1,202 research outputs found

    Estimating the Stochastic Sickness Effect on Employment, Worktime and Saving Decisions

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    This paper aims to study labor supply and saving decisions as a result of health uncertainty. O’Donnell (1995) suggested a theoretical positive relationship between working hours (or saving rate) and the perceived health uncertainty. That is, for risk-averse individuals, there exists a precaution motion to work harder and save more when facing the uncertainty for the health condition. We test this hypothetical relationship by applying the 2003-2005 data from the Panel Study of Family Dynamics (PSFD) in Taiwan. Following Hughes and Maguire’s approach (2003), our estimation result indicates that a stochastic sickness has positive effects on the decisions of working time and saving rate.Health, Uncertainty, Labor Supply, Saving

    UNDERSTANDING COLLABORATIVE STICKINESS INTENTION IN SOCIAL NETWORK SITES FROM THE PERSPECTIVE OF KNOWLEDGE SHARING

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    This study aims to investigate users’ knowledge sharing intention and collaborative stickiness intention towards social network sites (SNS). SNS offer an opportunity for users to interact and form relationships, while knowledge is accrued by integrating user’s information, experience, and practice. However, there have been few systematic studies that ask why people use SNS to share knowledge. We adopt social capital theory, social identity theory, as well as use and gratification theory to explore the determinants of members’ knowledge sharing intention in SNS. The survey was conducted on two education VCs of facebook, while most members were teachers and educators. Data analysis was carried out to validate our research model, and SmartPLS were used to analyze users’ collaborative stickiness intention. The result shows that social capital and social identity have impact on teacher’s knowledge sharing intention, in turn, influence on collaborative stickiness intention toward on SNS. Our findings not only help researchers interpret why members sharing their knowledge in VC, but also assist practitioners in developing better SNS strategy

    Phase Distribution and Phase Correlation of Financial Time Series

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    Scaling, phase distribution and phase correlation of financial time series are investigated based on the Dow Jones Industry Average (DJIA) and NASDAQ 10-minute intraday data for a period from Aug. 1 1997 to Dec. 31 2003. The returns of the two indices are shown to have nice scaling behaviors and belong to stable distributions according to the criterion of Levy's alpha stable distribution condition. A novel approach catching characteristic features of financial time series based on the concept of instantaneous phase is further proposed to study phase distribution and correlation. The analysis of phase distribution concludes return time series fall into a class which is different from other non-stationary time series. The correlation between returns of the two indices probed by the distribution of phase difference indicates there was a remarkable change of trading activities after the event of 911 attack, and this change persisted in later trading activities.Phase Distribution, High Frequency Data, Scaling Analysis, Levy Distribution, Stock Market, Frequency Variant

    Innovative Approaches: Leveraging Neuroscience Technologies for Understanding of Consumer Behavior in E-Commerce

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    The surge in interest surrounding the application of advanced technology in consumer behavior analysis within the e-commerce domain has grown significantly in recent years. Traditional market research methods, constrained by limitations in capturing accurate consumer responses, have paved the way for these sophisticated technologies to provide deeper insights into the intricacies of consumer behavior and decision-making processes. This comprehensive review navigates through various techniques utilized for scrutinizing consumer behavior, delving into the capabilities and limitations of each technology. EEG emerges as a powerful tool capable of measuring brain activity, shedding light on cognitive and emotional responses to marketing stimuli. The review further explores the potential applications of these technologies in the e-commerce landscape. Examples include assessing website design effectiveness using EEG. This review underscores the advantages of deploying advanced technologies in analyzing consumer behavior in e-commerce, showcasing their potential to enhance marketing strategies and user experiences. This article is particularly pertinent to applied science readers interested in the practical implementation of cutting-edge technologies in consumer behavior analysis

    Study of sponge gourd ascorbate peroxidase and winter squash superoxide dismutase under respective flooding and chilling stresses

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    AbstractThe objectives of this work were to study the responses of ascorbate peroxidase (APX), catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR), and physiological parameters of bitter melon (BM), sponge gourd (SG), and winter squash (WS) under waterlogged and low temperature conditions. The BM and SG plants were subjected to 0–72h flooding treatments. Moreover, BM and WS plants were exposed to chilling at 12/7°C (day/night) for 0–72h. The results show that different genotypes responded differently to environmental stress according to their various antioxidant enzymes and physiological parameters. The activity of APX in roots and leaves of SG plants significantly higher than that of BM plants during continuous flooding. Significant increases in SOD activity in leaves of WS plants were also observed throughout the entire chilling duration compared to BM plants. On the basis of our observations, we conclude that increased APX and SOD activities provide SG and WS plants with increased waterlogging and chilling stress tolerance, respectively. Both APX and SOD activities can be used for selecting BM lines with the best tolerances to water logging and chilling stresses

    UNDERSTANDING COLLABORATIVE STICKINESS INTENTION IN SOCIAL NETWORK SITES FROM THE PERSPECTIVE OF KNOWLEDGE SHARING

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    Abstract This study aims to investigate users' knowledge sharing intention and collaborative stickiness intention towards social network sites (SN

    Dynamic neural networks for real-time water level predictions of sewerage systems-covering gauged and ungauged sites

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    [[abstract]]In this research, we propose recurrent neural networks (RNNs) to build a relationship between rainfalls and water level patterns of an urban sewerage system based on historical torrential rain/storm events. The RNN allows signals to propagate in both forward and backward directions, which offers the network dynamic memories. Besides, the information at the current time-step with a feedback operation can yield a time-delay unit that provides internal input information at the next time-step to effectively deal with time-varying systems. The RNN is implemented at both gauged and ungauged sites for 5-, 10-, 15-, and 20-min-ahead water level predictions. The results show that the RNN is capable of learning the nonlinear sewerage system and producing satisfactory predictions at the gauged sites. Concerning the ungauged sites, there are no historical data of water level to support prediction. In order to overcome such problem, a set of synthetic data, generated from a storm water management model (SWMM) under cautious verification process of applicability based on the data from nearby gauging stations, are introduced as the learning target to the training procedure of the RNN and moreover evaluating the performance of the RNN at the ungauged sites. The results demonstrate that the potential role of the SWMM coupled with nearby rainfall and water level information can be of great use in enhancing the capability of the RNN at the ungauged sites. Hence we can conclude that the RNN is an effective and suitable model for successfully predicting the water levels at both gauged and ungauged sites in urban sewerage systems.[[incitationindex]]SCI[[booktype]]紙

    The Case ∣ A woman with bilateral flank pain

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    Outcomes of and factors associated with the development of bronchopulmonary dysplasia with pulmonary hypertension in very low birth weight infants: A retrospective study in a medical center

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    IntroductionBronchopulmonary dysplasia (BPD) with pulmonary hypertension (PH) leads to increased morbidity and mortality in extremely preterm infants. Recent studies have analyzed factors associated with development of PH in BPD; however, this research remains inconclusive, and controversy exists regarding the correlation between BPD and PH. This study aimed to investigate potential associated factors, clinical characteristics, and outcomes of BPD with pulmonary hypertension in very low birth weight (VLBW) preterm infants.MethodsWe conducted a retrospective study, reviewing the records of infants with gestational age (GA) <32 weeks and birth weight <1,500 g admitted to a tertiary neonatal intensive care unit between January 2020 and October 2021 who were diagnosed with moderate to severe BPD. Echocardiogram was performed at the postmenstrual age of 36 weeks or before discharge. The diagnosis of PH was based on the findings of echocardiogram. Prenatal and postnatal characteristics, demographic data, treatment details, and outcomes were collected and analyzed.ResultsA total of 139 VLBW infants with BPD were enrolled and divided into a PH group (n = 25) and a non-PH group (n = 114). The mean GA was 27.3 ± 2.3 weeks and the mean birth weight of infants with BPD was 927.3 ± 293.3 g. A multivariate logistic regression model revealed that a high positive end-expiratory pressure (PEEP) setting (OR: 2.105; 95% CI: 1.472–3.011; p < 0.001) in established BPD and surgical closure of patent ductus arteriosus (PDA; OR: 6.273; 95% CI: 1.574–24.977; p = 0.009) were associated with BPD–PH. Neonates with BPD who developed pulmonary hypertension remained hospitalized for longer (p < 0.001), received invasive mechanical ventilation support for longer (p < 0.001), had a higher incidence of retinopathy of prematurity (ROP; OR: 4.201; 95% CI: 1.561–11.304; p = 0.003), were more likely to require oxygen support at discharge (OR: 5.600; 95% CI: 2.175–14.416; p < 0.001), and were more likely to undergo tracheostomy (OR: 35.368; 95% CI: 4.03–310.43; p < 0.001).ConclusionPDA ligation and a higher PEEP setting were associated with BPD–PH in our cohort study. Compared with VLBW infants with BPD but without PH, infants with BPD and PH were hospitalized for longer, and also had a higher incidence of oxygen support after discharge, ROP, and tracheostomy

    Improving Performance of CIGS Solar Cells by Annealing ITO Thin Films Electrodes

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    Indium tin oxide (ITO) thin films were grown on glass substrates by direct current (DC) reactive magnetron sputtering at room temperature. Annealing at the optimal temperature can considerably improve the composition, structure, optical properties, and electrical properties of the ITO film. An ITO sample with a favorable crystalline structure was obtained by annealing in fixed oxygen/argon ratio of 0.03 at 400°C for 30 min. The carrier concentration, mobility, resistivity, band gap, transmission in the visible-light region, and transmission in the near-IR regions of the ITO sample were -1.6E+20 cm−3, 2.7E+01 cm2/Vs, 1.4E-03 Ohm-cm, 3.2 eV, 89.1%, and 94.7%, respectively. Thus, annealing improved the average transmissions (400–1200 nm) of the ITO film by 16.36%. Moreover, annealing a copper-indium-gallium-diselenide (CIGS) solar cell at 400°C for 30 min in air improved its efficiency by 18.75%. The characteristics of annealing ITO films importantly affect the structural, morphological, electrical, and optical properties of ITO films that are used in solar cells
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