Search results for: Pinqiao Wang

Authors: Xiang Wang, Yan Pang, Zhaomiao Liu

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Droplet-based microfluidics have been studied extensively with the development of the Micro-Electro-Mechanical System (MEMS) which bears the advantages of high throughput, high efficiency, low cost and low polydispersity. Droplets, worked as versatile carriers, could provide isolated chambers as the internal dispersed phase is protected from the outside continuous phase. Droplets are used to add reagents to start or end bio-chemical reactions, to generate concentration gradients, to realize hydrate crystallization or protein analyses, while droplets coalescence acts as an important control technology. In this paper, deionized water is used as the dispersed phase, and several kinds of oil are used as the continuous phase to investigate the influence of the viscosity ratio of the two phases on the coalescence process. The microchannels are fabricated by coating a polydimethylsiloxane (PDMS) layer onto another PDMS flat plate after corona treatment. All newly made microchannels are rinsed with the continuous oil phase for hours before experiments to ensure the swelling fully developed. High-speed microscope system is used to document the serial videos with a maximum speed of 2000 frames per second. The critical capillary numbers (Ca*) of droplet pairs in various junctions are studied and compared. Ca* varies with different junctions or different liquids within the range of 0.002 to 0.01. However, droplets without extra control would have the problem of synchronism which reduces the coalescence efficiency.

Keywords: coalescence, concentration, critical capillary number, droplet pair, split

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Authors: Saif Ullah, Guan Zailin, Xu Xianhao, He Zongdong, Wang Baoxi

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Assembly line balancing problem is aimed to divide the tasks among the stations in assembly lines and optimize some objectives. In assembly lines the workload on stations is different from each other due to different tasks times and the difference in workloads between stations can cause blockage or starvation in some stations in assembly lines. Buffers are used to store the semi-finished parts between the stations and can help to smooth the assembly production. The assembly line balancing and buffer sizing problem can affect the throughput of the assembly lines. Assembly line balancing and buffer sizing problems have been studied separately in literature and due to their collective contribution in throughput rate of assembly lines, balancing and buffer sizing problem are desired to study simultaneously and therefore they are considered concurrently in current research. Current research is aimed to maximize throughput, minimize total size of buffers in assembly line and minimize workload variations in assembly line simultaneously. A multi objective optimization objective is designed which can give better Pareto solutions from the Pareto front and a simple example problem is solved for assembly line balancing and buffer sizing simultaneously. Current research is significant for assembly line balancing research and it can be significant to introduce optimization approaches which can optimize current multi objective problem in future.

Keywords: assembly line balancing, buffer sizing, Pareto solutions

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Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

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Authors: Quan Li, Dongcai Shen, Zhengting Xiao, Xin Liu Mingrui Wu, Licheng Liu, Qin Li, Xianguo Li, Wentai Wang

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Direct electrocatalytic nitrogen oxidation (NOR) provides a promising alternative strategy for synthesizing high-value-added nitric acid from widespread N₂, which overcomes the disadvantages of the Haber-Bosch-Ostwald process. However, the NOR process suffers from the limitation of high N≡N bonding energy (941 kJ mol− ¹), sluggish kinetics, low efficiency and yield. It is a prerequisite to develop more efficient electrocatalysts for NOR. Herein, we synthesized double-shelled CeO₂ hollow spheres (D-CeO₂) and further modified with Ti₃C₂ MXene quantum dots (MQDs) for electrocatalytic N₂ oxidation, which exhibited a NO₃− yield of 71.25 μg h− ¹ mgcat− ¹ and FE of 31.80% at 1.7 V. The unique quantum size effect and abundant edge active sites lead to a more effective capture of nitrogen. Moreover, the double-shelled hollow structure is favorable for N₂ fixation and gathers intermediate products in the interlayer of the core-shell. The in-situ infrared Fourier transform spectroscopy confirmed the formation of *NO and NO₃− species during the NOR reaction, and the kinetics and possible pathways of NOR were calculated by density functional theory (DFT). In addition, a Zn-N₂ reaction device was assembled with D-CeO₂/MQDs as anode and Zn plate as cathode, obtaining an extremely high NO₃− yield of 104.57 μg h− ¹ mgcat− ¹ at 1 mA cm− ².

Keywords: electrocatalytic N₂ oxidation, nitrate production, CeO₂, MXene quantum dots, double-shelled hollow spheres

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Authors: Azizza Mala, Babo Fadlalla, Elnour Mohamed, Siran Wang, Junfeng Li, Tao Shao

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Sweet sorghum is considered one of the best plants for silage production and is now a more important feed crop in many countries worldwide. It is simple to ensile because of its high water-soluble carbohydrates (WSC) concentration and low buffer capacity. This study investigated the effect of adding Pediococcus acidilactici AZZ5 and Lactobacillus plantarum AZZ4 isolated from elephant grass on the fermentation quality of sweet sorghum silage. One commercial bacteria Lactobacillus Plantarum, Ecosyl MTD/1(C.B.)), and two strains were used as additives Pediococcus acidilactici (AZZ5), Lactobacillus plantarum subsp. Plantarum (AZZ4) at 6 log colony forming units (cfu)/g of fresh sweet sorghum grass in laboratory silos (1000g). After 15, 30, and 60 days, the silos for each treatment were opened. All of the isolated strains enhanced the silage quality of sweet sorghum silage compared to the control, as evidenced by significantly (P < 0.05) lower ammonia nitrogen (NH3-N) content and undesirable microbial counts, as well as greater lactic acid (L.A.) contents and lactic acid/acetic acid (LA/AA) ratios. In addition, AZZ4 performed better than all other inoculants during ensiling, as evidenced by a significant (P < 0.05) reduction in pH and ammonia-N contents and a significant increase in lactic acid contents.

Keywords: fermentation, lactobacillus plantarum, lactic acid bacteria, pediococcus acidilactic, sweet sorghum

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Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

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Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structure-process-property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: biosensor, DNA, biomarker, molecular dynamics simulation

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Authors: Chang-Liang Shih, Kuei-Min Liao, Ya-Yuan Wang, Wu-Chun Tu

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Forcipomyia taiwana, an important vexing pest, influences the development of the industry of Taiwan tourism and the quality of country life. Using human-attractant method to investigate the blood-sucking behavior of Forcipomyia taiwana in three districts in Taichung, it revealed that female F. taiwana only exhibits blood-sucking behavior in daytime, not in nighttime. The blooding-sucking behavior of female F. taiwana was affected by some factors, i.e., season and atmospheric factors. During 2008 to 2010, our study revealed that blood-sucking behavior commenced from 7:00 to 8:00 in the spring equinox, the summer solstice and the autumnal equinox, but from 8:00 to 9:00 in the winter solstice. However, regardless of any seasons, it revealed that blood-sucking behavior reached the acme between 13:00 and 15:00, and then descending. In those four seasons, the summer solstice had longer lighting and higher temperature, the average sucking activity was around 12 hours, on the contrary, the winter solstice had shorter lighting and lower temperature, the average sucking activity bridled to around 8 hours whilst it retrenched to 11 hours in the spring equinox and the autumnal equinox. To analyze the correlation between blood-sucking behavior and atmospheric factors, it revealed that female blood-sucking behavior was correlated positively to temperature and lighting but negatively to humidity. In addition, our study also showed that there is no blood-sucking behavior under 18ºC.

Keywords: Forcipomyia taiwana, circadian rhythm, blood-sucking behavior, season

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Authors: Yue Shuai Zhao, Rong Ping Shao, Wei Sun, Guo Hua Ren, Yong Wang, Li Chen Sun

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A large-scale cryopump (DN1250) used in large vacuum leak detecting system was designed and its performance experimentally investigated by Beijing Institute of Spacecraft Environment Engineering. The cryopump was cooled by four closed cycle helium refrigerators (two dual stage refrigerators and two single stage refrigerators). Detailed numerical analysis of the heat transfer in the first stage array and the second stage array were performed by using computational fluid dynamic method (CFD). Several design parameters were considered to find the effect on the temperature distribution and the cooldown time. The variation of thermal conductivity and heat capacity with temperature was taken into account. The thermal analysis method based on numerical techniques was introduced in this study, the heat transfer in the first stage array and the second stage cryopanel was carefully analyzed to determine important considerations in the thermal design of the cryopump. A performance test system according to the RNEUROP standards was built to test main performance of the cryopump. The experimental results showed that the structure of first stage array which was optimized by the method could meet the requirement of the cryopump well. The temperature of the cryopanel was down to 10K within 300 min, and the result of the experiment was accordant with theoretical analysis' conclusion. The test also showed that the pumping speed for N2 of the pump was up to 57,000 L/s, and the crossover was over than 300,000 Pa•L.

Keywords: cryopump, temperature distribution, thermal analysis, CFD Simulation

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Szu-Hua Wang

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Urban ecosystems, as complex coupled human-environment systems, contain abundant natural resources for breeding natural assets and, at the same time, attract urban assets and consume natural resources, triggered by urban development. Land use change illustrates the interaction between human activities and environments factually. However, IPCC (2014) announces that land use change and urbanization due to human activities are the major cause of climate change, leading to serious impacts on urban ecosystem resilience and risk. For this reason, risk assessment and resilience analysis are the keys for responding to climate change on urban ecosystems. Urban spatial planning can guide urban development by land use planning, transportation planning, and environmental planning and affect land use allocation and human activities by building major constructions and protecting important national land resources simultaneously. Urban spatial planning can aggravate climate change and, on the other hand, mitigate and adapt climate change. Research on effects of spatial planning on land use change and climate change is one of intense issues currently. Therefore, this research focuses on developing frameworks for risk assessment and resilience analysis from the aspect of ecosystem based on typhoon precipitation in Taipei area. The integrated method of risk assessment and resilience analysis will be also addressed for applying spatial planning practice and sustainable development.

Keywords: ecosystem, land use change, risk analysis, resilience

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Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

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In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI

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Authors: Zhuoyuan Wang, Benson T. H. Lim, Imriyas Kamardeen

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Effective service quality management has long been touted as a means of improving project and organisational performance. Particularly, in construction projects, main contractors are often seen as a broker between clients and subcontractors, and their service quality is thus associated with the overall project affinity and outcomes. While a considerable amount of research has focused on the aspect of clients-main contractors, very little research has been done to explore the effect of contractors’ service quality on subcontractors’ behaviours and so project outcomes. In addressing this gap, this study surveyed 97 subcontractors in the Chinese Construction industry and data was analysed using the Partial Least Square (PLS) Structural Equation Modelling (SEM) technique. The overall findings reveal that subcontractors categorised main contractors’ service quality into three dimensions: assurance; responsiveness; reliability and empathy. Of these, it is found that main contractors’ ‘assurance’ and ‘responsiveness’ positively influence subcontractors’ intention to engage in contractual behaviours. The results further show that the subcontractors’ intention to engage in organizational citizenship behaviours is associated with how flexible and committed the main contractors are in reliability and empathy. Collectively, both subcontractors’ contractual and organizational citizenship behaviours positively influence the overall project outcomes. In conclusion, the findings inform contractors different strategies towards managing and gaining subcontractors’ behaviour commitment in a socially connected, yet complex and uncertain, business environment.

Keywords: construction firms, organisational citizenship behaviour, service quality, social exchange theory

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Authors: Xiaoxiao Yu, Guodu He, Zihua Wu, Yuanyuan Wang, Huaqing Xie

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Core-shell composite structure is a common method to regulate the spectral absorption of nanofluids, but there occur complex preparation processes, which limit the applications in some fields, such as photothermal utilization and catalysis. This work proposed point-mode Cu₂O/TiN plasmonic nanofluids to regulate the spectral capturing ability and simplify the preparation process. Non-noble TiN nanoparticles with the localized surface plasmon resonance effect are dispersed in Cu₂O nanoparticles for forming a multi-point resonance source to enhance the spectral absorption performance. The experimental results indicate that the multiple resonance effect of TiN effectively improves the optical absorption and expands the absorption region. When the radius of Cu₂O nanoparticles is equal to 150nm, the optical absorption of point-mode Cu₂O/TiN plasmonic nanoparticles is best. Moreover, the photothermal conversion efficiency of Cu₂O/TiN plasmonic nanofluid can reach 97.5% at a volume fraction of 0.015% and an optical depth of 10mm. The point-mode nanostructure effectively enhances the optical absorption properties and greatly simplifies the preparation process of the composite nanoparticles, which can promote the application of multi-component photonic nanoparticles in the field of solar energy.

Keywords: solar energy, nanofluid, point-mode structure, Cu₂O/TiN, localized surface plasmon resonance effect

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Authors: Kun-Ping Cheng, Dong-Shang Chang, Rou-Wen Wang

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Pre-treatment of automobile paint-shop procedures are the preparation of warm water rinsing tank, hot water rinsing tank, degreasing tank, phosphate tank. The conventional boiler steam fuel is natural gas, producing steam to supply the heat exchange of each tank sink. In this study, the high-frequency soldering economizer is developed for recovering waste heat in the automotive paint-shop (RTO, Regenerative Thermal Oxidation). The heat recovery rate of the new economizer is 20% to 30% higher than the conventional embedded heat pipe. The adaptive control system responded to both RTO furnace exhaust gas and heat demands. In order to maintain the temperature range of the tanks, pre-treatment tanks are directly heated by waste heat recovery device (gas-to-water heat exchanger) through the hot water cycle of heat transfer. The performance of developed waste heat recovery system shows the annual recovery achieved to 1,226,411,483 Kcal of heat (137.8 thousand cubic meters of natural gas). Boiler can reduce fuel consumption by 20 to 30 percent compared to without waste heat recovery. In order to alleviate environmental impacts, the temperature at the end of the flue is further reduced from 160 to 110°C. The innovative waste heat recovery is helpful to energy savings and sustainable environment.

Keywords: waste heat recovery system, sustainability, RTO (Regenerative Thermal Oxidation), economizer, automotive industry

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Authors: Jacqueline Miller, Dongyuan Y. Wang, F. Dan Richard

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Before trying to make an ethical machine that holds a higher ethical standard than humans, a better understanding of human moral standards that could be used as a guide is crucial. How humans make decisions in dangerous driving situations like moral dilemmas can contribute to developing acceptable ethical principles for autonomous vehicles (AVs). This study uses a driving simulator to investigate whether drivers make utilitarian choices (choices that maximize lives saved and minimize harm) in unavoidable automobile accidents (moral dilemmas) with time pressure manipulated. This study also investigates how impulsiveness influences drivers’ behavior in moral dilemmas. Manipulating time pressure results in collisions that occur at varying time intervals (4 s, 5 s, 7s). Manipulating time pressure helps investigate how time pressure may influence drivers’ response behavior. Thirty-one undergraduates participated in this study using a STISM driving simulator to respond to driving moral dilemmas. The results indicated that the percentage of utilitarian choices generally increased when given more time to respond (from 4 s to 7 s). Additionally, participants in vehicle scenarios preferred responding right over responding left. Impulsiveness did not influence utilitarian choices. However, as time pressure decreased, response time increased. Findings have potential implications and applications on the regulation of driver assistance technologies and AVs.

Keywords: time pressure, automobile moral dilemmas, impulsiveness, reaction time

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Authors: Pei-Jung Wu, Ching-Ying Huang, Chih-Chia Lin, Chun-Han Li, Chien-Yuan Wang

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The fuel cell market has considerable development potential, but the cost is still less competitive. Replacing the traditional graphite plate with a stainless steel plate as a bipolar plate can greatly reduce the weight and volume of the stack, and has more cost advantages. However, the passivation layer on the surface of stainless steel makes the contact resistance reach the ohmic level and reduces the performance of the fuel cell. Therefore, it is necessary to reduce the interfacial contact resistance through the surface treatment. In this research, the thickness, uniformity, interfacial contact resistance (ICR), and adhesion of the carbon-based layer was analyzed. On the other hand, the effect of coating properties on the performance of the fuel cell was verified through I-V tests. The results show that after coating the contact resistance is greatly reduced by three stages to the microohm level, and as the film thickness is reduced, the contact resistance is reduced from 229~118 mΩ-cm² to 135~73 mΩ-cm² at a general assembly pressure of 1 to 2 MPa., and the current density at 0.6 V increased from 485.7 mA/cm² to 575.7 mA/cm². This study verifies the importance of the uniformity and ICR of the coating on proton exchange membrane fuel cell (PEMFC), and the surface coating technology is the key to affecting the characteristics of the coating.

Keywords: contact resistance, proton exchange membrane fuel cell, PEMFC, SS bipolar plate, spray coating process

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Authors: Yuan Fang, Wang-Ming Li, Yi-Chen Ruan

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Rural healthy old-age care for urban elderly who go to surrounding villages on vacation is a new mode of old-age care in developed coastal areas of China. Such villages that receive urban elderly can be called old-caring villages. Due to the popularity of healthy old-age care in rural areas, more and more urban elderly people participate in the ranks of rural old-age care, resulting in excessive number of tourists in some old-caring villages, exceeding the carrying capacity of the village. Excessive passenger flow may damage the ecological environment, social environment, and facilities environment of the village, and even affect the development potential of the village pension industry. On the basis of on-site investigation and questionnaire survey, this paper summarizes the willingness and behavioral characteristics of the urban elderly population and finds that it will have a certain impact on the old-caring villages in the process of pension vacation in the aspects of ecology, construction, society, and economy. According to the influence of tourists, the paper constructs a system of capacity restriction factors of the old-caring villages, which includes four types: ecological environment capacity, policy environment capacity, perceived congestion capacity, and village service capacity, and fourteen specific indicators. It will provide a theoretical basis for reasonable control of the development scale of the old-caring villages.

Keywords: old-caring villages, restriction factors system, tourists' influence, environmental capacity

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Authors: Jui-Chien Wang

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Because of China’s continued economic growth and dominance, increasingly many students of Chinese from western countries are interested in pursuing careers related to China. Unless we do more to teach them about contemporary Chinese society and Chinese cultural codes, however, few will be able to do so successfully. Most traditional language textbooks treat these topics only cursorily, and, because of the rapid pace of China’s social and economic development, what they do cover is frequently outdated and insufficient. However, understanding contemporary Chinese society and Chinese cultural codes is essential to successfully negotiating real-world China. The current paper details one of the main ways in which the presenter has dealt with this educational lacuna: the development and implementation of a series of teaching modules for advanced Chinese language classes. Each module explores a particular area, provides resources, and raises questions to engage students in strengthening their language and cultural competencies. The teaching modules address four main areas: (1) Chinese behavioral culture; (2) critical issues in contemporary China; (3) current events in China; and (4) great social transformations in contemporary China. The presenter will also discuss lessons learned and insights gained during the development and implementation process as well as the benefits of using these modules. In addition, the presenter will offer suggestions for the application of these modules, so that other language teachers will be able to make better use of them in their own classrooms.

Keywords: behavioral culture, contemporary Chinese society, cultural code, teaching module

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Authors: Deng Zengming, Wang Mingjiang

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As 3D video is explored as a hot research topic in the last few decades, free-viewpoint TV (FTV) is no doubt a promising field for its better visual experience and incomparable interactivity. View synthesis is obviously a crucial technology for FTV; it enables to render images in unlimited numbers of virtual viewpoints with the information from limited numbers of reference view. In this paper, a novel hybrid synthesis framework is proposed and blending priority is explored. In contrast to the commonly used View Synthesis Reference Software (VSRS), the presented synthesis process is driven in consideration of the temporal correlation of image sequences. The temporal correlations will be exploited to produce fine synthesis results even near the foreground boundaries. As for the blending priority, this scheme proposed that one of the two reference views is selected to be the main reference view based on the distance between the reference views and virtual view, another view is chosen as the auxiliary viewpoint, just assist to fill the hole pixel with the help of background information. Significant improvement of the proposed approach over the state-of –the-art pixel-based virtual view synthesis method is presented, the results of the experiments show that subjective gains can be observed, and objective PSNR average gains range from 0.5 to 1.3 dB, while SSIM average gains range from 0.01 to 0.05.

Keywords: fusion method, Gaussian mixture model, hybrid framework, view synthesis

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Authors: Yu Wen Wang, Shyh Ming Kuo, Hsia Ying Cheng, Yu Chiuan Wu

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Liver fibrosis is caused by the activation of hepatic stellate cells in the liver to secrete excessive and deposition of extracellular matrix. In recent years, many treatment strategies have been developed to reduce the activation of hepatic stellate cells and therefore to increase the decomposition of extracellular matrix. Bacopa monnieri, an herbaceous plant of the scrophulariaceae, containing saponins and glycosides, which with antioxidant, anti-inflammation, pain relief and free radical scavenging characteristics. This study was to evaluate the inhibition of hepatic stellate cell activity by Bacopa monnieri extract and its therapeutic potential in treating thioacetamide-induced liver fibrosis in rats. The results showed that the IC50 of Bacopa monnieri extract was 0.39 mg/mL. Bacopa monnieri extract could effectively reduce H2O2-induced hepatic stellate cells inflammation. In the TAA-induced liver fibrosis animal studies, albumin secretion recovered to normal level after treated with Bacopa monnieri extract for 2-w, and fibrosis related proteins, α-SMA and TGF-1levels decreased indicating the extract exerted therapeutic effect on the liver fibrosis. However, inflammatory factors TNF- obviously decreased after 4-w treatment. In summary, we could successfully extract the main component-Bacopaside I from the plant and acquired a potential therapy using this component in treating TAA-induced liver fibrosis in rat.

Keywords: anti-inflammatory, Bacopa monnieri, fibrosis, hepatic stellate cells, water extract

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Authors: Xiaoying Guo, Xiangyun Wang, Chunhua Jia

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Web page has been one of the most important way of knowing the world. Humans catch a lot of information from it everyday. Thus, understanding where human looks when they surfing the web pages is rather important. In normal scenes, the down-top features and top-down tasks significantly affect humans’ eye movement. In this paper, we investigated if the conventional visual salience algorithm can properly predict humans’ visual attractive region when they viewing the web pages. First, we obtained the eye movement data when the participants viewing the web pages using an eye tracker. By the analysis of eye movement data, we studied the influence of visual saliency and thinking way on eye-movement pattern. The analysis result showed that thinking way affect human’ eye-movement pattern much more than visual saliency. Second, we compared the results of web page visual salience region extracted by Itti model and Spectral Residual (SR) model. The results showed that Spectral Residual (SR) model performs superior than Itti model by comparison with the heat map from eye movements. Considering the influence of mind habit on humans’ visual region of interest, we introduced one of the most important cue in mind habit-fixation position to improved the SR model. The result showed that the improved SR model can better predict the human visual region of interest in web pages.

Keywords: web page salience region, eye-tracker, spectral residual, visual salience

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Authors: Ya-Ching Wang, Yi-Maun Subeq

Abstract:

Background: There is a lack of evidence to understand differences in risk for developing breast cancer between sexual minority women and heterosexual women in Taiwan. The purpose of this study is to compare differences in risk for developing breast cancer between the two groups of Taiwanese women. Methods: An online cross-sectional survey was used to collect data. A total of 238 Taiwanese women (mean age 30.69 years old, SD=8.231, range 20-60) were recruited between December 2016 and February 2017, including 115 heterosexual women and 123 sexual minority women. Results: There were no significant differences between heterosexual women and sexual minority women in body mass index, history of non-malignant breast disease, age at menarche and menopause, use of hormone replacement therapy, use of hormone replacement therapy, nor the prevalence of breast cancer. The sexual minority women had higher rates of current drinking, smoking and using breast-bindings and also reported exercise more a week; the heterosexual women had higher rates of pregnancy, children, breastfeed, miscarriages, abortion and use of birth control pills. Discussion/Conclusion: There were significant differences between heterosexual women and sexual minority women in reproductive factors and behavioral risk factors for the development of breast cancer. In particular, the finding that the sexual minority women had higher rate of using breast-bindings (56.6%) than the heterosexual women (4.7%) should be further explore, in order to understand whether long-term breast compression is associated with the development of breast cancer.

Keywords: breast cancer, risk, sexual orientation, Taiwan

Procedia PDF Downloads 365

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

Abstract:

For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

Procedia PDF Downloads 149

Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

Abstract:

Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

Procedia PDF Downloads 112

Authors: Shuang Qiu, Lingfeng Wang, Zhipeng Chen, Shijian Ge

Abstract:

Macroalgae are considered a promising approach for wastewater treatment as well as an alternative animal feed in addition to a biofuel feedstock. Their large size and/or tendency to grow as dense floating mats or substrate-attached turfs lead to lower separation and drying costs than microalgae. In this study, the macroalgae species Ulva lactuca (U. lactuca) were used to investigate their capacity for treating municipal wastewaters, and the feasibility of using the harvested biomass as an alternative food source for the fruitfly Drosophila melanogaster, an animal model for biological research. Results suggested that U. lactuca could successfully grow on three types of wastewaters studied with biomass productivities of 8.12-64.3 g DW (dry weight)/(m²∙d). The secondary wastewater (SW) was demonstrated as the most effective wastewater medium for U. lactuca growth. However, both high nitrogen (92.5-98.9%) and phosphorus (64.5-88.6%) removal efficiencies were observed in all wastewaters, particularly in primary wastewater (PW) and SW, however, in central wastewater (CW), the highest removal rates were obtained (N 24.7 ± 0.97 and P 0.69 ± 0.01 mg/(g DW·d)). Additionally, the inclusion of 20% washed U. lactuca with 80% standard fruitfly food (w/w) resulted in a longer lifespan and more stable body weights in flies. On the other hand, similar results were not obtained for the food treatment with the addition of 20 % unwashed U. lactuca. This study suggests a promising method for the macroalgae-based treatment of municipal wastewater and the biomass for animal feed.

Keywords: animal feed, flies, macroalgae, nutrient recovery, Ulva lactuca, wastewater

Procedia PDF Downloads 124

Authors: Yu-Ming Wang, Jia-Hong Jian

Abstract:

The Internet and digital publication technologies have brought dramatic impacts on how people collect, organize, disseminate, access, store, and use information. More and more governments, schools, and organizations spent huge funds to develop digital libraries. A digital library can be regarded as a web extension of traditional physically libraries. People can search diverse publications, find out the position of knowledge resources, and borrow or buy publications through digital libraries. People can gain knowledge and students or employees can finish their reports by using digital libraries. Since the considerable funds and energy have been invested in implementing digital libraries, it is important to understand the evaluative criteria from the users’ viewpoint in order to enhance user acceptance. This study develops a list of user acceptance criteria for digital libraries. An initial criteria list was developed based on some previously validated instruments related to digital libraries. Data were collected from user experiences of digital libraries. The exploratory factor analysis and confirmatory factor analysis were adopted to purify the criteria list. The reliabilities and validities were tested. After validating the criteria list, a user survey was conducted to collect the comparative importance of criteria. The analytic hierarchy process (AHP) method was utilized to derive the importance of each criterion. The results of this study contribute to an e understanding of the criteria and relative importance that users evaluate for digital libraries.

Keywords: digital library, user acceptance, analytic hierarchy process, factor analysis

Procedia PDF Downloads 253

Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

Abstract:

In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

Procedia PDF Downloads 304