Search results for: Liza L. S. Choi

Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Da Yoon Yu, Jeong A. Kim, In Sung Kim, Yeon Hee Hong, Jae Young Kim, Sang Suk Lee, Sung Chan Kim, So Hui Choe, In Soon Choi, Kwang Keun Cho

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The present study was conducted to identify the effects of synbiotics composed of lactic acid (LA) bacteria (LAB) and sea tangle on rat’s intestinal microorganisms and anti-obesity effects. The experiment was conducted for six weeks using an 8-week old male rat as experiment animals and the experimental design was to use six treatments groups of 4 repetitions using three mice per repetition. The treatment groups were organized into a normal fat diet control (NFC), a high fat (HF) diet control (HFC), a prebiotic 0% treatment (HF+LA+sea tangle 0%, ST0), a prebiotic 5% treatment (HF+LA+sea tangle 5%, ST5), a prebiotic 10% treatment (HF+LA+sea tangle 10%, ST10), and a prebiotic 15% treatment group (HF+LA+sea tangle 15%, ST15) to conduct experiments with various levels of prebiotics. According to the results of the experiment, the NFC group showed the highest daily weight gain (22.34g) and the ST0 group showed the lowest daily weight gain (19.41g). However, weight gains during the entire experimental period were the highest in the HFC group (475.73g) and the lowest in the ST0 group (454.23g). Feed efficiency was the highest in the HFC group (0.20). Treatment with synbiotics composed of LAB and sea tangle suppressed weight increases due to HF diet and reduced feed efficiency. Intestinal microorganisms were identified through pyrosequncing and according to the results, Firmicutes phylum (approximately 60%) and Bacteroidetes phylum (approximately 30%) accounted for approximately 90% or more of intestinal microorganisms in all of the treatment groups indicating these bacteria are dominating in the intestines. Firmicutes that is related to weight increases accounted for 64.96% of microorganisms in the NFC group, 75.32% in the HFC group, 59.51% in the ST0 group, 61.29% in the ST5 group, 49.91% in the ST10 group, and 39.65% in the ST15 group. Therefore, Firmicutes showed the highest share the HFC group that showed high weight gains and the lowest share in the group treated with mixed synbiotics composed of LAB and sea tangle. Bacteroidetes that is related to weight gain inhibition accounted for 32.12% of microorganisms in the NFC group, and HFC group 21.57%, ST0 group 37.66%, ST5 group 34.92%, ST10 group 44.46%, and ST15 group 53.22%. Therefore, the share of Bacteroidetes was the lowest in the HFC group with no addition of synbiotics and increased along with the level of treatment with synbiotics. Changes in blood components were not significantly different among the groups and SCFA yields were shown to be higher in groups treated with synbiotics than in groups not added with synbiotics. Through the present study, it was shown that the supply of synbiotics composed of LAB and sea tangle increased feed intake but led to weight losses and that the intake of synbiotics composed of LAB and sea tangle had anti-obesity effects due to decreases in Firmicutes which are microorganisms related to weight gains and increases in Bacteroidetes which are microorganisms related to weight losses. Therefore, synbiotics composed of LAB and sea tangle are considered to have the effect to prevent metabolic disorders in the rat.

Keywords: bacteroidetes, firmicutes, intestinal microbiota, lactic acid, sea tangle, synbiotics

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Authors: Jeong-Hyun Hong, Wonsuk Choi, Hyungdal Park, Jinseok Kim, Junesun Kim

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Identifying the chronic functions of an implanted neural electrode is an important factor in acquiring neural signals through the electrode or restoring the nerve functions after peripheral nerve injury. The purpose of this study was to investigate the biocompatibility of the chronic implanted neural electrode into the sciatic nerve. To do this, a sieve-type neural electrode was implanted at proximal and distal ends of a transected sciatic nerve as an experimental group (Sieve group, n=6), and the end-to-end epineural repair was operated with the cut sciatic nerve as a control group (reconstruction group, n=6). All surgeries were performed on the sciatic nerve of the right leg in Sprague Dawley rats. Behavioral tests were performed before and 1, 4, 7, 10, 14, and weekly days until 5 months following surgery. Changes in sensory function were assessed by measuring paw withdrawal responses to mechanical and cold stimuli. Motor function was assessed by motion analysis using a Qualisys program, which showed a range of motion (ROM) related to the joints. Neurofilament-heavy chain and fibronectin expression were detected 5 months after surgery. In both groups, the paw withdrawal response to mechanical stimuli was slightly decreased from 3 weeks after surgery and then significantly decreased at 6 weeks after surgery. The paw withdrawal response to cold stimuli was increased from 4 days following surgery in both groups and began to decrease from 6 weeks after surgery. The ROM of the ankle joint was showed a similar pattern in both groups. There was significantly increased from 1 day after surgery and then decreased from 4 days after surgery. Neurofilament-heavy chain expression was observed throughout the entire sciatic nerve tissues in both groups. Especially, the sieve group was showed several neurofilaments that passed through the channels of the sieve-type neural electrode. In the reconstruction group, however, a suture line was seen through neurofilament-heavy chain expression up to 5 months following surgery. In the reconstruction group, fibronectin was detected throughout the sciatic nerve. However, in the sieve group, the fibronectin was observed only in the surrounding nervous tissues of an implanted neural electrode. The present results demonstrated that the implanted sieve-type neural electrode induced a focal inflammatory response. However, the chronic implanted sieve-type neural electrodes did not cause any further inflammatory response following peripheral nerve injury, suggesting the possibility of the chronic application of the sieve-type neural electrodes. This work was supported by the Basic Science Research Program funded by the Ministry of Science (2016R1D1A1B03933986), and by the convergence technology development program for bionic arm (2017M3C1B2085303).

Keywords: biocompatibility, motor functions, neural electrodes, peripheral nerve injury, sensory functions

Procedia PDF Downloads 151

Authors: Soo-Yong Cho, Chong-Hyun Cho, Chae-Whan Rim, Sang-Kyu Choi, Jin-Gyun Kim, Ju-Seok Nam

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Recently, vertical axis wind turbines (VAWT) have been widely used to produce electricity even in urban. They have several merits such as low sound noise, easy installation of the generator and simple structure without yaw-control mechanism and so on. However, their blades are operated under the influence of the trailing vortices generated by the preceding blades. This phenomenon deteriorates its output power and makes difficulty predicting correctly its performance. In order to improve the performance of VAWT, wind power towers can be applied. Usually, the wind power tower can be constructed as a multi-story building to increase the frontal area of the wind stream. Hence, multiple sets of the VAWT can be installed within the wind power tower, and they can be operated at high elevation. Many different types of wind power tower can be used in the field. In this study, a wind power tower with circular column shape was applied, and the VAWT was installed at the center of the wind power tower. Seven guide walls were used as a strut between the floors of the wind power tower. These guide walls were utilized not only to increase the wind velocity within the wind power tower but also to adjust the wind direction for making a better working condition on the VAWT. Hence, some important design variables, such as the distance between the wind turbine and the guide wall, the outer diameter of the wind power tower, the direction of the guide wall against the wind direction, should be considered to enhance the output power on the VAWT. A numerical analysis was conducted to find the optimum dimension on design variables by using the computational fluid dynamics (CFD) among many prediction methods. The CFD could be an accurate prediction method compared with the stream-tube methods. In order to obtain the accurate results in the CFD, it needs the transient analysis and the full three-dimensional (3-D) computation. However, this full 3-D CFD could be hard to be a practical tool because it requires huge computation time. Therefore, the reduced computational domain is applied as a practical method. In this study, the computations were conducted in the reduced computational domain and they were compared with the experimental results in the literature. It was examined the mechanism of the difference between the experimental results and the computational results. The computed results showed this computational method could be an effective method in the design methodology using the optimization algorithm. After validation of the numerical method, the CFD on the wind power tower was conducted with the important design variables affecting the performance of VAWT. The results showed that the output power of the VAWT obtained using the wind power tower was increased compared to them obtained without the wind power tower. In addition, they showed that the increased output power on the wind turbine depended greatly on the dimension of the guide wall.

Keywords: CFD, performance, VAWT, wind power tower

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Authors: Min Koo Choi

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The paper will examine Im Sun-dŭk’s two short stories, 'Iryoil' (Sunday, 1937) and 'Nazuoya' (A Godmother, 1942), which illuminate the subjects of Korean intellectuals going through the later period of a harsh and oppressive Japanese colonial rule. When Japan went to war against China in 1937, Korea, a colony of Japan since 1910, became an outpost for Japanese expansionism into China, and the Korean people were mobilized into the war effort. Nationalist movements and radical ideas that posed a threat and opposition to Japanese colonial rule in Korea and its colonial expansionism were ruthlessly suppressed, and Koreans were forcibly assimilated into becoming Japanese citizens without political rights. Racial discrimination between Koreans and Japanese was prevalent. Im Sun-dŭk, who participated in the Socialist movement in the 1930s, had his debut as a literary writer and a critic in the late 1930s, when Korean literary society was reincorporated in order to collaborate with the Japanese war effort through writing and public speech. Sun-duk's writing illuminates the unique internal landscape of a female subject who strives to live on while preserving her commitment and dignity under the circumstances that force Korean intellectuals either to collaborate with or acquiesce to Japanese colonial rule. 'Iryoil' (Sunday, 1937) foregrounds an educated intellectual, Hyeyŏng, who supplies her fiancé in prison for political involvement in resistance against Japan. On Sundays, she turns down her friends’ suggestion for enjoying holidays outside, due to her indebtedness to her fiancé. Her fiancé's imprisonment indicates the social conscience that still remains, and she seeks to share the commitment and suffering with her fiancé. The short story 'Nazuoya' (A Godmother, 1942), written in Japanese due to the suppression of Korean language publications at the time, also problematizes Japanese policy that forces Koreans to change their names into Japanese. Through the narrator I, who struggles to find a meaningful name for her cousin brother’s baby, she highlights how meaningful one’s name is for one’s life and identity. What makes her two stories unique is that her writing draws other people’s confessions into its own narrative through fragmentary forms, such as part of letter or reflection. The voices of others are intersected with the main character in 'Iryoil' (Sunday, 1937) and a narrator in 'Nazuoya' (A Godmother, 1942). In many ways, the narrator and main character provide the confessional voices who display the characters' gloomy interiorities. Even though these confessional voices do not share the commitment and values, both the main character and I in the stories reveal a more open set of viewpoints to them. In this way, they seek to form bonds and encouragement and acquire a more resilient sensibility that embraces those who strive to survive and endure in the gloomy days of the later period of Japanese colonial rule.

Keywords: Im Sun-dŭk, Japanese colonial rule, Korean literature, socialist movement

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Authors: Hyomin Lee, Jinhyun Lee, Jinyeon Hwang, Younghoon Choi, Byeongseo Son

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Global warming is a world-wide issue. Various carbon capture and storage (CCS) technologies for reducing CO2 concentration in the atmosphere have been increasingly studied. Mineral carbonation is one of promising method for CO2 sequestration. Waste cement generating from aggregate recycling processes of waste concrete is potentially a good raw material containing reactive components for mineral carbonation. The major goal of our long-term project is to developed effective methods for CO2 sequestration using waste cement. In the present study, the carbonation characteristics of hydrated cement were examined by conducting two different direct aqueous carbonation experiments. We also evaluate the influence of NaCl and MgCl2 as additives to increase mineral carbonation efficiency of hydrated cement. Cement paste was made with W:C= 6:4 and stored for 28 days in water bath. The prepared cement paste was pulverized to the size less than 0.15 mm. 15 g of pulverized cement paste and 200 ml of solutions containing additives were reacted in ambient temperature and pressure conditions. 1M NaCl and 0.25 M MgCl2 was selected for additives after leaching test. Two different sources of CO2 was applied for direct aqueous carbonation experiment: 0.64 M NaHCO3 was used for CO2 donor in method 1 and pure CO2 gas (99.9%) was bubbling into reacting solution at the flow rate of 20 ml/min in method 2. The pH and Ca ion concentration were continuously measured with pH/ISE Multiparameter to observe carbonation behaviors. Material characterization of reacted solids was performed by TGA, XRD, SEM/EDS analyses. The carbonation characteristics of hydrated cement were significantly different with additives. Calcite was a dominant calcium carbonate mineral after the two carbonation experiments with no additive and NaCl additive. The significant amount of aragonite and vaterite as well as very fine calcite of poorer crystallinity was formed with MgCl2 additive. CSH (calcium silicate hydrate) in hydrated cement were changed to MSH (magnesium silicate hydrate). This transformation contributed to the high carbonation efficiency. Carbonation experiment with method 1 revealed that that the carbonation of hydrated cement took relatively long time in MgCl2 solution compared to that in NaCl solution and the contents of aragonite and vaterite were increased as increasing reaction time. In order to maximize carbonation efficiency in direct aqueous carbonation with CO2 gas injection (method 2), the control of solution pH was important. The solution pH was decreased with injection of CO2 gas. Therefore, the carbonation efficiency in direct aqueous carbonation was closely related to the stability of calcium carbonate minerals with pH changes. With no additive and NaCl additive, the maximum carbonation was achieved when the solution pH was greater than 11. Calcium carbonate form by mineral carbonation seemed to be re-dissolved as pH decreased below 11 with continuous CO2 gas injection. The type of calcium carbonate mineral formed during carbonation in MgCl2 solution was closely related to the variation of solution pH caused by CO2 gas injection. The amount of aragonite significantly increased with decreasing solution pH, whereas the amount of calcite decreased.

Keywords: CO2 sequestration, Mineral carbonation, Cement and concrete, MgCl2 and NaCl

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Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

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The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

Procedia PDF Downloads 233

Authors: Carmen W. H. Chan, Helen Y. L. Chan, Kai Chow Choi, Ka Ming Chow, Cecilia W. M. Kwan, Nancy H. Y. Ng, Jackie Robinson

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Introduction: In Hong Kong, a significant number of deaths occur in acute care wards, which requires nurses in these settings to provide end-of-life care and lead ACP implementation. However, nurses in these settings, in fact, have very low-level involvement in ACP discussions because of limited training in ACP conversations. Objective: This study aims to assess the impact of a multi-media experiential ACP (MEACP) training program, which is guided by the experiential learning model and theory of planned behaviour, on nurses' knowledge and confidence in assisting patients with ACP. Methodology: The study utilizes a cluster randomized controlled trial with a 12-week follow-up. Eligible nurses working in acute care hospital wards are randomly assigned at the ward level, in a 1:1 ratio, to either the control group (no ACP education) or the intervention group (4-week MEACP training program). The training programme includes training through a webpage and mobile application, as well as a face-to-face training workshop with enhanced lectures and role play, which is based on the Theory of Planned Behavior and Kolb's Experiential Learning Model. Questionnaires were distributed to assess nurses' knowledge (a 10-item true/false questionnaire) and level of confidence (five-point Likert scale) in ACP at baseline (T0), four weeks after the baseline assessment (T1), and 12 weeks after T1 (T2). In this interim report, data analysis was mainly descriptive in nature. Result: The interim report focuses on the preliminary results of 165 nurses at T0 (Control: 74, Intervention: 91) over a 5-month period, 69 nurses from the control group who completed the 4-week follow-up and 65 nurses from the intervention group who completed the 4-week MEACP training program at T1. The preliminary attrition rate is 6.8% and 28.6% for the control and intervention groups, respectively, as some nurses did not complete the whole set of online modules. At baseline, the two groups were generally homogeneous in terms of their years of nursing practice, weekly working hours, working title, and level of education, as well as ACP knowledge and confidence levels. The proportion of nurses who answered all ten knowledge questions correctly increased from 13.8% (T0) to 66.2% (T1) for the intervention group and from 13% (T0) to 20.3% (T1) for the control group. The nurses in the intervention group answered an average of 7.57 and 9.43 questions correctly at T0 and T1, respectively. They showed a greater improvement in the knowledge assessment at T1 with respect to T0 when compared with their counterparts in the control group (mean difference of change score, Δ=1.22). They also exhibited a greater gain in level of confidence at T1 compared to their colleagues in the control group (Δ=0.91). T2 data is yet available. Conclusion: The prevalence of nurses engaging in ACP and their level of knowledge about ACP in Hong Kong is low. The MEACP training program can enrich nurses by providing them with more knowledge about ACP and increasing their confidence in conducting ACP.

Keywords: advance directive, advance care planning, confidence, knowledge, multi-media experiential, randomised control trial

Procedia PDF Downloads 77

Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

Abstract:

Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Hyemi Kim, Jay Kim, Kyunghoon Han, Ra-Yeong Choi, In-Woo Kim, Hyung Joo Suh, Ki-Bae Hong, Sung Hee Han

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Chitosan is used in various industries such as food and medical care because it is known to have various functions such as anti-obesity, anti-inflammatory and anti-cancer benefits. Most of the commercial chitosan is extracted from crustaceans. As the harvest rate of snow crabs and red snow crabs decreases and safety issues arise due to environmental pollution, research is underway to extract chitosan from insects. In this study, we used Response Surface Methodology (RSM) to predict the optimal conditions to produce chitosan oligosaccharides from mealworms (MCOS), which can be absorbed through the intestine as low-molecular-weight chitosan. The experimentally confirmed optimal conditions for MCOS production using chitosanase were found to be a substrate concentration of 2.5%, enzyme addition of 30 mg/g and a reaction time of 6 hours. The chemical structure and physicochemical properties of the produced MCOS were measured using MALDI-TOF mass spectra and FTIR spectra. The MALDI-TOF mass spectra revealed peaks corresponding to the dimer (375.045), trimer (525.214), tetramer (693.243), pentamer (826.296), and hexamer (987.360). In the FTIR spectra, commercial chitosan oligosaccharides exhibited a weak peak pattern at 3500-2500 cm-1, unlike chitosan or chitosan oligosaccharides. There was a difference in the peak at 3200~3500 cm-1, where different vibrations corresponding to OH and amine groups overlapped. Chitosan, chitosan oligosaccharide, and commercial chitosan oligosaccharide showed peaks at 2849, 2884, and 2885 cm-1, respectively, attributed to the absorption of the C-H stretching vibration of methyl or methine. The amide I, amide II, and amide III bands of chitosan, chitosan oligosaccharide, and commercial chitosan oligosaccharide exhibited peaks at 1620/1620/1602, 1553/1555/1505, and 1310/1309/1317 cm-1, respectively. Furthermore, the solubility of MCOS was 45.15±3.43, water binding capacity (WBC) was 299.25±4.57, and fat binding capacity (FBC) was 325.61±2.28 and the solubility of commercial chitosan oligosaccharides was 49.04±9.52, WBC was 280.55±0.50, and FBC was 157.22±18.15. Thus, the characteristics of MCOS and commercial chitosan oligosaccharides are similar. The results of investigating the impact of chitosan oligosaccharide on the proliferation of probiotics revealed increased growth in L. casei, L. acidophilus, and Bif. Bifidum. Therefore, the major short-chain fatty acids produced by gut microorganisms, such as acetic acid, propionic acid, and butyric acid, increased within 24 hours of adding 1% (p<0.01) and 2% (p<0.001) MCOS. The impact of MCOS on the overall gut microbiota was assessed, revealing that the Chao1 index did not show significant differences, but the Simpson index decreased in a concentration-dependent manner, indicating a higher species diversity. The addition of MCOS resulted in changes in the overall microbial composition, with an increase in Firmicutes and Verrucomicrobia (p<0.05) compared to the control group, while Proteobacteria and Actinobacteria (p<0.05) decreased. At the genus level, changes in microbiota due to MCOS supplementation showed an increase in beneficial bacteria like lactobacillus, Romboutsia, Turicibacter, and Akkermansia (p<0.0001) while harmful bacteria like Enterococcus, Morganella, Proterus, and Bacteroides (p<0.0001) decreased. In this study, chitosan oligosaccharides were successfully produced under established conditions from mealworms, and these chitosan oligosaccharides are expected to have prebiotic effects, similar to those obtained from crabs.

Keywords: mealworms, chitosan, chitosan oligosaccharide, prebiotics

Procedia PDF Downloads 64

Authors: Imdad Ullah Khan, Yongseok Yoon, Kyeung Uk Choi, Kwang Rae Jo, Namyul Kim, Eunbee Lee, Wan Hee Kim, Oh-Kyeong Kweon

Abstract:

The primary spinal cord injury (SCI) causes mechanical damage to the neurons and blood vessels. It leads to secondary SCI, which activates multiple pathological pathways, which expand neuronal damage at the injury site. It is characterized by vascular disruption, ischemia, excitotoxicity, oxidation, inflammation, and apoptotic cell death. It causes nerve demyelination and disruption of axons, which perpetuate a loss of impulse conduction through the injured spinal cord. It also leads to the production of myelin inhibitory molecules, which with a concomitant formation of an astroglial scar, impede axonal regeneration. The pivotal role regarding the neuronal necrosis is played by oxidation and inflammation. During an early stage of spinal cord injury, there occurs an abundant expression of reactive oxygen species (ROS) due to defective mitochondrial metabolism and abundant migration of phagocytes (macrophages, neutrophils). ROS cause lipid peroxidation of the cell membrane, and cell death. Abundant migration of neutrophils, macrophages, and lymphocytes collectively produce pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1beta (IL-1β), matrix metalloproteinase, superoxide dismutase, and myeloperoxidases which synergize neuronal apoptosis. Therefore, it is crucial to control inflammation and oxidation injury to minimize the nerve cell death during secondary spinal cord injury. Therefore, in response to oxidation and inflammation, heme oxygenase-1 (HO-1) is induced by the resident cells to ameliorate the milieu. In the meanwhile, neurotrophic factors are induced to promote neuroregeneration. However, it seems that anti-stress enzyme (HO-1) and neurotrophic factor (BDNF) do not significantly combat the pathological events during secondary spinal cord injury. Therefore, optimum healing can be induced if anti-inflammatory and neurotrophic factors are administered in a higher amount through an exogenous source. During the first experiment, the inflammation and neuroregeneration were selectively targeted. HO-1 expressing MSCs (HO-1 MSCs) and BDNF expressing MSCs (BDNF MSC) were co-transplanted in one group (combination group) of dogs with subacute spinal cord injury to selectively control the expression of inflammatory cytokines by HO-1 and induce neuroregeneration by BDNF. We compared the combination group with the HO-1 MSCs group, BDNF MSCs group, and GFP MSCs group. We found that the combination group showed significant improvement in functional recovery. It showed increased expression of neural markers and growth-associated proteins (GAP-43) than in other groups, which depicts enhanced neuroregeneration/neural sparing due to reduced expression of pro-inflammatory cytokines such as TNF-alpha, IL-6 and COX-2; and increased expression of anti-inflammatory markers such as IL-10 and HO-1. Histopathological study revealed reduced intra-parenchymal fibrosis in the injured spinal cord segment in the combination group than in other groups. Thus it was concluded that selectively targeting the inflammation and neuronal growth with the combined use of HO-1 MSCs and BDNF MSCs more favorably promote healing of the SCI. HO-1 MSCs play a role in controlling the inflammation, which favors the BDNF induced neuroregeneration at the injured spinal cord segment of dogs.

Keywords: HO-1 MSCs, BDNF MSCs, neuroregeneration, inflammation, anti-inflammation, spinal cord injury, dogs

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Authors: Carles Martinez-Almoyna Gual, Jiwon Choi

Abstract:

Urban communities face risks of disintegration and segregation as a consequence of globalised migration processes towards urban environments. Linking social and cultural components with environmental and economic dimensions becomes the goal of all the disciplines that aim to shape more sustainable urban environments. Solutions require interdisciplinary approaches and the use of a complex array of tools. One of these tools is the implementation of urban farming, which provides a wide range of advantages for creating more inclusive spaces and integrated communities. Since food is strongly related to the values and identities of any cultural group, it can be used as a medium to promote social inclusion in the context of urban multicultural societies. By bringing people together into specific urban sites, food production can be integrated into multifunctional spaces while addressing social, economic and ecological goals. The goal of this research is to assess different approaches to urban agriculture by analysing three existing community gardens located in Newtown, a suburb of Wellington, New Zealand. As a context for developing research, Newtown offers different approaches to urban farming and is really valuable for observing current trends of socialization in diverse and multicultural societies. All three spaces are located on public land owned by Wellington City Council and confined to a small, complex and progressively denser urban area. The developed analysis was focused on social, cultural and physical dimensions, combining community engagement with different techniques of spatial assessment. At the same time, a detailed investigation of each community garden was conducted with comparative analysis methodologies. This multidirectional setting of the analysis was established for extracting from the case studies both specific and typological knowledge. Each site was analysed and categorised under three broad themes: people, space and food. The analysis revealed that all three case studies had really different spatial settings, different approaches to food production and varying profiles of supportive communities. The main differences identified were demographics, values, objectives, internal organization, appropriation, and perception of the space. The community gardens were approached as case studies for developing design research. Following participatory design processes with the different communities, the knowledge gained from the analysis was used for proposing changes in the physical environment. The end goal of the design research was to improve the capacity of the spaces to facilitate social inclusiveness. In order to generate tangible changes, a range of small, strategic and feasible spatial interventions was explored. The smallness of the proposed interventions facilitates implementation by reducing time frames, technical resources, funding needs, and legal processes, working within the community´s own realm. These small interventions are expected to be implemented over time as part of an ongoing collaboration between the different communities, the university, and the local council. The applied research methodology showcases the capacity of universities to develop civic engagement by working with real communities that have concrete needs and face overall threats of disintegration and segregation.

Keywords: community gardening, landscape architecture, participatory design, placemaking, social inclusion

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

Abstract:

Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

Procedia PDF Downloads 190