Search results for: Jia-Ming Chen

Authors: Chia-Chen Wu, Chih-Fu Wu, Pey-Weng Lien, Kai-Chieh Lin

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In the past, the most comprehensively adopted light source was incandescent light bulbs, but with the appearance of LED light sources, traditional light sources have been gradually replaced by LEDs because of its numerous superior characteristics. However, many of the standards do not apply to LEDs as the two light sources are characterized differently. This also intensifies the significance of studies on LEDs. As a Kansei design study investigating the visual glare produced by traffic arrows implemented with LEDs, this study conducted a semantic analysis on the styles of traffic arrows used in domestic and international occasions. The results will be able to reduce drivers’ misrecognition that results in the unsuccessful arrival at the destination, or in traffic accidents. This study started with a literature review and surveyed the status quo before conducting experiments that were divided in two parts. The first part involved a screening experiment of arrow samples, where cluster analysis was conducted to choose five representative samples of LED displays. The second part was a semantic experiment on the display of arrows using LEDs, where the five representative samples and the selected ten adjectives were incorporated. Analyzing the results with Quantification Theory Type I, it was found that among the composition of arrows, fletching was the most significant factor that influenced the adjectives. In contrast, a “no fletching” design was more abstract and vague. It lacked the ability to convey the intended message and might bear psychological negative connotation including “dangerous,” “forbidden,” and “unreliable.” The arrow design consisting of “> shaped fletching” was found to be more concrete and definite, showing positive connotation including “safe,” “cautious,” and “reliable.” When a stimulus was placed at a farther distance, the glare could be significantly reduced; moreover, the visual evaluation scores would be higher. On the contrary, if the fletching and the shaft had a similar proportion, looking at the stimuli caused higher evaluation at a closer distance. The above results will be able to be applied to the design of traffic arrows by conveying information definitely and rapidly. In addition, drivers’ safety could be enhanced by understanding the cause of glare and improving visual recognizability.

Keywords: LED, arrow, Kansei research, preferred imagery.

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Authors: Han-Mei Chen, Rongxin Zhou, Taige Wang

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Glass is widely used in everyday life, from glass bottles for beverages, to architectural glass for various forms of glazing. Although the mainstream of used glass is recycled in the UK, the single-use and then recycling procedure results in a lot of waste as it incorporates intact glass with smashing, re-melting and remanufacturing. These processes bring massive energy consumption with a huge loss of high embodied energy and economic value, compared to re-use which’s towards a ‘zero carbon’ target. As a tourism city, Liverpool has more glass bottle consumption than most less leisure focused cities. It is therefore vital for Liverpool to find an upgrading approach for the single-use glass bottles with a low carbon output. This project aims to assess the feasibility of an industrial symbiosis and upgrading framework of glass and to investigate the ways of achieving them. It is significant to Liverpool’s future industry strategy since it provides an opportunity to target on economy recovery for post-COVID by industry symbiosis and an up-grading waste management in Liverpool to respond to the climate emergency. In addition, it will influence the local government policy for glass bottle reuse and recycling in North West England, and as a good practice to be further recommended to other areas of the UK. First, critical literature review of glass waste strategies has been conducted in the UK, and world-wide industrial symbiosis practices. Second, mapping, data collection and analysis have shown the current life cycle chain and the strong links of glass reuse and upgrading potentials via site visits to 16 local waste recycling centres. The results of this research have demonstrated the understanding the influence of key factors on the development of a circular industrial symbiosis business model for beverage glass bottles. The current waste management procedures of glass bottle industry, its business model, supply chain and the material flow have been reviewed. The various potential opportunities for glass bottle up-valuing have been investigated towards an industrial symbiosis in Liverpool. Finally, an up-valuing business model has been developed for an industrial symbiosis framework of glass in Liverpool. For glass bottles, there are two possibilities: 1) focus on upgrading processes towards re-use rather than single-use and recycling, 2) focus on ‘smart’ re-use and recycling leading to optimised values in other sectors to create a wider industry symbiosis for a multi-level and circular economy.

Keywords: Glass bottles, industry symbiosis, smart reuse, waste upgrading.

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: Crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest.

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Authors: Ali Zaker, Zhi Chen

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Due to the concerns about the depletion of fossil fuel sources and the deteriorating environment, the attempt to investigate the production of renewable energy will play a crucial role as a potential to alleviate the dependency on mineral fuels. One particular area of interest is generation of bio-oil through sewage sludge (SS) pyrolysis. SS can be a potential candidate in contrast to other types of biomasses due to its availability and low cost. However, the presence of high molecular weight hydrocarbons and oxygenated compounds in the SS bio-oil hinders some of its fuel applications. In this context, catalytic pyrolysis is another attainable route to upgrade bio-oil quality. Among different catalysts (i.e., zeolites) studied for SS pyrolysis, activated chars (AC) are eco-friendly alternatives. The beneficial features of AC derived from SS comprise the comparatively large surface area, porosity, enriched surface functional groups and presence of a high amount of metal species that can improve the catalytic activity. Hence, a sludge-based AC catalyst was fabricated in a single-step pyrolysis reaction with NaOH as the activation agent and was compared with HZSM5 zeolite in this study. The thermal decomposition and kinetics were invested via thermogravimetric analysis (TGA) for guidance and control of pyrolysis and catalytic pyrolysis and the design of the pyrolysis setup. The results indicated that the pyrolysis and catalytic pyrolysis contain four obvious stages and the main decomposition reaction occurred in the range of 200-600 °C. Coats-Redfern method was applied in the 2nd and 3rd devolatilization stages to estimate the reaction order and activation energy (E) from the mass loss data. The average activation energy (Em) values for the reaction orders n = 1, 2 and 3 were in the range of 6.67-20.37 kJ/mol for SS; 1.51-6.87 kJ/mol for HZSM5; and 2.29-9.17 kJ/mol for AC, respectively. According to the results, AC and HZSM5 both were able to improve the reaction rate of SS pyrolysis by abridging the Em value. Moreover, to generate and examine the effect of the catalysts on the quality of bio-oil, a fixed-bed pyrolysis system was designed and implemented. The composition analysis of the produced bio-oil was carried out via gas chromatography/mass spectrometry (GC/MS). The selected SS to catalyst ratios were 1:1, 2:1 and 4:1. The optimum ratio in terms of cracking the long-chain hydrocarbons and removing oxygen-containing compounds was 1:1 for both catalysts. The upgraded bio-oils with HZSM5 and AC were in the total range of C4-C17 with around 72% in the range of C4-C9. The bio-oil from pyrolysis of SS contained 49.27% oxygenated compounds while the presence of HZSM5 and AC dropped to 7.3% and 13.02%, respectively. Meanwhile, generation of value-added chemicals such as light aromatic compounds were significantly improved in the catalytic process. Furthermore, the fabricated AC catalyst was characterized by BET, SEM-EDX, FT-IR and TGA techniques. Overall, this research demonstrated that AC is an efficient catalyst in the pyrolysis of SS and can be used as a cost-competitive catalyst in contrast to HZSM5.

Keywords: Activated char, bio-oil, catalytic pyrolysis, HZSM5, sewage sludge.

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Authors: Ren-Jy Ben, Jo-Chi Jao, Chiu-Ya Liao, Ya-Ru Tsai, Lain-Chyr Hwang, Po-Chou Chen

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Cancer is still one of the serious diseases threatening the lives of human beings. How to have an early diagnosis and effective treatment for tumors is a very important issue. The animal carcinoma model can provide a simulation tool for the studies of pathogenesis, biological characteristics, and therapeutic effects. Recently, drug delivery systems have been rapidly developed to effectively improve the therapeutic effects. Liposome plays an increasingly important role in clinical diagnosis and therapy for delivering a pharmaceutic or contrast agent to the targeted sites. Liposome can be absorbed and excreted by the human body, and is well known that no harm to the human body. This study aimed to compare the therapeutic effects between encapsulated (doxorubicin liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox) anti-tumor drugs using magnetic resonance imaging (MRI). Twenty-four New Zealand rabbits implanted with VX2 carcinoma at left thighs were classified into three groups: control group (untreated), Dox-treated group, and LipoDox-treated group, 8 rabbits for each group. MRI scans were performed three days after tumor implantation. A 1.5T GE Signa HDxt whole body MRI scanner with a high resolution knee coil was used in this study. After a 3-plane localizer scan was performed, three-dimensional (3D) fast spin echo (FSE) T2-weighted Images (T2WI) was used for tumor volumetric quantification. Afterwards, two-dimensional (2D) spoiled gradient recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was used for tumor perfusion evaluation. DCE-MRI was designed to acquire four baseline images, followed by contrast agent Gd-DOTA injection through the ear vein of rabbit. A series of 32 images were acquired to observe the signals change over time in the tumor and muscle. The MRI scanning was scheduled on a weekly basis for a period of four weeks to observe the tumor progression longitudinally. The Dox and LipoDox treatments were prescribed 3 times in the first week immediately after the first MRI scan; i.e. 3 days after VX2 tumor implantation. ImageJ was used to quantitate tumor volume and time course signal enhancement on DCE images. The changes of tumor size showed that the growth of VX2 tumors was effectively inhibited for both LipoDox-treated and Dox-treated groups. Furthermore, the tumor volume of LipoDox-treated group was significantly lower than that of Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is significantly lower than that of the other two groups, which implies that targeted therapeutic drug remained in the tumor tissue. This study provides a radiation-free and non-invasive MRI method for therapeutic monitoring of targeted liposome on an animal tumor model.

Keywords: Doxorubicin, dynamic contrast-enhanced MRI, lipodox, magnetic resonance imaging, VX2 tumor model.

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Authors: Delphine Mukaneza, Lin Qiao, Wang Pengxin, Li Yan, Chen Yingyi

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Human activities on land use make the land-cover gradually change or transit. In this study, we examined the use of Landsat TM data to detect the land use change of Kigali between 1987 and 2009 using remote sensing techniques and analysis of data using ENVI and ArcGIS, a GIS software. Six different categories of land use were distinguished: bare soil, built up land, wetland, water, vegetation, and others. With remote sensing techniques, we analyzed land use data in 1987, 1999 and 2009, changed areas were found and a dynamic situation of land use in Kigali city was found during the 22 years studied. According to relevant Landsat data, the research focused on land use change in accordance with the role of remote sensing in the process of urbanization. The result of the work has shown the rapid increase of built up land between 1987 and 1999 and a big decrease of vegetation caused by the rebuild of the city after the 1994 genocide, while in the period of 1999 to 2009 there was a reduction in built up land and vegetation, after the authority of Kigali city established, a Master Plan where all constructions which were not in the range of the master Plan were destroyed. Rwanda's capital, Kigali City, through the expansion of the urban area, it is increasing the internal employment rate and attracts business investors and the service sector to improve their economy, which will increase the population growth and provide a better life. The overall planning of the city of Kigali considers the environment, land use, infrastructure, cultural and socio-economic factors, the economic development and population forecast, urban development, and constraints specification. To achieve the above purpose, the Government has set for the overall planning of city Kigali, different stages of the detailed description of the design, strategy and action plan that would guide Kigali planners and members of the public in the future to have more detailed regional plans and practical measures. Thus, land use change is significantly the performance of Kigali active human area, which plays an important role for the country to take certain decisions. Another area to take into account is the natural situation of Kigali city. Agriculture in the region does not occupy a dominant position, and with the population growth and socio-economic development, the construction area will gradually rise and speed up the process of urbanization. Thus, as a developing country, Rwanda's population continues to grow and there is low rate of utilization of land, where urbanization remains low. As mentioned earlier, the 1994 genocide massacres, population growth and urbanization processes, have been the factors driving the dramatic changes in land use. The focus on further research would be on analysis of Rwanda’s natural resources, social and economic factors that could be, the driving force of land use change.

Keywords: Land use change, urbanization, Kigali City, Landsat.

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Authors: Chau-Kuang Chen, Juanita Buford, Colette Davis, Raisha Allen, John Hughes, Jr., James Tyus, Dexter Samuels

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During the post-Civil War era, the city of Nashville, Tennessee, had the highest mortality rate in the United States. The elevated death and disease rates among former slaves were attributable to lack of quality healthcare. To address the paucity of healthcare services, Meharry Medical College, an institution with the mission of educating minority professionals and serving the underserved population, was established in 1876. Purpose: The social ecological framework and partial least squares (PLS) path modeling were used to quantify the impact of socioeconomic status and adverse health outcome on primary care professionals serving the disadvantaged community. Thus, the study results could demonstrate the accomplishment of the College’s mission of training primary care professionals to serve in underserved areas. Methods: Various statistical methods were used to analyze alumni data from 1975 – 2013. K-means cluster analysis was utilized to identify individual medical and dental graduates in the cluster groups of the practice communities (Disadvantaged or Non-disadvantaged Communities). Discriminant analysis was implemented to verify the classification accuracy of cluster analysis. The independent t-test was performed to detect the significant mean differences of respective clustering and criterion variables. Chi-square test was used to test if the proportions of primary care and non-primary care specialists are consistent with those of medical and dental graduates practicing in the designated community clusters. Finally, the PLS path model was constructed to explore the construct validity of analytic model by providing the magnitude effects of socioeconomic status and adverse health outcome on primary care professionals serving the disadvantaged community. Results: Approximately 83% (3,192/3,864) of Meharry Medical College’s medical and dental graduates from 1975 to 2013 were practicing in disadvantaged communities. Independent t-test confirmed the content validity of the cluster analysis model. Also, the PLS path modeling demonstrated that alumni served as primary care professionals in communities with significantly lower socioeconomic status and higher adverse health outcome (p < .001). The PLS path modeling exhibited the meaningful interrelation between primary care professionals practicing communities and surrounding environments (socioeconomic statues and adverse health outcome), which yielded model reliability, validity, and applicability. Conclusion: This study applied social ecological theory and analytic modeling approaches to assess the attainment of Meharry Medical College’s mission of training primary care professionals to serve in underserved areas, particularly in communities with low socioeconomic status and high rates of adverse health outcomes. In summary, the majority of medical and dental graduates from Meharry Medical College provided primary care services to disadvantaged communities with low socioeconomic status and high adverse health outcome, which demonstrated that Meharry Medical College has fulfilled its mission. The high reliability, validity, and applicability of this model imply that it could be replicated for comparable universities and colleges elsewhere.

Keywords: Disadvantaged Community, K-means Cluster Analysis, PLS Path Modeling, Primary care.

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