To assess the reliability of chronobiological models of sleep/wake regulation, it is necerssary that the models predict the data which has been studied in sleep research, and they should be generalized across all ages. To date, many adult human data on such models have accumulated, yet it is evident that a comprehensive theory of the biorhythmic aspects of sleep/wake states has not established. Circadian rhythms such as the time going to bed, sleep onset, slow wave sleep pressure, periodicity of REM sleep, daytime performance, and early evening alertness are resumed everyday. Even in adult humans, sleep is inherently polyphasic. In both the disentrained and entrained states, naps when allowed tend to recur in a temporally lawful manner. The monophasic sleep pattern of most industrial societies therefore appears to be purely of social origin. The endogenous biorhythmic nature of circasemidian sleep tendency is supported by the ubiquity of the phenomenon across all ages. The NREM/REM sleep cycle within sleep with its inherent physiological, endocrine, and neurochemical fluctuations represents the best-documented ultradian sleep rhythms. Also, a daytime ultradian variation in sleepiness with a periodicity similar to nocturnal NREM/REM cycle(BRAC hypothesis) is suggested. This review article provides a brief synoptic review of the evidences for circadian, circasemidian, and ultradian sleep/wake rhythms, and then the authour will suggest the issues which expedite fuller modeling of sleep/wake system, to be further discussed.
In this study, the effect of user characteristics and technical characteristics of a blockchain-based financial platform on the intention to use of financial consumers was analyzed. Also, in this influence relationship, we analyzed what kind of causal relationship between relative advantage and perceived risk on intention to use. From June 1 to July 30, 2021, a non-face-to-face self-filling online survey was conducted with a sample of subjects who had experience using a financial platform grafted with blockchain technology, and the study was conducted in 187 copies. For statistical processing, frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis and 3-step mediated regression analysis were performed using SPSS 21.0 program. The significance level of the statistical value was set to less than 95%. The research results are as follows. First, it was found that innovativeness and usefulness affect the intention to use in the user characteristics. Second, in the technical characteristics, compatibility and reliability were found to affect the intention to use. Third, it was found that relative advantage and perceived risk play a partial mediating role in the relationship between user characteristics and intention to use. Fourth, it was found that relative advantage and perceived risk play a partial mediating role in the relationship between technical characteristics and intention to use. Fifth, it was found that there were differences in the ubiquity of user characteristics, compatibility of technical characteristics and intention to use according to the experience of using the certificate. The results of this study can contribute to the development of a financial platform based on the Internet of Things.
Using Herzberg's motive hygiene theory, this study also investigated the influence of motivation factors and hygiene factors on acceptance and resistance of mobile facial recognition payment services, and the influence of consumer innovation as a parameter on acceptance and resistance from motivation factors and hygiene factors. A survey was conducted on Chinese users who had experience using mobile payment services. IBM SPSS Statistics 26 and SmartPLS 3.0 were used for statistical analysis. As a result of the analysis, the motivating factors of mobile facial recognition payment services have a positive (+) impact on acceptance, and there were no significant results on resistance. In addition, hygiene factors have been shown to have negative (-) effects on acceptance and positive (+) effects on resistance. Consumer innovation, which is a parameter in relation to motivation factors and acceptance and resistance, had a partial mediation effect, and a partial mediation effect was also seen in the relationship between hygiene factors and resistance, but no mediation effect was found in the relationship between hygiene factors and acceptance. The motivating factors found through research results such as rapidity, ubiquity, perceived usability, perceived ease of use, privacy concerns, security, status quo inertia, use barriers, and loss avoidance, which are factors of non-contact and hygiene, can be used as basic data for activating mobile facial recognition payment services.
The purpose of this study is to identify the difficulties in business implementation that blockchain suppliers are experiencing, and to suggest ways to promote blockchain technology by solving them. First, industrial surveys of blockchain supply companies were collected. Next, a survey was conducted to confirm whether financial service users intend to use blockchain technology. The research results are as follows. First, in user characteristics, usefulness and innovation were found to have an effect on intention to use. In the technical characteristics, suitability and reliability were found to affect the intention to use. Second, in user characteristics, usefulness and innovativeness were found to affect the intention to use by mediating promotion conditions. In the technical characteristics, suitability and reliability were found to affect the intention to use by mediating the promotion conditions. Third, it was found that the new technology environment modulates the effect of ubiquity and innovativeness on the intention to use. The new technology environment was found to moderate the impact of security on intention to use. Fourth, it was found that the organizational environment moderates the effect of security and suitability on the intention to use. A plan to solve the difficulties of these blockchain suppliers and a plan to promote blockchain-based financial services are presented.
Hee-Seon Kim;Dae-Weon Kim;Byung-Man Chae;Sang-Woo Lee
Resources Recycling
/
v.32
no.3
/
pp.9-17
/
2023
Efforts are currently underway to develop a method for efficiently recovering lithium from the cathode material of waste lithium iron phosphate batteries (LFP). The successful application of lithium battery recycling can address the regional ubiquity and price volatility of lithium resources, while also mitigating the environmental impact associated with both waste battery material and lithium production processes. The isomorphic substitution leaching process was used to recover lithium from spent lithium iron phosphate batteries. Lithium was leached by the isomorphic substitution of Fe2+ in LFP using a relatively inexpensive ferric chloride etching solution as a leaching agent. In the study, the leaching rate of lithium was compared using the ferric chloride etching solution at various multiples of the LFP molar ratio: 0.7, 1.0, 1.3, and 1.6 times. The highest lithium leaching rate was shown at about 98% when using 1.3 times the LFP molar ratio. Subsequently, to eliminate Fe, the leachate was treated with NaOH. The Fe-free solution was then used to synthesize lithium carbonate, and the harvested powder was characterized and validated. The surface shape and crystal phase were analyzed using SEM and XRD analysis, and impurities and purity were confirmed using ICP analysis.
Temperature and weather are all around us, quite literally. Furthermore, temperature and weather not only permeate our atmosphere, constantly affecting our visceral states of warmth and coldness, but they metaphorically permeate our language. People, products, and ideas can all be "hot" or "cold." Given this ubiquity, it is perhaps surprising that relatively little research has systematically examined the influence of temperature on choice and judgment. Temperature-related words such as "hot" and "cold" are often used to describe impulsive and calculated behaviors, respectively. These metaphoric connotations of thermal concepts raise the question as to whether temperature, psychological states and decision making are related to each other, and if so, how. The current research examines these questions and finds support for a relationship. Across one field study and one laboratory experiment, I demonstrate that both hot ambient room temperature (Spa) and hot temperature primes (words) trigger decision outcomes in line with the metaphoric association between hot temperature and impulsivity. In the field study, participants were recruited in hot (40-50 degrees Celsius) and cold (10 degrees Celsius) rooms at a spa. Participants were simply asked to indicate their willingness-to-pay (WTP) for three product categories (travel package, birthday dinner, and cell phone). The results showed that participants in the hot room in comparison to those in the cold room were willing to pay more for the same products. Next, I tested if our results would go beyond ambient temperature and would hold if I were to prime temperature concepts by using a different priming method (i.e., subliminal vs. supraliminal). In line with the previous findings in the spa, participants in the hot priming condition were more likely to choose the wrong answer for the bat and baseball question than those in the cold priming condition. In addition, product type (e.g., pleasure vs. necessity) can moderate the effect of hot temperature on impulsivity. Mood and arousal did not mediate participants' responses. My findings seem to suggest that the effects of temperature on decision outcomes can be attributed to metaphoric associations rather than incidental mood or arousal. The current research applies a novel perspective in understanding the relationship between temperature and judgment and decision making. Also, the results have practical implications for packaging, advertising, merchandising, and pricing of goods and services, as well as for public policy and awareness. One of the most natural implications of my findings would be that retailers would be better off carrying more impulse purchase items on hot days. Furthermore, point-of-purchase promotions encouraging impulse purchase is more likely to be effective in retail environments with higher temperature than with lower temperature. In addition, advertisements and product packages evoking hot temperature associations (e.g., beach, sunshine, summer) might lead consumers to pay higher price for the advertised product than those with cold temperature associations.
Recently, the use of prepaid electronic payments such as electronic wallets, digital currency and prepaid points is gradually increasing. Prepaid electronic payments has the characteristic of being used after charging first. This study empirically investigated the factors affecting the intention to use online charging in order to help improve the service that require prepaid recharge by applying transformed TAM. Since there are not many previous studies for the intention to use online charging, we extract factors through preceding researches for electronic cash and mobile easy payment. Also we analyze the intention to use online charging for transportation card users, focusing on the moderating effects. As a result of the study, it was found that 'convenience', 'ubiquity', and 'self-efficacy' among the independent variables had a positive (+) effect on mediation variable 'perceived usefulness'. 'Perceived usefulness' was analyzed to have a significant influence on the dependent variable 'usage intention'. According to users' gender, internet usage time, internet shopping frequency, online charging frequency and transportation card usage type, the moderating effect was significant on 'perceived usefulness' and 'usage intention'. As an implication, it was suggested that service improvement and differentiated marketing are needed in direction of increasing the usefulness of services. Additional research directions were proposed for services such as e-wallets, prepaid points and digital currencies by adding other factors and moderate variables.
This paper proposes 'postfilimc metamorphosis' and 'reanimation' as two concepts that aim at giving account to the aesthtetic tendencies and genealogies of what Suzanne Buchan calls 'pervasive animation', a category that refers to the unprecedented expansion of animation's formal, technological and experiential boundaries. Buchan's term calls for an interdisciplinary approach to animation by highlighting a range of phenomena that signal the growing embracement of the images and media that transcend the traditional definition of animation, including the lens-based live-action image as the longstanding counterpart of the animation image, and the increasing uses of computer-generated imagery, and the ubiquity of various animated images dispersed across other media and platforms outside the movie theatre. While Buchan's view suggests the impacts of digital technology as a determining factor for opening this interdisciplinary, hybrid fields of 'pervasive animation', I elaborate upon the two concepts in order to argue that the various forms of metamorphorsis and motion found in these fields have their historical roots. That is, 'postfilmic metamorphosis' means that the transformative image in postfimic media such as video and the computer differs from that in traditional celluloid-based animation materially and technically, which demands a refashioned investigation into the history of the 'image-processing' video art which was categorized as experimental animation but largely marginalized. Likewise, 'reanimation' cne be defined as animating the still images (the photographic and the painterly images) or suspending the originally inscribed movement in the moving image and endowing it with a neewly created movement, and both technical procedues, developed in experimental filmmaking and now enabled by a variety of moving image installations in contemporary art, aim at reconsidering the borders between stillness and movement, and between film and photography. By discussing a group of contemporary moving image artworks (including those by Takeshi Murata, David Claerbout, and Ken Jacobs) that present the aesthetic features of 'postfilmic metamorphosis' and 'reanimation' in relation to their precursors, this paper argues that the aesthetic implications of the works that pertain to 'pervasive animation' lie in their challenging the tradition dichotomies of the graphic/the live-action images and stillness/movement. The two concepts, then, respond to a revisionist approach to reconfigure the history and ontology of other media images outside the traditional boundaries of animation as a way of offering a refasioned understanding of 'pervasive animation'.
The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.
Contamination of groundwater by agrochemicals used in the regional-scale Is now a major environmental problem, and this is especially true for Cheju island where virtually all potable water is from groundwater. The objective of this study was to assess leaching potential of eight pesticides in soils of citrus orchards using groundwater ubiquity score (GUS), retardation factor (RF) and attenuation factor (AF). Considering GUS estimated in 30 citrus orchard soils, metribuzin and metolachlor were classified as leacher, alachlor in volcanic ash soils and linuron in non-volcanic soils were classified as leacher, but chlorothalonil and chlorpyrifos were classified as non-leacher. For RF values, metribuzin was classified to be mobile in soils of low organic carbon, metolachlor and alachlor were classified to be moderately immobile in most soils, but linuron, diuron, diniconazole, chlorothalonil and chlorpyrifos were all classified to be very immobile. For AF values, diniconazole, chlorothalonil, and chlorpyrifos were classified to be very unlikely leachable in all of the soils, metribuzin was classified to be likely leachable, and metolahclor, alachlor, linuron and diuron were classified to be leachable only in non-volcanic soils. Although there were some variations in the relative potential of teachability of pesticides estimated with the three different indices, the ranking was essentially determined on the base of the intrinsic properties of the chemicals and environmental properties. Among the eight pesticides, metribuzin, metolachlor, and alachlor, which have high water solubility and low $K_{oc}$ values, have a significant leaching potential especially in non-volcanic ash soils of low organic carbon. But diniconazole, chlorothalonil, and chlorpyrifos, which have low water solubility and high $K_{oc}$ values, were classified to be very immobile in all of the soils. Therefore, to lower the possibility of pesticide contamination of the groundwater in Cheju island, those pesticides which have high water solubility and low $K_{oc}$ values should be used with care in soils of low organic carbon including non-volcanic ash soils.
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