implications and future research are also discussed. [ABSTRACT FROM AUTHOR]

A general theory of tabular form root distribution procedures based on LDL(super *) factorization of Bezoutians has been presented in this paper. In particular, we have concentrated on the singular cases arising in the Routh test. A one-to-one correspondence has been established between the rank profile of the underlying Bezoutians and the occurrence of the singular cases. Combining this interpretation with the newly developed factorization procedures of Pal and Kailath, it has been possible to extend the new unified approach of Lev-Ari, Bistritz, and Kailath to the singular cases. By doing so not only did we obtain all the known procedures but we also obtained new results.

A general theory of tabular form root distribution procedures based on LDL(super *) factorization of Bezoutians is presented in this note. In particular, we concentrate on the singular cases arising in the Schur-Cohn test. A one-to-one correspondence is established between the rank profile of the underlying Bezoutians and the occurrence of the singular cases. Combining this interpretation with the newly developed factorization procedures of Pal and Kailath, it is possible to extend the new unified approach of Lev-Ari, Bistritz, and Kailath to the singular cases. By doing so, not only do we derive the well known Schur-Cohn procedure, but we also obtain new results. In fact, we are able to derive a new completely recursive procedure to deal with the 'first kind of singularity.'

Physical closure of educational institutes worldwide due to the COVID-19 pandemic has resulted in the emergence of a new era of video-based learning. The current circumstances are unique that have forced students to use digital technologies for their learning purpose. However, the successful usage of such a system relies on the understanding of the adoption factors, for which an integrated model is proposed based on the Technology Acceptance Model and the Task Technology Fit Model. Additionally, this work considers the moderating effects of gender and digital inequality. Data are collected from 232 students all of whom have taken part in a full-semester video-based online learning course in times of the pandemic. A Partial Least Squares method is used for analyzing the data. Results show that video-based learning positively fits into the student's perception and their actual use of the system. The effect of individual characteristics is more than the technology characteristics on the task-technology-fit chain. The integrated model can predict 64.6% of the variance in the final dependent variable: actual usage of video-based learning. Further, while the moderating effect of gender is found to be significant, that for digital inequality is non-significant. Finally, the theoretical and practical implications are discussed. [ABSTRACT FROM AUTHOR]

Online shopping is an emerging trend throughout the world. Likewise, it is used in China among Chinese consumers, but not all foreigners use it frequently due to several factors. This study discussed those factors which cause hindrance for foreigners to use online shopping and their behavior towards it. To do so, the authors have proposed the model by extending the technology acceptance model (TAM). The data were collected from the international students in China through a survey questionnaire and analyzed by SPSS to draw the results of the proposed relationships. The findings show that the online shopping behavior of international students in China is negatively related to financial risk and positively related to trust and ease of use. Moreover, purchase intention mediates these relationships. The results will be useful for consumers and online sellers to retain existing consumers and attract more foreigners studying in China. Moreover, the paper mentioned the implications and future directions of the study. [ABSTRACT FROM AUTHOR]

The metaverse is an emerging area of research and has a lot of potential in providing individuals with an alternate place of inhabitation. The importance of metaverse escapism although has been discussed in current literatures, but what can be its drivers and consequences is unclear. From a theoretical perspective, escapism can be modelled in two way: cause-based (positivist) and effect-based (negativist). In this work we propose a positivist approach by theorizing how different types of real-life problems (autonomy, competence, and relatedness) will drive metaverse escapism, fostering attachment with this virtual place. We collect 585 responses from users of VR-based metaverse applications like Horizon World, VR Chat, etc. The results are analysed using Partial Least Squares based Structural Equation Modelling (PLS-SEM) technique. We found that only autonomy and competence problems lead to metaverse escapism, and further to virtual place attachment. Metaverse escapism acts like a full mediator in the link between real-world problems and virtual place attachment. Likewise, anxiety positively moderates the relationship between competence problem and escapism, but negatively moderates the relationship between autonomy problem and escapism. Our work contributes to the metaverse literatures by identifying those who are likely to engage in metaverse escapism. Our model explains 60.4% of the variance in virtual place attachment, indicating the practical significance of identifying the correct targets and fostering their attachment with this virtual world. • We examine how real-life problems impact attachment with metaverse. • Autonomy and competence problems motivate metaverse escapism. • Escapism is explored from a positive approach. • Anxiety weakens autonomy problems but strengthens competence problems on escapism. [ABSTRACT FROM AUTHOR]

Over the past few years there has been an exponential increase in the amount of multimedia data being streamed over the Internet. At the same time, we are also witnessing a change in the way quality of any particular service is interpreted, with more emphasis being given to the end-users. Thus, silently there has been a paradigm shift from the traditional Quality of Service approach (QoS) towards a Quality of Experience (QoE) model while evaluating the service quality. A lot of work that tries to evaluate the quality of audio, video, and multimedia services over the Internet has been done. At the same time, research is also going on trying to map the two different domains of quality metrics, i.e., the QoS and QoE domain. Apart from the work done by individual researchers, the International Telecommunications Union (ITU) has been quite active in this area of quality assessment. This is obvious from the large number of ITU standards that are available for different application types. The sheer variety of techniques being employed by ITU as well as other researchers sometimes tends to be too complex and diversified. Although there are survey papers that try to present the current state of the art methodologies for video quality evaluation, none has focused on the ITU perspective. In this work, we try to fill up this void by presenting up-to-date information on the different measurement methods that are currently being employed by ITU for a video streaming scenario. We highlight the outline of each method with sufficient detail and try to analyze the challenges being faced along with the direction of future research. [ABSTRACT FROM AUTHOR]

Artificial-intelligence (AI) powered conversational (CAI) agents have been growing in popularity. Like human personality, CAI agent personality can also impact the relationship users develop with them. In this work we adopt a multi-methodological systematic approach for generating CAI agent personality descriptors. 235 unique descriptors are obtained grouped into 8 personality dimensions. Having generated the personality framework, we propose a research model based on Stimulus Organism Response framework and Sternberg's Triangular Theory of Love for explaining how these personality traits lead to formation of love with these agents affecting their usage scenario. Results indicate that all the three components of love (passion, intimacy, and commitment) have significant effects on the usage scenario. However, depending upon the agent personality the nature of relationships varies. Cognitive personality results in fatuous love, affective personality results in consummate love, and social personality results in friendly relationship. A conceptual difference is observed between brand love, and the "love for AI." The results of this research will not only help the HCI designers to create suitable machine personality for various AI-based agents, but it will also provide an unconventional approach towards examining adoption of emerging AI-based technologies by exploring the love aspect between man and machines. • Eight personality dimensions of conversational agents. • Combining human, brand, and website personality frameworks. • Love components (passion, intimacy, and commitment) affect usage scenario. • Agent personality type determines the nature of loving relationship. [ABSTRACT FROM AUTHOR]

We propose a modular no-reference video quality prediction model for videos that are encoded with H.265/HEVC and VP9 codecs and viewed on mobile devices. The impairments which can affect video transmission are classified into two broad types depending upon which layer of the TCP/IP model they originated from. Impairments from the network layer are called the network QoS factors, while those from the application layer are called the application/payload QoS factors. Initially we treat the network and application QoS factors separately and find out the 1 : 1 relationship between the respective QoS factors and the corresponding perceived video quality or QoE. The mapping from the QoS to the QoE domain is based upon a decision variable that gives an optimal performance. Next, across each group we choose multiple QoS factors and find out the QoE for such multifactor impaired videos by using an additive, multiplicative, and regressive approach. We refer to these as the integrated network and application QoE, respectively. At the end, we use a multiple regression approach to combine the network and application QoE for building the final model. We also use an Artificial Neural Network approach for building the model and compare its performance with the regressive approach. [ABSTRACT FROM AUTHOR]

The primary aim of this paper is to propose a non-linear regression based technique for mapping different network Quality of Service (QoS) factors to an integrated end-user Quality of Experience (QoE) or Mean Opinion Score (MOS) value for an online video streaming service on a mobile phone. We use six network QoS factors for finding out the user QoE. The contribution of this paper is threefold. First, we investigate the impact of the network QoS factors on the perceived video quality. Next, we perform an individual mapping of the significant network QoS parameters obtained in stage 1 to the user QoE based upon a non-linear regression method. The optimal QoS to QoE mapping function is chosen based upon a decision variable. In the final stage, we evaluate the integrated QoE of the system by taking the combined effect of all the QoS factors considered. Extensive subjective tests comprising of over 50 people across a wide variety of video contents encoded with H.265/HEVC and VP9 codec have been conducted in order to gather the actual MOS data for the purpose of QoS to QoE mapping. Our proposed hybrid model has been validated against unseen data and reveals good prediction accuracy. [ABSTRACT FROM AUTHOR]