Search results for: Yong Wang

Authors: Siti Rafeah Md Rafei, Karen Wang Yanping, Park Mi Kyoung

Abstract:

Tissue samples are precious supply for molecular studies or disease identification diagnosed using molecular assays, namely real-time PCR (qPCR). It is critical to establish the most favorable nucleic acid extraction that gives the PCR-amplifiable genomic DNA. Furthermore, automated nucleic acid extraction is an appealing alternative to labor-intensive manual methods. Operational complexity, defined as the number of steps required to obtain an extracted sample, is one of the criteria in the comparison. Here we are comparing the One BioMed’s automated X8 platform with the commercially available manual-operated kits from QIAGEN Mini Kit and Roche. We extracted DNA from rat fresh-frozen tissue (from different type of organs) in the matrices. After tissue pre-treatment, it is added to the One BioMed’s X8 pre-filled cartridge, and the QIAGEN QIAmp column respectively. We found that the results after subjecting the eluates to the Real Time PCR using BIORAD CFX are comparable.

Keywords: DNA extraction, frozen tissue, PCR, qPCR, rat

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Authors: Tae-Hoon Kim, Kwon-Ha Yoon, Hong Young Jun, Ki-Jong Kim, Young Hwan Lee, Myeung Su Lee, Keum Ha Choi, Ki Jung Yun, Eun Young Cho, Yong-Yeon Jeong, Chung-Hwan Jun

Abstract:

Purpose: To assess the changes of hepatic metabolite for differentiation between non-alcoholic steatohepatitis (NASH) and simple steatosis on proton magnetic resonance spectroscopy (1H-MRS) in both humans and animal model. Methods: The local institutional review board approved this study and subjects gave written informed consent. 1H-MRS measurements were performed on a localized voxel of the liver using a point-resolved spectroscopy (PRESS) sequence and hepatic metabolites of alanine (Ala), lactate/triglyceride (Lac/TG), and TG were analyzed in NASH, simple steatosis and control groups. The group difference was tested with the ANOVA and Tukey’s post-hoc tests, and diagnostic accuracy was tested by calculating the area under the receiver operating characteristics (ROC) curve. The associations between metabolic concentration and pathologic grades or non-alcoholic fatty liver disease(NAFLD) activity scores were assessed by the Pearson’s correlation. Results: Patient with NASH showed the elevated Ala(p<0.001), Lac/TG(p < 0.001), TG(p < 0.05) concentration when compared with patients who had simple steatosis and healthy controls. The NASH patients were higher levels in Ala(mean±SEM, 52.5±8.3 vs 2.0±0.9; p < 0.001), Lac/TG(824.0±168.2 vs 394.1±89.8; p < 0.05) than simple steatosis. The area under the ROC curve to distinguish NASH from simple steatosis was 1.00 (95% confidence interval; 1.00, 1.00) with Ala and 0.782 (95% confidence interval; 0.61, 0.96) with Lac/TG. The Ala and Lac/TG levels were well correlated with steatosis grade, lobular inflammation, and NAFLD activity scores. The metabolic changes in human were reproducible to a mice model induced by streptozotocin injection and a high-fat diet. Conclusion: 1H-MRS would be useful for differentiation of patients with NASH and simple hepatic steatosis.

Keywords: non-alcoholic fatty liver disease, non-alcoholic steatohepatitis, 1H MR spectroscopy, hepatic metabolites

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Authors: Tai-Yue Wang, Yi-Ho Chen

Abstract:

In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model.

Keywords: supply chain, price promotion, mathematical models, dominant retailer

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Authors: Yi-Jiun Chou, Ying-Hsuan Li, Yi-Jung Liu, Hsin-Yu Chiang, Hsuan-Ching Wang

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Background: Patients received therapeutic hypothermia (TH) after resuscitation from cardiac arrest are more dependent on continue and intensive nursing care. It involves many difficult steps, especially achieving target body temperature. To our best knowledge, there is no consensus or recommended standards on nursing practice of TH. Aim: The aim of this study is to increase the completion rate of nursing care at therapeutic hypothermia. Methods: We took five measures: (1) Amendment of nursing standards of therapeutic hypothermia; (2) Amendment of TH checklist items to nursing records; (3) Establishment of monitor procedure; (4) Design each period of TH care reminder cards; (5) Providing in-service training sections of TH for ICU nursing staff. Outcomes: The completion rate of nursing care at therapeutic hypothermia increased from 78.1% to 89.3%. Conclusion: The project team not only increased the completion rate but also improved patient safety and quality of care.

Keywords: therapeutic hypothermia, nursing, critical care, quality of care

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Authors: Ruey-Chi Wang, Po-Hsiang Huang, Ping-Chang Chuang, Shu-Jen Chen

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High-performance Li: CuO/reduced graphene oxide (RGO) flexible electrodes for supercapacitors were fabricated via a low-temperature and low-cost route. To increase energy density while maintaining high power density and long-term cyclability, Li was doped to increase the electrical conductivity of CuO particles between RGO flakes. Electrochemical measurements show that the electrical conductivity, specific capacitance, energy density, and rate capability were all enhanced by Li incorporation. The optimized Li:CuO/RGO electrodes show a high energy density of 179.9 Wh/kg and a power density of 900.0 W/kg at a current density of 1 A/g. Cyclic life tests show excellent stability over 10,000 cycles with a capacitance retention of 93.2%. Li doping improves the electrochemical performance of CuO, making CuO a promising pseudocapacitive material for fabricating low-cost excellent supercapacitors.

Keywords: supercapacitor, CuO, RGO, lithium

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Authors: Yong Chen

Abstract:

To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

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In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: non-minimum phase system, optimal linear quadratic tracker, proportional plus integral observer, state and disturbance estimator

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Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

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The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

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Authors: Fangfang Wang, Tianjing Wang, Leyi Fu, Feng Yun, Ningning Xie, Jue Zhou, Fan Qu

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Background: Ferroptosis, a recently discovered form of programmed cell death characterized by iron-dependent lipid peroxidation, may be linked to polycystic ovary syndrome (PCOS). Diseases marked by iron overload have been correlated with ferroptosis. Coincidently, investigations have revealed anomalies in iron metabolism among women with PCOS; however, there were inconsistencies in the evidence. Objective and Rationale: This review aimed to comprehensively explore the potential relationship between ferroptosis and PCOS by investigating the differences in iron metabolism among women with PCOS in comparison to a control group. Additionally, a narrative synthesis was provided on the past research status regarding the association between PCOS and ferroptosis. Methods: A systematic search of the literature was performed using PubMed, Embase, Web of Science from inception up to December 2022. Search terms relating to assisted PCOS, ferroptosis, and iron metabolism were used. PRISMA guidance was followed. RevMan 5.4 was utilized for conducting the meta-analysis, wherein the investigated outcomes included iron status (ferritin, iron, transferrin saturation) and a systemic iron-regulatory hormone (hepcidin). A narrative synthesis was performed to explore the correlation between PCOS and ferroptosis. Results: In the meta-analysis comprising a total of 16 studies, significant differences in serum ferritin levels between the PCOS group and the control group were observed (15 studies, standardized mean difference (SMD): 0.41, 95% CI: 0.22 to 0.59, P<0.01). This indicates elevated serum ferritin levels in PCOS patients compared to women without PCOS. The transferrin saturation in PCOS patients was significantly higher than that in the control group (3 studies, mean difference (MD): 4.39, 95% CI: 1.67 to 7.11, P<0.01). Regarding serum iron (6 studies, SMD: 0.05, 95% CI: -0.24 to 0.33, P=0.75) and serum hepcidin (4 studies, SMD: -0.44, 95% CI: -1.41 to 0.52, P=0.37), no statistically significant differences were observed between the PCOS group and the control group. Other studies have found that ferroptosis is involved in the occurrence and development of PCOS, offering valuable insights for guiding potential treatment measures and prognosis evaluation of PCOS. In addition, ferroptosis is involved in the miscarriage of PCOS-like rats; thus, controlling ferroptosis might improve pregnancy outcomes in PCOS. Conclusions: The observation of a significant elevation in serum ferritin and transferrin saturation levels in women with PCOS may suggest an underlying disturbance in iron metabolism, potentially inducing the activation of ferroptosis. Further research is imperative to elucidate the underlying pathophysiology, providing insights for potential preventive measures and therapeutic strategies. Limitation: There are some limitations as follows: First, due to limited extractable information, we excluded purely abstract publications and non-English publications. Second, the majority of original articles were case-control studies, making it difficult to determine the causal relationship between iron metabolism abnormalities and the onset of PCOS. Third, there is substantial heterogeneity in the definition of PCOS.

Keywords: polycystic ovary syndrome, ferroptosis, iron metabolism, systematic review and meta-analysis

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Authors: M. Gomaa Abdoelatef, Robert M. Field, Lee, Yong-Kwan

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Growing human populations have placed increased demands on water supplies and a heightened interest in desalination infrastructure. Key elements of the economics of desalination projects are thermal and electrical inputs. With growing concerns over the use of fossil fuels to (indirectly) supply these inputs, coupling of desalination with nuclear power production represents a significant opportunity. Individually, nuclear and desalination technologies have a long history and are relatively mature. For desalination, Reverse Osmosis (RO) has the lowest energy inputs. However, the economically driven output quality of the water produced using RO, which uses only electrical inputs, is lower than the output water quality from thermal desalination plants. Therefore, modern desalination projects consider that RO should be coupled with thermal desalination technologies (MSF, MED, or MED-TVC) with attendant steam inputs to permit blending to produce various qualities of water. A large nuclear facility is well positioned to dispatch large quantities of both electrical and thermal power. This paper considers the supply of thermal energy to a large desalination facility to examine heat balance impact on the nuclear steam cycle. The APR1400 nuclear plant is selected as prototypical from both a capacity and turbine cycle heat balance perspective to examine steam supply and the impact on electrical output. Extraction points and quantities of steam are considered parametrically along with various types of thermal desalination technologies to form the basis for further evaluations of economically optimal approaches to the interface of nuclear power production with desalination projects. In our study, the thermodynamic evaluation will be executed by DE-TOP which is the IAEA desalination program, it is approved to be capable of analyzing power generation systems coupled to desalination systems through various steam extraction positions, taking into consideration the isolation loop between the APR-1400 and the thermal desalination plant for safety concern.

Keywords: APR-1400, desalination, DE-TOP, IAEA, MSF, MED, MED-TVC, RO

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Authors: A. Khosrozadeh, M. A. Darabi, M. Xing, Q. Wang

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Fabrication of a high-performance supercapacitor (SC) using a flexible cellulose-based composite film of polyaniline (PANI), reduced graphene oxide (RGO), and silver nanowires (AgNWs) is reported. The flexibility, high capacitive behaviour, and cyclic stability of the entire device make it a good candidate for wearable SCs. The results show that a capacitance as high as 73.4 F/g (1.6 F/cm2) at a discharge rate of 1.1 A/g is achieved by the device. In addition, the SC demonstrates a power density up to 468.8 W/kg and an energy density up to 5.1 wh/kg. The flexibility of the composite film is attributed to the binding effect of cellulose fibers as well as reinforcing effect of AgNWs. The excellent electrochemical performance of the device is found to be owing to the synergistic effect between PANI/RGO/AgNWs ternary in a cushiony cellulose matrix and porous structure of the composite.

Keywords: cellulose, polyaniline, reduced graphene oxide, silver, super capacitor

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Authors: Wang Yanping Karen, Mohd Rafeah Siti, Park MI Kyoung

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Formalin-fixed paraffin embedded (FFPE) tissue is important in the area of oncological diagnostics. This method of preserving tissues enabling them to be stored easily at ambient temperature for a long time. This decreases the risk of losing the DNA quantity and quality after extraction, reducing sample wastage, and making FFPE more cost effective. However, extracting DNA from FFPE tissue is a challenge as DNA purified is often highly cross-linked, fragmented, and degraded. In addition, this causes problems for many downstream processes. In this study, there will be a comparison of DNA extraction efficiency between One BioMed’s Xceler8 automated platform with commercial available extraction kits (Qiagen and Roche). The FFPE tissue slices were subjected to deparaffinization process, pretreatment and then DNA extraction using the three mentioned platforms. The DNA quantity were determined with real-time PCR (BioRad CFX ) and gel electrophoresis. The amount of DNA extracted with the One BioMed’s X8 platform was found to be comparable with the other two manual extraction kits.

Keywords: DNA extraction, FFPE tissue, qiagen, roche, one biomed X8

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Authors: Chien-Lin Wang, Cha-Ling Ko, Tainsong Chen

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Pulse wave velocity (PWV) of blood flow provides important information of vessel property and blood pressure which can be used to assess cardiovascular disease. However, the above measurements need expensive equipment, such as Doppler ultrasound, MRI, angiography etc. The photoplethysmograph (PPG) signals are commonly utilized to detect blood volume changes. In this study, two infrared (IR) probes are designed and placed at a fixed distance from finger base and fingertip. An analog circuit with automatic gain adjustment is implemented to get the stable original PPG signals from above two IR probes. In order to obtain the time delay precisely between two PPG signals, we obtain the pulse transit time from the second derivative of the original PPG signals. To get a portable, wireless and low power consumption PWV measurement device, the low energy Bluetooth 4.0 (BLE) and the microprocessor (Cortex™-M3) are used in this study. The PWV is highly correlated with blood pressure. This portable device has potential to be used for continuous blood pressure monitoring.

Keywords: pulse wave velocity, photoplethysmography, portable device, biomedical engineering

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Mahan Qwamizadeh, Kun Zhou, Zuoqi Zhang, Yong Wei Zhang

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Typical load-bearing biological materials like bone, mineralized tendon and shell, are biocomposites made from both organic (collagen) and inorganic (biomineral) materials. This amazing class of materials with intrinsic internally designed hierarchical structures show superior mechanical properties with regard to their weak components from which they are formed. Extensive investigations concentrating on static loading conditions have been done to study the biological materials failure. However, most of the damage and failure mechanisms in load-bearing biological materials will occur whenever their structures are exposed to dynamic loading conditions. The main question needed to be answered here is: What is the relation between the layout and architecture of the load-bearing biological materials and their dynamic behavior? In this work, a staggered model has been developed based on the structure of natural materials at nanoscale and Finite Element Analysis (FEA) has been used to study the dynamic behavior of the structure of load-bearing biological materials to answer why the staggered arrangement has been selected by nature to make the nanocomposite structure of most of the biological materials. The results showed that the staggered structures will efficiently attenuate the stress wave rather than the layered structure. Furthermore, such staggered architecture is effectively in charge of utilizing the capacity of the biostructure to resist both normal and shear loads. In this work, the geometrical parameters of the model like the thickness and aspect ratio of the mineral inclusions selected from the typical range of the experimentally observed feature sizes and layout dimensions of the biological materials such as bone and mineralized tendon. Furthermore, the numerical results validated with existing theoretical solutions. Findings of the present work emphasize on the significant effects of dynamic behavior on the natural evolution of load-bearing biological materials and can help scientists to design bioinspired materials in the laboratories.

Keywords: load-bearing biological materials, nanostructure, staggered structure, stress wave decay

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Authors: Yong Min You

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The study on the torque ripple of Permanent Magnet Synchronous Motors (PMSMs) has been rapidly progressed, which effects on the noise and vibration of the electric vehicle. There are several ways to reduce torque ripple, which are the increase in the number of slots and poles, the notch of the rotor and stator teeth, and the skew of the rotor and stator. However, the conventional methods have the disadvantage in terms of material cost and productivity. The demagnetization characteristic of PMSMs must be attained for electric vehicle application. Due to rare earth supply issue, the demand for Dy-free permanent magnet has been increasing, which can be applied to PMSMs for the electric vehicle. Dy-free permanent magnet has lower the coercivity; the demagnetization characteristic has become more significant. To improve the torque ripple as well as the demagnetization characteristics, which are significant parameters for electric vehicle application, an unequal air-gap model is proposed for a PMSM. A shape optimization is performed to optimize the design variables of an unequal air-gap model. Optimal design variables are the shape of an unequal air-gap and the angle between V-shape magnets. An optimization process is performed by Latin Hypercube Sampling (LHS), Kriging Method, and Genetic Algorithm (GA). Finite element analysis (FEA) is also utilized to analyze the torque and demagnetization characteristics. The torque ripple and the demagnetization temperature of the initial model of 45kW PMSM with unequal air-gap are 10 % and 146.8 degrees, respectively, which are reaching a critical level for electric vehicle application. Therefore, the unequal air-gap model is proposed, and then an optimization process is conducted. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 7.7 %. In addition, the demagnetization temperature of the optimized model was also increased by 1.8 % while maintaining the efficiency. From these results, a shape optimized unequal air-gap PMSM has shown the usefulness of an improvement in the torque ripple and demagnetization temperature for the electric vehicle.

Keywords: permanent magnet synchronous motor, optimal design, finite element method, torque ripple

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Authors: Lin Xie, Yang Wang

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An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: education, communication, psychology, student learning, language teaching

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Authors: Li Li, Lei Wang, Chenglin Du, Mengxin Ren, Xinzheng Zhang, Wei Cai, Jingjun Xu

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Strong coupling between excitons of quantum dots and plasmons in nanocavites can be realized at room temperature due to the strong confinement of the plasmon fields, which offers building blocks for quantum information systems or ultralow-power switches and lasers. In this work, by using cathodoluminescence, ultrastrong coupling with Rabi splitting above 1 eV between breathing plasmons in Aluminum metal-insulator-metal (MIM) cavity and excited state of CdZnS/ZnS quantum dots was reported in near-UV spectrum. Analytic analysis and full-wave electromagnetic simulations provide the evidence for the strong coupling and confirm the hybridization of the QDs exciton and LSP breathing mode. This study opens the way for new emerging applications based on strongly coupled light-matter states all over the visible region down to ultra-violet frequencies.

Keywords: breathing mode, plasmonics, quantum dot, strong coupling, ultraviolet

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Authors: Yeo Ryeong Jeon, Pyong Kon Cho, Eun Ok Han, Hyon Chul Jang, Yong Min Kim

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This study surveyed on recognition related to radiation safety for radiation safety managers and workers those who have been worked in Republic of Korea education and research institution. At present, South Korea has no guideline and manual of radiation safety for education and research institution. Therefore, we tried to find an educational basis for development of radiation safety guideline and manual. To check the level of knowledge, attitude, and behavior about radiation safety, we used the questionnaire that consisted of 29 questions against knowledge, attitude and behavior, 4 questions against self-efficacy and expectation based on four factors (radiation source, human, organizational and physical environment) of the Haddon's matrix. Responses were collected between May 4 and June 30, 2015. We analyzed questionnaire by means of IBM SPSS/WIN 15 which well known as statistical package for social science. The data were compared with mean, standard deviation, Pearson's correlation, ANOVA (analysis of variance) and regression analysis. 180 copies of the questionnaire were returned from 60 workplaces. The overall mean results for behavior level was relatively lower than knowledge and attitude level. In particular, organizational environment factor on the radiation safety management indicated the lowest behavior level. Most of the factors were correlated in Pearson’s correlation analysis, especially between knowledge of human factors and behavior of human factors (Pearson’s correlation coefficient 0.809, P<.01). When analysis performed in line with the main radiation source type, institutions where have been used only opened RI (radioisotope) behavior level was the lowest among all subjects. Finally, knowledge of radiation source factor (β=0.556, P<.001) and human factor(β=0.376, P<.001) had the greatest impact in terms of behavior practice. Radiation safety managers and workers think positively about radiation safety management, but are poorly informed organizational environment of their institution. Thus, each institution need to efforts to settlement of radiation safety culture. Also, pedagogical interventions for improving knowledge on radiation safety needs in terms of safety accident prevention.

Keywords: radiation safety management, factor analysis, SPSS, republic of Korea

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

Abstract:

Cloud virtualization technologies are becoming more and more prevalent, cloud users usually encounter the problem of how to access to the virtualized remote desktops easily over the web without requiring the installation of special clients. To resolve this issue, we took advantage of the HTML5 technology and developed web-based remote desktop. It permits users to access the terminal which running in our cloud platform from anywhere. We implemented a sketch of web interface following the cloud computing concept that seeks to enable collaboration and communication among users for high performance computing. Given the development of remote desktop virtualization, it allows to shift the user’s desktop from the traditional PC environment to the cloud platform, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. This is also made possible by the low administrative costs as well as relatively inexpensive end-user terminals and reduced energy expenses.

Keywords: virtualization, remote desktop, HTML5, cloud computing

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Authors: Jianhua Wang, Ying Zhou, Han Guo

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Translation underwent culture turn for more than half a century, which brought translation and its studies beyond intra-texts. Different cultures in recent years have developed towards a translation turn, which made a great contribution to relocate national or local cultures being localized to become regional or global cultures. As China grows quickly economically integrating into the world, it becomes urgent to relate China’s story and disseminate the Chinese culture. Due to the weaknesses and drawbacks of different existing cultural translation theories for Chinese culture to go out, a new perspective on translation turn for the go-out of Chinese culture should be drawn to spread better and disseminate Chinese culture to other countries. Based on the existing cultural translation theories, the equivalence of ideology, style of the translator and agency of the support are proposed to draw a new perspective: an innovative poly-system theory for Chinese culture translation.

Keywords: cultural translation theory, Chinese culture, innovative poly system, global cultures

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Authors: Hoong C. Chin, Soon H. Chew, Zhaoxia Wang

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Work on sustainable developments and the call for action in education for sustainable development have been ongoing for a number of years. Training engineering students with the relevant competencies, particularly in sustainable development literacy, has been identified as an urgent task in universities. This requires not only a holistic, multi-disciplinary approach to education but also a suitable training environment to develop the needed skills and to inculcate the appropriate attitudes in students towards sustainable development. To demonstrate how this can be done, a module involving an overseas field trip was introduced in 2013 at the National University of Singapore. This paper provides details of the module and describes its training philosophy and methods. Measured against the student learning outcomes, stipulated by the Engineering Accreditation Board, the module scored well on all of them, particularly those related to complex problem solving, environmental and sustainability awareness, multi-disciplinary team work and varied-level communications.

Keywords: civil engineering education, socio-economically sustainable infrastructure, student learning outcome, sustainable development

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Authors: Wang Lin, Li Zhiqiang

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The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: behavior pattern, cooperative learning, data analyze, k-means clustering algorithm

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Authors: Wang Zhanquan, Yang Zeping, Gu Chunhua, Zhu Fazhi, Guo Weibin

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Recently, Massive Open Online Courses (MOOCs) are becoming the new trend of education. There are many problems under the environment of Database Principle curriculum teaching process in MOOCs, such as teaching ideas and theories which are out of touch with the reality, how to carry out the technical teaching and interactive practice in the MOOCs environment, thus the methods of database course under the environment of MOOCs are proposed. There are three processes to deal with problem solving in the research, which are problems proposed, problems solved, and inductive analysis. The present research includes the design of teaching contents, teaching methods in classroom, flipped classroom teaching mode under the environment of MOOCs, learning flow method and large practice homework. The database designing ability is systematically improved based on the researching methods.

Keywords: problem solving-driven, MOOCs, teaching art, learning flow;

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Wang Qian, Bian Cheng Xiang

Abstract:

In recent years, with the improvement of China's urbanization level, the number of urban motor vehicles has grown rapidly. As residents' daily commuting necessities, cars cause a lot of exhaust emissions and urban traffic congestion. In the "Fourteenth Five Year Plan" of China, it is proposed to strive to reach the peak of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. Urban transport accounts for a high proportion of carbon emission sources. It is an important driving force for the realization of China's carbon peak strategy. Some cities have introduced and implemented the policy of "car restriction" to solve related urban problems by reducing the use of cars. This paper analyzes the implementation of the "automobile restriction" policy, evaluates the relevant effects of the automobile restriction policy, and discusses how to better optimize the "automobile restriction" policy in the process of urban governance.

Keywords: carbon emission, traffic jams, vehicle restrictions, evaluate

Procedia PDF Downloads 130

Authors: Wang, Kuei-Ing, Jou-Fan Shih

Abstract:

This study adopts deterrence theory as well as social identities as moderators, and explores their moderating affects on online toxic disinhibition. Survey and Experimental methodologies are applied to test the research model and four hypotheses are developed in this study. The controllability of identity positively influenced the behavior of toxic disinhibition both in experimental and control groups while the fluidity of the identity did not have significant influences on online disinhibition. Punishment certainty, punishment severity as well as social identity negatively moderated the relation between the controllability of the identity and the toxic disinhibition. The result of this study shows that internet users hide their real identities when they behave inappropriately on internet, but once they acknowledge that the inappropriate behavior will be found and punished severely, the inappropriate behavior then will be weakened.

Keywords: seductive properties of internet, online disinhibition, punishment certainty, punishment severity, social identity

Procedia PDF Downloads 487

Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

Abstract:

The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

Procedia PDF Downloads 93

Authors: Jiandong Lv, Xingang Wang, Cuiling Shao

Abstract:

The rapid development of social media platforms has made it one of the important news sources. While it provides people with convenient real-time communication channels, fake news and rumors are also spread rapidly through social media platforms, misleading the public and even causing bad social impact in view of the slow speed and poor consistency of artificial rumor detection. We propose an end-to-end rumor detection model-TIMF, which captures the dependencies between multimodal data based on the interactive attention mechanism, uses a transformer for cross-modal feature sequence mapping and combines hybrid fusion strategies to obtain decision results. This paper verifies two multi-modal rumor detection datasets and proves the superior performance and early detection performance of the proposed model.

Keywords: hybrid fusion, multimodal fusion, rumor detection, social media, transformer

Procedia PDF Downloads 199