Universal and Culture-Specific Conceptualization of Anger in Russian

1. Introduction Emotion concept used to be treated as an arbitrary and irrational semantic domain escaping any linguistic research. Considering that emotion is fundamentally introspective concept only accessible to the experiencing subject and is basically culture-dependent concept(Russell 1991), it is understandable that emotion concept has long been an alienated subject matter in linguistic semantics. Only through cognitive approach to language and conceptual metaphor theory, emotion concepts came to be accounted for as having coherent semantic substance. Köecses and Lakoff's pioneering research on 'anger' in English(Lakoff 1987) shows how emotionality and rationality are not mutually exclusive and how emotion concepts are experientially grounded. Through cognitive approach to language and emotion concept, the traditional reason-emotion binarism and cognition-affect dichotomy came to be reexamined.1)This research was funded by Korean Research Foundation (KRF-2004-074-AM0060)

Flightless-I Controls Fat Storage in Drosophila

Triglyceride homeostasis is a key process of normal development and is essential for the maintenance of energy metabolism. Dysregulation of this process leads to metabolic disorders such as obesity and hyperlipidemia. Here, we report a novel function of the Drosophila flightless-I (fliI) gene in lipid metabolism. Drosophila fliI mutants were resistant to starvation and showed increased levels of triglycerides in the fat body and intestine, whereas fliI overexpression decreased triglyceride levels. These flies suffered from metabolic stress indicated by increased levels of trehalose in hemolymph and enhanced phosphorylation of eukaryotic initiation factor 2 alpha (eIF2??). Moreover, upregulation of triglycerides via a knockdown of fliI was reversed by a knockdown of desat1 in the fat body of flies. These results indicate that fliI suppresses the expression of desat1, thereby inhibiting the development of obesity; fliI may, thus, serve as a novel therapeutic target in obesity and metabolic diseases

Generalized matrix-based Bayesian network for multi-state systems

To achieve a resilient society, the reliability of core engineering systems should be evaluated accurately. However, this remains challenging due to the complexity and large scale of real-world systems. Such complexity can be efficiently modelled by Bayesian network (BN), which formulates the probability distribution through a graph-based representation. On the other hand, the scale issue can be addressed by the matrix-based Bayesian network (MBN), which allows for efficient quantification and flexible inference of discrete BN. However, the MBN applications have been limited to binary-state systems, despite the essential role of multi-state engineering systems. Therefore, this paper generalizes the MBN to multi-state systems by introducing the concept of composite state. The definitions and inference operations developed for MBN are modified to accommodate the composite state, while formulations for the parameter sensitivity are also developed for the MBN. To facilitate applications of the generalized MBN, three commonly used techniques for decomposing an event space are employed to quantify the MBN, i.e. utilizing event definition, branch and bound (BnB), and decision diagram (DD), each being accompanied by an example system. The numerical examples demonstrate the efficiency and applicability of the generalized MBN. The supporting source code and data can be download at https://github.com/jieunbyun/Generalized-MBN-multi-state

Linear Programming by Delayed Column Generation for Bounds on Reliability of Larger Systems

In various efforts to secure the resilience of community, accurate reliability analysis of civil systems is critical considering their pivotal functions. As such systems generally consist of multiple components, their reliability analysis requires complete information to construct joint probabilistic dis-tributions of component events, which is rarely available in practice. In order to obtain the best estimates on the system reliability based on the available information, the linear programming (LP) bounds method was proposed (Song and Der Kiureghian 2003).The method obtains bounds on system reliability by solv-ing LP problems constructed by decomposing the event space into mutually exclusive and collectively exhaustive (MECE) events. Despite the optimality and flexibility of the LP bounds method, there is a limitation in the size of systems as the number of MECE events increases exponentially in regards to that of component events. In order to address this issue, this paper develops an alternative LP bounds formu-lation by employing delayed column generation, in which the LP is solved as an iteration of smaller binary integer programming (BIP). The BIP can be formulated by Boolean algebra that represents the inclusion relationships between component events, system event, and constraint events. The proposed formulation requires polynomial memory in regards to the number of constraints, allowing the evaluation of the LP bounds for larger systems and changing the major bottleneck from the number of components to that of constraint events incorporated into the LP. Four numerical examples are provided to illustrate and demonstrate the proposed method.This research was supported by a grant (18SCIP-B146946-01) from Smart Civil Infrastructure Re-search Program funded by Ministry of Land, In-frastructure, and Transport of Korean government

Efficient Optimization for Multi-Objective Decision-Making on Civil Systems Using Discrete Influence Diagram

The breakdown of civil systems, e.g. bridge networks and water distribution networks, has a significant social and economic impact, highlighting the importance of optimal decision-making on such systems. Modeling and optimization of probabilistic decision-making problems for civil systems, can be facilitated by graphical methodologies such as influence diagram (ID). However, the converging structure in IDs representing civil systems, which relates the random variables standing for component events and that for system event, results in the exponential increase in the number of modeling parameters and variables to be optimized as that of component events increases. In order to address these challenges, in this paper, the recently proposed matrix-based Bayesian network (MBN) is employed to quantify the IDs. To facilitate the optimization process, a proxy objective function is also proposed. The proxy func-tion not only significantly reduces the number of variables to be optimized, but also allows an efficient framework for multi-objective optimization in which the weighted sum of the objectives is optimized to obtain a set of non-dominated solutions. Three numerical examples demonstrate the performance of the proposed methodology.This research was supported by a grant (18SCIP-B146946-01) from Smart Civil Infrastructure Re-search Program funded by Ministry of Land, In-frastructure, and Transport of Korean government

Production of conductive bacterial cellulose-polyaniline membranes in the presence of metal salts

This study presents a cost-effective method of enhancing the electrical conductivity and washing durability of bacterial cellulose (BC)-polyaniline (PANI) membrane by the addition of metal salt. In this study, two types of metal salts were tested: copper (II) sulfate and iron (II) sulfate. The optimal condition to produce BC-PANI-metal salt membranes was 0.05% (w/v) of copper (II) sulfate (copper salt). X-ray diffraction analysis showed that the crystallinity of BC-PANI increased after adding copper salt. According to the increased degree of crystallinity, the polymer chain structure of BC-PANI-copper salt (BC-PANI-Cu) was more organized than that of BC-PANI, as confirmed by scanning electron microscopy. In addition, this ordered structure of BC-PANI-Cu indicated enhanced electrical conductivity. Moreover, the addition of copper salt improved the electrical conductivity of BC-PANI to a level about 3.8 times higher than that of BC-PANI produced without metal salt, and it retained about 40% of its original electrical conductivity after three washing cycles. From the results, the addition of copper salt improved both the electrical conductivity and washing durability of the BC-PANI membrane.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. NRF-2019R1A2C1009217).info:eu-repo/semantics/publishedVersio

From Agasa Cristie to Group Image Play-Analysis of Horror Survival Game Panic Room : Escaping from the Den on Emotional Elements Development

A maniac computer game genre called "Survival Horror Games‟ is aimed for making gamers feel cathartic feeling when they escaped from the designed horror successfully. The degree of gaming quality, however, is not easy to measure. In this paper, we apply Caillois‟ game playing categories and other standards to measure how a game induces the feeling of fear and other emotional experience to players. Once dominated horror survival game series called Panic Room: Escaping from the Den was chosen to analyze and evaluate with those standards as well as its narratives and subsystems. Especially the 2nd version was most welcomed to users among 4 versions thus we focused on the difference between the version 1 and the version 2 in terms of game playing and fear elements in the game content and story structure. In result, version 2 showed much more Agon and Mimicry and all other fear elements than version 1. The group image playing structure and conference/collection subsystem that were newly provided to version 2 were attributed to its success

Postoperative cervical length to predict success of repeat cerclage in singleton pregnancies with prolapsed membranes after prior cerclage

BackgroundThis study aimed to evaluate the outcome of repeat cerclage (RC) in singleton pregnancies with prolapsed membranes following a prior cerclage and analyze predictive factors for delivery at ≥26 weeks of gestation following RC.Materials and methodsPatients who underwent RC between 2010 and 2020 at the Hallym University Medical Center were reviewed. Women with singleton pregnancies with prolapsed membranes following prior cerclage were candidates for RC. We analyzed the characteristics, pregnancy outcomes, perioperative clinical and laboratory findings, and postoperative cervical length (CL) to identify the factors for predicting delivery at ≥26 weeks following RC.ResultsThirty-five women with RC were identified; the median gestational age (GA) at a prior cerclage was 14 weeks, the average GA at RC was 21 + 3 weeks, and the median GA at delivery following RC was 26 + 2 weeks. Patients were divided into two groups based on their delivery status at 26 weeks: 17 women delivered at <26 weeks (range, 18 + 4–25 + 6 weeks) (Group A) and 18 women delivered at ≥26 weeks (range, 26 + 2–40 + 3 weeks) (Group B). The median GA at delivery in group A was 22 + 4 weeks, whereas that in group B was 33 + 4 weeks (p < 0.001). No differences in preoperative clinical and laboratory findings were observed between the two groups. However, the postoperative CL in group A was significantly shorter than that in group B (12 mm vs. 21.5 mm, p < 0.001). The ROC curve of postoperative CL predicting delivery at ≥26 weeks showed an AUC of 0.843; a CL of 20 mm showed a sensitivity of 61.1% and a specificity of 100%.ConclusionRC may prolong singleton pregnancies with prolapsed membranes following prior cerclage. A postoperative CL ≥20 mm may predict the success of RC