Search results for: Li-Yun Wang

Authors: Chia-li Wang

Abstract:

The surge of service and commerce platforms, such as e-commerce and internet-of-things, have rapidly changed our lives. How to avoid the congestion and get the job done in the platform is now a common problem that many people encounter every day. This requires platform users to make decisions about when to enter the platform. To that end, we investigate the strategic entering time of a simple platform containing random numbers of buyers and sellers of some item. Upon a trade, the buyer and the seller gain respective profits, yet they pay the cost of waiting in the platform. To maximize their expected payoffs from trading, both buyers and sellers can choose their entering times. This creates an interesting and practical framework of a game that is played among buyers, among sellers, and between them. That is, a strategy employed by a player is not only against players of its type but also a response to those of the other type, and, thus, a strategy profile is composed of strategies of buyers and sellers. The players' best response, the Nash equilibrium (NE) strategy profile, is derived by a pair of differential equations, which, in turn, are used to establish its existence and uniqueness. More importantly, its structure sheds valuable insights of how the entering strategy of one side (buyers or sellers) is affected by the entering behavior of the other side. These results provide a base for the study of dynamic pricing for stochastic demand-supply imbalances. Finally, comparisons between the social welfares (the sum of the payoffs incurred by individual participants) obtained by the optimal strategy and by the NE strategy are conducted for showing the efficiency loss relative to the socially optimal solution. That should help to manage the platform better.

Keywords: double-sided queue, non-cooperative game, nash equilibrium, price of anarchy

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Authors: Levent Taylan Ozgur Yildirim, Qihao Qian, John Yilin Wang

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A critical review of assessments of geological carbon dioxide (CO2) storage resources in Pennsylvania and the surrounding region was completed with a focus on the studies of Midwest Regional Carbon Sequestration Partnership (MRCSP), United States Department of Energy (US-DOE), and United States Geological Survey (USGS). Pennsylvania Geological Survey participated in the MRCSP Phase I research to characterize potential storage formations in Pennsylvania. The MRCSP’s volumetric method estimated ~89 gigatonnes (Gt) of total CO2 storage resources in deep saline formations, depleted oil and gas reservoirs, coals, and shales in Pennsylvania. Meanwhile, the US-DOE calculated storage efficiency factors using log-odds normal distribution and Monte Carlo sampling, revealing contingent storage resources of ~18 Gt to ~20 Gt in deep saline formations, depleted oil and gas reservoirs, and coals in Pennsylvania. Additionally, the USGS employed Beta-PERT distribution and Monte Carlo sampling to determine buoyant and residual storage efficiency factors, resulting in 20 Gt of contingent storage resources across four storage assessment units in Appalachian Basin. However, few studies have explored CO2 storage resources in shales in the region, yielding inconclusive findings. This article provides a critical and most up to date review and analysis of geological CO2 storage resources in Pennsylvania and the region.

Keywords: carbon capture and storage, geological CO2 storage, pennsylvania, appalachian basin

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Authors: Chechen Liao, Pui-Lai To, Yi-Hui Wang

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Recently location-based augmented reality games (LBS+AR) have become increasingly popular as a major form of entertainment. Location-based augmented reality games have provided a lot of opportunities for face-to-face interaction among players. Prior studies also indicate that the social side of location-based augmented reality games are one of the major reasons for players to engage in the games. However, the impact of the usage of location-based augmented reality games has not been well explored. The study examines how interpersonal interaction affects social capital and health through playing location-based augmented reality games. The study also investigates how social capital mediates the relationships between interpersonal interaction and health. The study uses survey method to collect data. Six-hundred forty-seven questionnaires are collected. Structural equation modeling is used to investigate the relationships among variables. The causal relationships between variables in the research model are tested. The results of the study indicated that four interpersonal attraction attributes, including ability, proximity, similarity, and familiarity, are identified by ways of factor analysis. Interpersonal attraction is important for location-based augmented reality game-players to develop bonding and bridging social capital. Bonding and bridging social capital have a positive impact on the mental and social health of game-players. The results of the study provide academic and practical implications for future growth of location-based augmented reality games.

Keywords: health, interpersonal interaction, location-based augmented reality games, social capital

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Authors: Peijen Pamela Chuang, Tzu-Hua Wang

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To address the notion of educational equity, undergo the global pandemic, a digital learning system was cross-disciplinarily designed by a 15-year-experienced teaching practitioner. A study was performed on students through the use of this pioneering e-learning system, in which Taiwanese students with different learning styles and special needs have a foreign language- English as the target subject. 121 students are particularly selected from an N= 580 sample spread across 20 inclusive and special education schools throughout districts of Taiwan. To bring off equity, the participants are selected from a mix of different socioeconomic statuses. Grouped data, such as classroom observation, individual learning preference, prerequisite knowledge, learning interest, and learning performance of the population, is carefully documented for further analyzation. The paper focuses on documenting the awareness and needs of this pedagogical methodology revolution, data analysis of UX (User Experience), also examination and system assessment of this system. At the time of the pilot run, this newly-developed e-learning system had successfully applied for and received a national patent in Taiwan. This independent research hoped to expand the awareness of the importance of individual differences in SDG4 (Substantial Development Goals 4) as a part of the ripple effect, and serve as a comparison for future scholars in the pedagogical research with an interdisciplinary approach.

Keywords: e-learning, educational equity, foreign language acquisition, inclusive education, individual differences, interdisciplinary innovation, learning preferences, SDG4

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Authors: Szu-Hua Wang

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Urban areas contain abundant potential biochemical storages and renewable and non-renewable flows. Urban natural environments for breeding natural assets and urban economic development for maintaining urban functions can be analyzed form the concept of ecological economic system. Land use change and ecosystem services change are resulting from the interactions between human activities and environments factually. Land use change due to human activities is the major cause of climate change, leading to serious impacts on urban ecosystem services, including provisioning services, regulating services, cultural services and supporting services. However, it lacks discussion on the interactions among urban land use change, ecosystem services change, and extreme precipitation events. Energy synthesis can use the same measure standard unit, solar energy, for different energy resources (e.g. sunlight, water, fossil fuels, minerals, etc.) and analyze contributions of various natural environmental resources on human economic systems. Therefore, this research adopts the concept of ecological, economic systems and energy synthesis for analyzing dynamic spatial impacts of land use change on ecosystem services, using the Taipei area as a case study. The analysis results show that changes in land use in the Taipei area, especially the conversion of natural lands and agricultural lands to urban lands, affect the ecosystem services negatively. These negative effects become more significant during the extreme precipitation events.

Keywords: urban ecological economic system, extreme precipitation events, ecosystem services, energy

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Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

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Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Pei-Chih Wu, Hsien-Chang Wang

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Taiwan, a climatically challenged island, has always been keen on the issue of water resource management due to its limitations in water storage. Since water resource management has been the focal point of many adaptations to climate change, there has been a lack of attention on another issue, water quality. This study chooses the Errer River Basin as the experimental focus for water quality in Taiwan. With the Errer River Basin being one of the most polluted rivers in Taiwan, this study observes the effects of climate change on this river over a period of time. Taiwan is also targeted by multiple typhoons every year, the heavy rainfall and strong winds create problems of pollution being carried to different river segments, including into the ocean. This study aims to create an impact and risk assessment on Errer River Basin, to show the connection from climate change to potential extreme events, which in turn could influence water quality and ultimately human health. Using dynamic downscaling, this study narrows the information from a global scale to a resolution of 1 km x 1 km. Then, through interpolation, the resolution is further narrowed into a resolution of 200m x 200m, to analyze the past, present, and future of extreme events. According to different climate change scenarios, this study designs an assessment index on the vulnerability of the Errer River Basin. Through this index, Errer River inhabitants can access advice on adaptations to climate change and act accordingly.

Keywords: climate change, adaptation, water quality, risk assessment

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Authors: Qiming Wang

Abstract:

Dynamic polymer networks (DPNs) crosslinked by dynamic bonds have received intensive attention because of their special crack-healing capability. Diverse DPNs have been synthesized using a number of dynamic bonds, including dynamic covalent bond, hydrogen bond, ionic bond, metal-ligand coordination, hydrophobic interaction, and others. Despite the promising success in the polymer synthesis, the fundamental understanding of their self-healing mechanics is still at the very beginning. Especially, a general analytical model to understand the interfacial self-healing behaviors of DPNs has not been established. Here, we develop polymer-network based analytical theories that can mechanistically model the constitutive behaviors and interfacial self-healing behaviors of DPNs. We consider that the DPN is composed of interpenetrating networks crosslinked by dynamic bonds. bonds obey a force-dependent chemical kinetics. During the self-healing process, we consider the The network chains follow inhomogeneous chain-length distributions and the dynamic polymer chains diffuse across the interface to reform the dynamic bonds, being modeled by a diffusion-reaction theory. The theories can predict the stress-stretch behaviors of original and self-healed DPNs, as well as the healing strength in a function of healing time. We show that the theoretically predicted healing behaviors can consistently match the documented experimental results of DPNs with various dynamic bonds, including dynamic covalent bonds (diarylbibenzofuranone and olefin metathesis), hydrogen bonds, and ionic bonds. We expect our model to be a powerful tool for the self-healing community to invent, design, understand, and optimize self-healing DPNs with various dynamic bonds.

Keywords: self-healing polymers, dynamic covalent bonds, hydrogen bonds, ionic bonds

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Authors: Chaomeng Liu, Li Li, Xiao Wang, Li Ren, Qinge Zhang

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Late-life depression (LLD) is a prevalent mental disorder among the elderly, frequently accompanied by significant cognitive decline, and has emerged as a worldwide public health concern. Microglia, astrocytes, and peripheral immune cells play pivotal roles in regulating inflammatory responses within the central nervous system (CNS) across diverse cerebral disorders. This review commences with the clinical research findings and accentuates the recent advancements pertaining to microglia and astrocytes in the neuroinflammation process of LLD. The reciprocal communication network between the CNS and immune system is of paramount importance in the pathogenesis of depression and cognitive decline. Stress-induced downregulation of tight and gap junction proteins in the brain results in increased blood-brain barrier permeability and impaired astrocyte function. Concurrently, activated microglia release inflammatory mediators, initiating the kynurenine metabolic pathway and exacerbating the quinolinic acid/kynurenic acid imbalance. Moreover, the balance between Th17 and Treg cells is implicated in the preservation of immune homeostasis within the cerebral milieu of individuals suffering from LLD. The ultimate objective of this review is to present future strategies for the management and treatment of LLD, informed by the most recent advancements in research, with the aim of averting or postponing the onset of AD.

Keywords: neuroinflammation, late-life depression, microglia, astrocytes, central nervous system, blood-brain barrier, Kynurenine pathway

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Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

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Authors: Zelalem Abebe Bekele, Kun Lei, Xiukai Lan, Xiangyu Liu, Hui Wen, Kaiyou Wang

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Spin-polarized currents offer an efficient means of manipulating the magnetization of a ferromagnetic layer for big data and neuromorphic computing. Research has shown that the orbital Hall effect (OHE) can produce orbital currents, potentially surpassing the counter spin currents induced by the spin Hall effect. However, it’s essential to note that orbital currents alone cannot exert torque directly on a ferromagnetic layer, necessitating a conversion process from orbital to spin currents. Here, we present an efficient method for achieving perpendicularly magnetized spin-orbit torque (SOT) switching by harnessing the localized orbital Hall current generated from a Mo layer within a Mo/CoGd device. Our investigation reveals a remarkable enhancement in the interface-induced planar Hall effect (PHE) within the Mo/CoGd bilayer, resulting in the generation of a z-polarized planar current for manipulating the magnetization of CoGd layer without the need for an in-plane magnetic field. Furthermore, the Mo layer induces out-of-plane orbital current, boosting the in-plane and out-of-plane spin polarization by converting the orbital current into spin current within the dual-property CoGd layer. At the optimal Mo layer thickness, a low critical magnetization switching current density of 2.51×10⁶ A cm⁻² is achieved. This breakthrough opens avenues for all-electrical control energy-efficient magnetization switching through orbital current, advancing the field of spin-orbitronics.

Keywords: spin-orbit torque, orbital hall effect, spin hall current, orbital hall current, interface-generated planar hall current, anisotropic magnetoresistance

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Authors: Chen Zhang; Qiang Wang

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With the rapid development of the new generation of digital technology, various industries have created more and more value by using digital technology, accelerating the digital transformation of various industries. The economic form of human society has evolved with the progress of technology, and in this context, the power conversion, transformation and upgrading of the manufacturing industry in terms of quality, efficiency and energy change has become a top priority. Based on the digitalization background, this paper analyzes the transformation and upgrading efficiency of the manufacturing industry and evaluates the impact of the driving factors, which have very important theoretical and practical significance. This paper utilizes qualitative research methods, entropy methods, data envelopment analysis methods and econometric models to explore the transformation and upgrading efficiency of manufacturing enterprises and driving factors. The study shows that the transformation and upgrading efficiency of the manufacturing industry shows a steady increase, and regions rich in natural resources and social resources provide certain resources for transformation and upgrading. The ability of scientific and technological innovation has been improved, but there is still much room for progress in the transformation of scientific and technological innovation achievements. Most manufacturing industries pay more attention to green manufacturing and sustainable development. In addition, based on the existing problems, this paper puts forward suggestions for improving infrastructure construction, developing the technological innovation capacity of enterprises, green production and sustainable development.

Keywords: digitization, manufacturing firms, transformation and upgrading, efficiency, driving factors

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Wei Wang

Abstract:

Queli Hotel, Xixi Scenery Spot Reception and Square Pagoda Garden are three important landmarks of localized Chinese modern architecture (LCMA) in the architectural design context of "Inheriting the Traditions in Modern Architecture" in the 1980s. As the most representative cases of LCMA in the 1980s, they interpret the traditions of Chinese garden and imperial roof from different perspectives. Based on the research text, conceptual drawings, construction drawings and site investigation, this paper extracts two groups of prominent contradictions in practice ("Pattern-Material-Structure" and "Type-Topography-Body") for keyword-based analysis to compare and examine different choices and balances by architects. Based on this, this paper attempts to indicate that the ideographic form derived from macro-narrative and the innovative investigation in construction is a pair of inevitable contradictions that must be handled and coordinated in these practices. The collision of the contradictions under specific conditions results in three cognitive attitudes and practical strategies towards traditions: Formal symbolism, spatial abstraction and construction-based narrative. These differentiated thoughts about Localization and Chineseness reflect various professional ideologies and value standpoints in the transition of Chinese Architecture discipline in the 1980s. The great variety in this particular circumstance suggests tremendous potential and possibilities of the future LCMA.

Keywords: construction, meaning, Queli Hotel, square pagoda garden, tradition, Xixi scenery spot reception

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Authors: Wen-Juinn Chen, Yi-Phei Chou, Jou-Han Wang

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Tainan coast is suffering from beach erosion, wave overtopping, and lowland flooding; though most of the shoreline has been protected by seawalls, they still threatened by sea level rise. For coastal resources developing, coastal land utilization, and to draft an appropriate mitigate strategy. Firstly; we must assess the impact of beach erosion under a different scenario of climate change. Here, we have used the meteorological data since 1898 to 2012 to prove that the Tainan area did suffer the impact of climate change. The result shows the temperature has been raised to about 1.7 degrees since 1989. Also, we analyzed the tidal data near the Tainan coast (Anpin site and Junjunn site), it shows sea level rising with a rate about 4.1~4.8 mm/year, this phenomenon will have serious impacts on Tainan coastal area, especially it will worsen coastal erosion. So we have used Bruun rule to calculate the shoreline retreated rate at every two decade period since 2012. Wave data and bottom sand diameter D50 were used to calculate the closure depth that will be used in Bruun formula and the active length of the profile is computed by the beach slope and Dean's equilibrium concept. After analysis, we found that in 2020, the shoreline will be retreated about 3.0 to 12 meters. The maximum retreat is happening at Chigu coast. In 2060, average shoreline retreated distance is 22m, but at Chigu and Tsenwen, shoreline may be backward retreat about 70m and will be reached about 130m at 2100, this will cause a lot of coastal land loss to the sea, protect and mitigate project must be quickly performed.

Keywords: sea level rise, shoreline, coastal erosion, climate change

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Authors: Kawsar Ahmed, Hong Wang

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The study's goal was to estimate the causal mediation impact of tobacco tax before and after price hikes among low-income male smokers, with a particular emphasis on the effect estimating pathways framework for continuous and dichotomous variables. From July to December 2021, a cross-sectional investigation of observational data (n=739) was collected from Bangladeshi low-wage smokers. The Quasi-Bayesian technique, binomial probit model, and sensitivity analysis using a simulation of the computational tools R mediation package had been used to estimate the effect. After a price rise for tobacco products, the average number of cigarettes or bidis sticks taken decreased from 6.7 to 4.56. Tobacco product rising prices have a direct effect on low-income people's decisions to quit or lessen their daily smoking habits of Average Causal Mediation Effect (ACME) [effect=2.31, 95 % confidence interval (C.I.) = (4.71-0.00), p<0.01], Average Direct Effect (ADE) [effect=8.6, 95 percent (C.I.) = (6.8-0.11), p<0.001], and overall significant effects (p<0.001). Tobacco smoking choice is described by the mediated proportion of income effect, which is 26.1% less of following price rise. The curve of ACME and ADE is based on observational figures of the coefficients of determination that asses the model of hypothesis as the substantial consequence after price rises in the sensitivity analysis. To reduce smoking product behaviors, price increases through taxation have a positive causal mediation with income that affects the decision to limit tobacco use and promote low-income men's healthcare policy.

Keywords: causal mediation analysis, directed acyclic graphs, tobacco price policy, sensitivity analysis, pathway estimation

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Authors: David Chao, John Lai, Alvin Wu, Carl Wang

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For lithium-ion batteries with multiple cell configurations, some use scenarios can cause uneven aging effects to each cell within the battery because of uneven current distribution. Hence the focus of the study is to explore the aging effect(s) on batteries with different construction designs. In order to systematically study the influence of various factors in some key battery configurations, a detailed analysis of three key battery construction factors is conducted. And those key factors are (1) terminal position; (2) cell alignment matrix; and (3) interconnect resistance between cells. In this study, the 2S2P circuitry has been set as a model multi-cell battery to set up different battery samples, and the aging behavior is studied by a cycling test to analyze the current distribution and recoverable capacity. According to the outcome of aging tests, some key findings are: (I) different cells alignment matrices can have an impact on the cycle life of the battery; (II) symmetrical structure has been identified as a critical factor that can influence the battery cycle life, and unbalanced resistance can lead to inconsistent cell aging status; (III) the terminal position has been found to contribute to the uneven current distribution, that can cause an accelerated battery aging effect; and (IV) the internal connection resistance increase can actually result in cycle life increase; however, it is noteworthy that such increase in cycle life is accompanied by a decline in battery performance. In summary, the key findings from the study can help to identify the key aging factor of multi-cell batteries, and it can be useful to effectively improve the accuracy of battery capacity predictions.

Keywords: multiple cells battery, current distribution, battery aging, cell connection

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Authors: Xing Wang, Lin Feng, Xuan Zou, Hongchen liu

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Immediate Implantation after tooth extraction is considered to be the ideal way to retain the alveolar bone, but some scholars believe the aesthetic effect in the Early Implantation case are more reliable. In this study, 89 patients were added to this retrospective study up to 5 years. Assessment indicators was including the survival of the implant (peri-implant infection, implant loosening, shedding, crowns and occlusal), aesthetics (color and fullness gums, papilla height, probing depth, X-ray alveolar crest height, the patient's own aesthetic satisfaction, doctors aesthetics score), repair defects around the implant (peri-implant bone changes in height and thickness, whether the use of autologous bone graft, whether to use absorption/repair manual nonabsorbable material), treatment time, cost and the use of antibiotics.The results demonstrated that there is no significant difference in long-term success rate of immediate implantation, early implantation and delayed implantation (p> 0.05). But the results indicated immediate implantation group could get get better aesthetic results after two years (p< 0.05), but may increase the risk of complications and failures (p< 0.05). High-risk indicators include gingival recession, labial bone wall damage, thin gingival biotypes, planting position and occlusal restoration bad and so on. No matter which type of implanting methods was selected, the extraction methods and bone defect amplification techniques are observed as a significant factors on aesthetic effect (p< 0.05).

Keywords: immediate implantation, long-term effects, aesthetics area, dental implants

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Yuanyuan Wang, Chun Hui

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Drawing on social capital theory, this article discusses how individuals may utilize network ties to come up with creativity. Social capital theory elaborates how network ties enhances individual creativity from three dimensions: structural access, and relational and cognitive mechanisms. We categorize network ties into strong and weak in terms of tie strength. With less structural constraints, weak ties allow diverse and heterogeneous knowledge to prosper, further facilitating individuals to build up connections among diverse even distant ideas. On the other hand, strong ties with the relational mechanism of cooperation and trust may benefit the accumulation of psychological capital, ultimately to motivate and sustain creativity. We suggest that differential ties play different roles for individual creativity: Weak ties deliver informational benefit directly rifling individual creativity from informational resource aspect; strong ties offer solidarity benefits to reinforce psychological capital, which further inspires individual creativity engagement from a psychological viewpoint. Social capital embedded in network ties influence individuals’ informational acquisition, motivation, as well as cognitive ability to be creative. Besides, we also consider the moderating effects constraining the relatedness between network ties and creativity, such as knowledge articulability. We hypothesize that when the extent of knowledge articulability is low, that is, with low knowledge codifiability, and high dependency and ambiguity, weak ties previous serving as knowledge reservoir will not become ineffective on individual creativity. Two-wave survey will be employed in Mainland China to empirically test mentioned propositions.

Keywords: network ties, social capital, psychological capital, knowledge articulability, individual creativity

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Authors: Wei Wang, Martin Chen

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The reconstitution behaviours of nutritional products could impact user experience. Reconstitution issues such as lump formation and white flecks sticking to bottles surfaces could be very unappealing for the consumers in milk preparation. The controlling steps in dissolving instant milk powders include wetting, swelling, sinking, dispersing, and dissolution as in the literature. Each stage happens simultaneously with the others during milk preparation, and it is challenging to isolate and measure each step individually. This study characterized three adult nutritional products for different properties including particle size, density, dispersibility, stickiness, and capillary wetting to understand the relationship between powder physical properties and their reconstitution behaviours. From the results, the formation of clumps can be caused by different factors limiting the critical steps of powder reconstitution. It can be caused by small particle size distribution, light particle density limiting powder wetting, or the rapid swelling and dissolving of particle surface materials to impede water penetration in the capillary channels formed by powder agglomerates. For the grain or white flecks formation in milk preparation, it was believed to be controlled by dissolution speed of the particles after dispersion into water. By understanding those relationship between fundamental powder structure and their user experience in reconstitution, this information provides us new and multiple perspectives on how to improve the powder characteristics in the commercial manufacturing.

Keywords: characterization, dairy nutritional powder, physical property, reconstitution

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Authors: Ming-Jong Yao, Chin-Sum Shui, Chih-Han Wang

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This paper is developed based on a real-world decision scenario that an industrial gas company that applies the Vendor Managed Inventory model and supplies liquid oxygen with a self-operated heterogeneous vehicle fleet to hospitals in nearby cities. We name it as a Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule and formulate it as a non-linear mixed-integer linear programming problem which simultaneously determines the length of the planning cycle (PC), the length of the replenishment cycle and the dates of replenishment for each customer and the vehicle routes of each day within PC, such that the average daily operation cost within PC, including inventory holding cost, setup cost, transportation cost, and overtime labor cost, is minimized. A solution method based on genetic algorithm, embedded with an encoding and decoding mechanism and local search operators, is then proposed, and the hash function is adopted to avoid repetitive fitness evaluation for identical solutions. Numerical experiments demonstrate that the proposed solution method can effectively solve the problem under different lengths of PC and number of customers. The method is also shown to be effective in determining whether the company should expand the storage capacity of a customer whose demand increases. Sensitivity analysis of the vehicle fleet composition shows that deploying a mixed fleet can reduce the daily operating cost.

Keywords: cyclic inventory routing problem, joint replenishment, heterogeneous vehicle, genetic algorithm

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Authors: Zhang Lei, Zhao Qingrong, Wang Chen, Zhang Sufang, Zhang Hanguo

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Larch is the main afforestation and timber tree species in Northeast China, and drought is one of the main factors limiting the growth of Larch and other organisms in Northeast China. In order to further explore the mechanism of Larch drought resistance, PEG was used to simulate drought stress. The full-length sequencing of Larch embryogenic callus under PEG simulated drought stress was carried out by combining Illumina-Hiseq and SMRT-seq. A total of 20.3Gb clean reads and 786492 CCS reads were obtained from the second and third generation sequencing. The de-redundant transcript sequences were predicted by lncRNA, 2083 lncRNAs were obtained, and the target genes were predicted, and a total of 2712 target genes were obtained. The de-redundant transcripts were further screened, and 1654 differentially expressed genes (DEGs )were obtained. Among them, different DEGs respond to drought stress in different ways, such as oxidation-reduction process, starch and sucrose metabolism, plant hormone pathway, carbon metabolism, lignin catabolic/biosynthetic process and so on. This study provides basic full-length sequencing data for the study of Larch drought resistance, and excavates a large number of DEGs in response to drought stress, which helps us to further understand the function of Larch drought resistance genes and provides a reference for in-depth analysis of the molecular mechanism of Larch drought resistance.

Keywords: larch, drought stress, full-length transcriptome sequencing, differentially expressed genes

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Authors: Pei Wang

Abstract:

The concept of social-emotional learning (SEL) is becoming increasingly popular in both research and practical applications worldwide. However, there is a lack of empirical studies and implementation of SEL in China, particularly from the perspective of parents. This qualitative study examined how Chinese parents perceived SEL, how their views on SEL were shaped, and how these views affected their decisions regarding their children’s education programs. Using the Collaborative for Academic Social and Emotional Learning Interactive Wheel framework and Bronfenbrenner's bioecological theory, the study conducted interviews with eight parents whose children attended public, international, and private schools in China. All collected data were conducted a thematic analysis involving three coding phases. The findings revealed that interviewees perceived SEL as significant to children’s development but held diverse understandings and perspectives on SEL at school depending on the amount and the quality of SEL resources available in their children’s schools. Additionally, parents’ attitudes towards the exam-oriented education system and Chinese culture influenced their views on SEL in school. Nevertheless, their socioeconomic status (SES) was the most significant factor in their perspectives on SEL, which significantly impacted their choices in their children's educational programs. High-SES families had more options to pursue SEL resources by sending their children to international schools or Western countries, while lower middle-class SES families had limited SEL resources in public schools. This highlighted educational inequality in China and emphasized the need for greater attention and investment in SEL programs in Chinese public schools.

Keywords: Chinese, inequality, parent, school, social-emotional learning

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

Abstract:

A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

Procedia PDF Downloads 196

Authors: Yakui Bai, Chen Sun, Ke Wang

Abstract:

An experimental investigation of environmental effect on fatigue behavior in SA508 Gr.3 Cl.2 Steam Generator Forging CAP1400 nuclear power plant has been carried out. In order to simulate actual loading condition, a range of strain amplitude was applied in different low cycle fatigue (LCF) tests. The current American Society of Mechanical Engineers (ASME) design fatigue code does not take full account of the interactions of environmental, loading, and material's factors. A range of strain amplitude was applied in different low cycle fatigue (LCF) tests at a strain rate of 0.01%s⁻¹. A design fatigue model was constructed by taking environmentally assisted fatigue effects into account, and the corresponding design curves were given for the convenience of engineering applications. The corrosion fatigue experiment was performed in a strain control mode in 320℃ borated and lithiated water environment to evaluate the effects of a mixed environment on fatigue life. Stress corrosion cracking (SCC) in steam generator large forging in primary water of pressurized water reactor was also observed. In addition, it is found that the CF life of SA508 Gr.3 Cl.2 decreases with increasing temperature in the water environment. The relationship between the reciprocal of temperature and the logarithm of fatigue life was found to be linear. Through experiments and subsequent analysis, the mechanisms of reduced low cycle fatigue life have been investigated for steam generator forging.

Keywords: failure behavior, low alloy steel, steam generator forging, stress corrosion cracking

Procedia PDF Downloads 123

Authors: Chien-Song Chyang, Wei-Chih Wang

Abstract:

For the incineration process, the inhibition of dioxin formation is an important issue. Many investigations indicate that adding sulfur compounds in the combustion process can be an effectively inhibition for the dioxin formation. In the process, the ratio of sulfur-to-chlorine plays an important role for the reduction efficiency of dioxin formation. Ca-base sorbent is also a common used for the acid gas removing. Moreover, that is also the indirectly way for dioxin inhibition. Although sulfur and calcium can reduce the dioxin formation, it still have some confusion exists between these additives. To understand and clarify the relationship between the dioxin and simultaneous addition of sulfur and calcium are presented in this study. The experimental data conducted in a pilot scale fluidized bed combustion system at various operating conditions are analysis comprehensively. The focus is on the dioxin of fly ash in this study. The experimental data in this study showed that the PCDD/Fs concentration in the fly ash collected from the baghouse is increased slightly as the simultaneous addition of sulfur and calcium. This work described the CO concentration with the addition of sulfur and calcium at the freeboard temperature from 800°C to 900°C, which is raised by the fuel complexity. The positive correlation exists between the dioxin concentration and CO concentration and carbon contained in the fly ash.. At the same sulfur/chlorine ratio, the toxic equivalent quantity (TEQ) can be reduced by increasing the actual concentration of sulfur and calcium. The homologue profiles showed that the P₅CDD and P₅CDF were the two major sources for the toxicity of dioxin. 2,3,7,8-TCDD and 2,3,7,8-TCDF reduced by the addition of pyrite and hydrated lime. The experimental results showed that the trend of PCDD/Fs concentration in the fly ash was different by the different sulfur/chlorine ratio with the addition of sulfur at 800°C.

Keywords: reduction of dioxin emissions, sulfur-to-chlorine ratio, de-chlorination, Ca-based sorbent

Procedia PDF Downloads 145

Authors: Jin Hun Choi, So Hyun Ahn, Seong Keun Wang, Ik-Seung Chee, Jung Lan Kim, Sun Woo Lee

Abstract:

Objectives: The purpose of the study is to investigate the effects of day hospital care in hospitalized schizophrenic patients in terms of treatment adherence and treatment outcomes. Methods: Among schizophrenic patients hospitalized between 2011 and 2012, 23 day hospital care patient and 40 control subjects were included in the study. All candidates underwent Beck Cognitive Insight Scale, Drug Attitude Inventory, World Health Organization Quality of Life Assessment and Psychological Well-Being Scale when their symptoms were stabilized during hospitalization, and after being discharged, 23 patients received day hospital care for two months and then changed to out-patient care while 40 patients received out-patient care immediately after discharge. At the point of two months of out-patient care, the treatment adherence of the two groups was evaluated; tracking observation was performed until February, 2013, and survival rates were compared between the two groups. Results: Treatment adherence was higher in the day hospital care group than in the control group. Kaplan-Meier survival analysis showed a higher survival rate for the day hospital care group compared to the control group. Levels of cognitive insight and quality of life were higher after day hospital care than before day hospital care in the day hospital care group. Conclusions: Through the study, it was confirmed that when hospitalized schizophrenic patients received continuous day hospital care after being discharged, they received further out-patient care more faithfully. The study is considered to aid in the understanding regarding schizophrenic patients’ treatment adherence issues and improvement of treatment outcomes.

Keywords: schizophrenia, day hospital care, adherence, outcomes

Procedia PDF Downloads 352

Authors: Jingjing Huang, Nengwei Li, Guanghua Wei, Jiabin You, Chao Wang, Junliang Zhang

Abstract:

In this work, molecular dynamics (MD) simulation is applied to analyze the mass transport process in the cathode of proton exchange membrane fuel cell (PEMFC), of which all types of molecules situated in the cathode is considered. a reasonable and effective MD simulation process is provided, and models were built and compared using both Materials Studio and LAMMPS. The mass transport is one of the key issues in the study of proton exchange membrane fuel cells (PEMFCs). In this report, molecular dynamics (MD) simulation is applied to analyze the influence of Nafion ionomer distribution and Pt nano-particle size on mass transport process in the cathode. It is indicated by the diffusion coefficients calculation that a larger quantity of Nafion, as well as a higher equivalent weight (EW) value, will hinder the transport of oxygen. In addition, medium-sized Pt nano-particles (1.5~2nm) are more advantageous in terms of proton transport compared with other particle sizes (0.94~2.55nm) when the center-to-center distance between two Pt nano-particles is around 5 nm. Then mass transport channels are found to be formed between the hydrophobic backbone and the hydrophilic side chains of Nafion ionomer according to the radial distribution function (RDF) curves. And the morphology of these channels affected by the Pt size is believed to influence the transport of hydronium ions and, consequently the performance of PEMFC.

Keywords: cathode catalytic layer, mass transport, molecular dynamics, proton exchange membrane fuel cell

Procedia PDF Downloads 239