Search results for: combined capture

Authors: Flex Anim

Abstract:

The financial system is a decentralized studies system that was put into place in Ghana as a grassroots financial studies approach. Its main goal is to give people the precise knowledge, abilities, and training required for a given trade, business, profession, or occupation. In this essay, the question of how the financial studies system's devolution to local businesses results in responsible and responsive representation as well as long-term company learning is raised. It centers on two case studies, Asekwa Municipal and Oforikrom. The next question posed by the study is how senior high school students are rebuilding their livelihoods and socioeconomic well-being by creating new curriculum and social practices related to the finance and business studies system. The paper here concentrates on Kumasi District and makes inferences for the other two examples. The paper demonstrates how the financial studies system's establishment of representative groups creates the democratic space required for the successful representation of community goals. Nonetheless, the interests of a privileged few are advanced as a result of elite capture. The state's financial and business training programs do not adhere to the financial studies system's established policy procedures and do not transfer pertinent and discretionary resources to local educators. As a result, local educators are unable to encourage representation that is accountable and responsive. The financial studies system continues to pique the interest of rural areas, but this desire is skewed toward getting access to financial or business training institutions for higher education. Since the locals are not actively involved in financial education, the financial studies system serves just to advance the interests of specific populations. This article explains how rhetoric and personal benefits can be supported by the public even in the case of "failed" interventions.

Keywords: financial studies system, financial studies' devolution, local government, senior high schools and financial education, as well as community goals and representation

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Authors: V. Veena, Suguna Yesodharan, E. P. Yesodharan

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Two Advanced Oxidation Processes (AOP) i.e., sono- and photo-catalysis mediated by semiconductor oxide catalyst, ZnO has been found effective for the removal of trace amounts of the toxic dye pollutant Indigocarmine (IC) from water. The effect of various reaction parameters such as concentration of the dye, catalyst dosage, temperature, pH, dissolved oxygen etc. as well as the addition of oxidisers and presence of salts in water on the rate of degradation has been evaluated and optimised. The degradation follows variable kinetics depending on the concentration of the substrate, the order of reaction varying from 1 to 0 with increase in concentration. The reaction proceeds through a number of intermediates and many of them have been identified using GCMS technique. The intermediates do not affect the rate of degradation significantly. The influence of anions such as chloride, sulphate, fluoride, carbonate, bicarbonate, phosphate etc. on the degradation of IC is not consistent and does not follow any predictable pattern. Phosphates and fluorides inhibit the degradation while chloride, sulphate, carbonate and bicarbonate enhance. Adsorption studies of the dye in the absence as well as presence of these anions show that there may not be any direct correlation between the adsorption of the dye on the catalyst and the degradation. Oxidants such as hydrogen peroxide and persulphate enhance the degradation though the combined effect and it is less than the cumulative effect of individual components. COD measurements show that the degradation proceeds to complete mineralisation. The results will be presented and probable mechanism for the degradation will be discussed.

Keywords: AOP, COD, indigocarmine, photocatalysis, sonocatalysis

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Authors: Claire Song

Abstract:

Background: TikTok is an emerging social media platform creating an outlet for nurses to express and communicate their nursing experiences and stress related to nursing. Purpose: This study investigates the lived experiences of nursing burnout shared on TikTok. Method: The cross-sectional content analysis examines the video content, format, type, and quantitative indicators, including the number of likes and comments. Results: A total of 35 videos and 18616 comments were examined, published between November 2020 and May 2023. Combined, these 35 videos received 24859 comments and 1159669 of likes. Most of the videos included nurses, and 12 included nurses in professional attire. Three videos included interviewers in the video, but the rest of the videos were self-recorded. Four themes of nurses’ burnout experiences were identified: 1) high-intensity work environment, 2) negative internal perception, 3) culture of nursing work, and 4) poor teamwork experience. Conclusion: This study explored the description of nurses’ burnout experiences via a creative platform. Social media, such as TikTok, is a valuable outlet for healthcare providers to express and share their experiences. Future research might consider using the social media platform to explore coping strategies and resilience in nurses who experienced burnout.

Keywords: burnout, emotional wellbeing, nursing, social media

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Chengcao Sun, Shujun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, Dejia Li

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Recently, the long non-coding RNA (lncRNA) NEAT1 has been identified as an oncogenic gene in multiple cancer types and elevated expression of NEAT1 was tightly linked to tumorigenesis and cancer progression. However, the molecular basis for this observation has not been characterized in progression of non-small cell lung cancer (NSCLC). In our studies, we identified NEAT1 was highly expressed in NSCLC patients and was a novel regulator of NSCLC progression. Patients whose tumors had high NEAT1 expression had a shorter overall survival than patients whose tumors had low NEAT1 expression. Further, NEAT1 significantly accelerates NSCLC cell growth and metastasis in vitro and tumor growth in vivo. Additionally, by using bioinformatics study and RNA pull down combined with luciferase reporter assays, we demonstrated that NEAT1 functioned as a competing endogenous RNA (ceRNA) for has-miR-377-3p, antagonized its functions and led to the de-repression of its endogenous targets E2F3, which was a core oncogene in promoting NSCLC progression. Taken together, these observations imply that the NEAT1 modulated the expression of E2F3 gene by acting as a competing endogenous RNA, which may build up the missing link between the regulatory miRNA network and NSCLC progression.

Keywords: long non-coding RNA NEAT1, hsa-miRNA-377-3p, E2F3, non-small cell lung cancer, tumorigenesis

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Omuvwie R. Ewien

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Palm oil production in Delta State, Nigeria, is a significant economic activity. However, ensuring its sustainability is crucial to mitigate environmental impacts, promote social equity, and maintain long-term economic viability. This abstract provides an overview of palm oil production sustainability in Delta State, focusing on environmental, social, and economic aspects. In terms of environmental sustainability, the impact of palm oil plantations on deforestation and biodiversity loss is explored. The adoption of sustainable land use practices and measures to reduce greenhouse gas emissions, such as conserving high conservation value areas and utilizing methane capture systems, are highlighted. Social sustainability considerations encompass the inclusion and empowerment of smallholders, ensuring fair labor practices and community engagement. Supporting small-scale farmers, promoting fair working conditions, and investing in local infrastructure and services are identified as key strategies. Economic sustainability is emphasized through yield improvement, efficiency, and value addition. Enhancing productivity and profitability for farmers, promoting downstream processing and market diversification, and building economic resilience is crucial for long-term sustainability. Government policies, including regulatory frameworks and public-private collaborations, play a pivotal role in promoting sustainable palm oil production. Enabling policies and partnerships with industry stakeholders and NGOs facilitates the adoption of sustainable practices. Challenges such as illegal activities, the need to balance economic development with environmental conservation, and leveraging technology for sustainability are discussed. The abstract concludes by emphasizing the importance of stakeholders' commitment to prioritize sustainable palm oil production in Delta State, Nigeria, for a sustainable future.

Keywords: palm oil production, environmental sustainability, community development, yield improvement, future outlook

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Authors: Atilla Bayram

Abstract:

This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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Authors: Nishi Malhotra

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Art has developed as a mode of investment and saving. Art and culture of any nation is the source of foreign direct investment (FDI) generation and growth development. Several intermediaries and skill-building organizations thrive on at and culture for their earnings. Indian art market has grown to Rs. 2000 Crores. Art establishment houses access to privileged information is the main reason for arbitrariness and volatility in the market. The commercialization of art and development of the markets with refinement in the taste of the customers have led to the development of art as an investment avenue. Investors keen on investing in these products can do so, and earnings from art are taxable too, like any other capital asset. This research paper is aimed at exploring the role of art and culture as an investment avenue in India and reasons for increasing volatilities in the art market. Based on an extensive literature review and secondary research, a benchmarking study has been conducted to capture the growth of the art as an investment avenue. These studies indicate that during the financial crisis of 2008-10, the art emerged as an alternative investment avenue. The paper aims at discussing the financial engineering of various art funds and instruments. Based on secondary data available from Sotheby’s, Christies, Bonham, there is a positive correlation between strategic diversification and increasing return in the Art market. Similarly, digitization has led to disintermediation in the art markets and also helped to increase the market base. The data clearly enumerates the growing interest of the Indian investor towards art as an investment option. Much like any other broad asset class, art market too thrives on excess returns provided by diversification. Many financial intermediaries and art funds have emerged, to offer valuable investment planning advisory to a genuine investor. This paper clearly highlights the increasing returns of strategic diversification and its impact on reducing volatility in the art markets. Moreover, with coming up of e-auctions and websites, investors are able to analyse art more objectively. Digitization and commercialization of art have definitely helped in reducing volatility in world art markets.

Keywords: art, investment avenue, diversification, digitization

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Authors: Tu-Chieh Hung, Wei-Mon Yan, Xiao-Dong Wang, Yu-Xian Huang

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This work employs a combined optimization procedure including a simplified conjugate-gradient method and a three-dimensional fluid flow and heat transfer model to study the optimal geometric parameter design of double-layered microchannel heat sinks. The overall thermal resistance RT is the objective function to be minimized with number of channels, N, the channel width ratio, β, the bottom channel aspect ratio, αb, and upper channel aspect ratio, αu, as the search variables. It is shown that, for the given bottom area (10 mm×10 mm) and heat flux (100 W cm-2), the optimal (minimum) thermal resistance of double-layered microchannel heat sinks is about RT=0.12 ℃/m2W with the corresponding optimal geometric parameters N=73, β=0.50, αb=3.52, and, αu= 7.21 under a constant pumping power of 0.05 W. The optimization process produces a maximum reduction by 52.8% in the overall thermal resistance compared with an initial guess (N=112, β=0.37, αb=10.32 and, αu=10.93). The results also show that the optimal thermal resistance decreases rapidly with the pumping power and tends to be a saturated value afterward. The corresponding optimal values of parameters N, αb, and αu increase while that of β decrease as the pumping power increases. However, further increasing pumping power is not always cost-effective for the application of heat sink designs.

Keywords: optimization, double-layered microchannel heat sink, simplified conjugate-gradient method, thermal resistance

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Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: Guillaume Craveur

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This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

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Authors: Hongmeng Su, Luyu Zhao, Yanyan Qian, Hong Fan

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Aim: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that endanger human health seriously. RNA methylation, especially N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C), a crucial epigenetic transcriptional regulatory mechanism, plays an important role in tumorigenesis, progression and prognosis. This research aims to systematically evaluate the prognostic value of m⁶A and m⁵C modulators in HCC patients. Methods: Twenty-four modulators of m⁶A and m⁵C were candidates to analyze their expression level and their contribution to predict the prognosis of HCC. Consensus clustering analysis was applied to classify HCC patients. Cox and LASSO regression were used to construct the risk model. According to the risk score, HCC patients were divided into high-risk and low/medium-risk groups. The clinical pathology factors of HCC patients were analyzed by univariate and multivariate Cox regression analysis. Results: The HCC patients were classified into 2 clusters with significant differences in overall survival and clinical characteristics. Nine-gene risk model was constructed including METTL3, VIRMA, YTHDF1, YTHDF2, NOP2, NSUN4, NSUN5, DNMT3A and ALYREF. It was indicated that the risk score could serve as an independent prognostic factor for patients with HCC. Conclusion: This study constructed a Nine-gene risk model by modulators of m⁶A and m⁵C and investigated its effect on the clinical prognosis of HCC. This model may provide important consideration for the therapeutic strategy and prognosis evaluation analysis of patients with HCC.

Keywords: hepatocellular carcinoma, m⁶A, m⁵C, prognosis, RNA methylation

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Authors: Phimsupha Kokchang, Divine Ifransca Wijaya

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The energy transition is crucial for mitigating climate change and achieving sustainable development and resilience. As the energy transition advances, generation Z is entering the economic world and will soon be responsible for taking care of the environment. This study aims to investigate the factors influencing generation Z’s pro-environmental behavior to support the energy transition. The theory of planned behavior approach was combined with the pro-environmental behavior concept to examine generation Z’s support toward the energy transition through participating in activism, using energy from renewable sources, opting for energy-efficient utilities or vehicles, and influencing others. Data were collected through an online questionnaire of 400 respondents aged 18-26 living in Jakarta, Indonesia. Partial least square structural equation modeling (PLS-SEM) using SmartPLS 3.0 software was used to analyze the reliability and validity of the measurement model. The results show that attitude, subjective norms, and perceived behavior control positively correlate with generation Z’s pro-environmental behavior to support the energy transition. This finding could enhance understanding and provide insights to formulate effective strategies and policies to increase generation Z’s support towards the energy transition. This study contributes to the energy transition discussion as it is included in the Sustainable Development Goals, as well as pro-environmental behavior and theory of planned behavior literature.

Keywords: energy transition, pro-environmental behavior, theory of planned behavior, generation Z

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Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

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Authors: Samuel Emeka Anarah, Kingsley Nnaemeka Ogbu, Obasi Arinze

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Quantifying the hydrological response due to changes in climate change is imperative for proper management of water resources within a watershed. The impact of climate change on the hydrology of the Upper Ebony River (UER) watershed, South East Nigeria, was studied using the Soil and Water Assessment Tool (SWAT) hydrological model. A climatological time series analysis from 1985 - 2014 using non-parametric test showed significant negative trends in precipitation and relative humidity trend while minimum and maximum temperature, solar radiation and wind speed showed significant positive trends. Future hypothetical land-use change scenarios (Scenarios 1, 2, 3 and 4) representing urbanization and conversion of forest to agricultural land were combined with future downscaled climate model (CSIRO-Mk3-6-0) and simulated in SWAT model. Relative to the Baseline scenario (2005 - 2014), the results showed a decrease in streamflow by 10.29%, 26.20%, 11.80% and 26.72% for Scenarios 1, 2, 3, and 4 respectively. Model results suggest development of adaptation strategies to cope with the predicted hydrological conditions under future climate change in the watershed.

Keywords: climate change, hydrology, runoff, SWAT model

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Authors: Christian C. Vaso, Rinlee Butch M. Cervera

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One of the most promising anode materials for solid oxide electrolysis cell (SOEC) application is the Sr-doped LaMnO₃ (LSM) which is known to have a high electronic conductivity but low ionic conductivity. To increase the ionic conductivity or diffusion of ions through the anode, Yttria-stabilized Zirconia (YSZ), which has good ionic conductivity, is proposed to be combined with LSM to create a composite electrode and to obtain a high mixed ionic and electronic conducting anode. In this study, composite of lanthanum strontium manganite and YSZ oxide, La_0.8Sr_0.2MnO₃/Zr_0.92Y_0.08O₂ (LSM/YSZ), with different wt.% compositions of LSM and YSZ were synthesized using solid-state reaction. The obtained prepared composite samples of 60, 50, and 40 wt.% LSM with remaining wt.% of 40, 50, and 60, respectively for YSZ were fully characterized for its microstructure by using powder X-ray diffraction (XRD), Thermogravimetric analysis (TGA), Fourier transform infrared (FTIR), and Scanning electron microscope/Energy dispersive spectroscopy (SEM/EDS) analyses. Surface morphology of the samples via SEM analysis revealed a well-sintered and densified pure LSM, while a more porous composite sample of LSM/YSZ was obtained. Electrochemical impedance measurements at intermediate temperature range (500-700 °C) of the synthesized samples were also performed which revealed that the 50 wt.% LSM with 50 wt.% YSZ (L50Y50) sample showed the highest total conductivity of 8.27x10^-1 S/cm at 600 ^oC with 0.22 eV activation energy.

Keywords: ceramics, microstructure, fuel cells, electrochemical impedance spectroscopy

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Authors: Terry Liang Khin Teo, Sun Woh Lye, Kai Lun Brendon Goh

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As applied to dynamic monitoring situations, the prevailing approach to situation awareness (SA) assumes that the relevant areas of interest (AOI) be perceived before that information can be processed further to affect decision-making and, thereafter, action. It is not entirely clear whether this is the case. This study seeks to investigate the monitoring of dynamic objects through matching eye fixations with the relevant AOIs in boundary-crossing scenarios. By this definition, a match is where a fixation is registered on the AOI. While many factors may affect monitoring characteristics, traffic simulations were designed in this study to explore two factors, namely: the number of inbounds/outbound traffic transfers and the number of entry and/or exit points in a radar monitoring sector. These two factors were graded into five levels of difficulty ranging from low to high traffic flow numbers. Combined permutation in terms of levels of difficulty of these two factors yielded a total of thirty scenarios. Through this, results showed that changes in the traffic flow numbers on transfer resulted in greater variations having match limits ranging from 29%-100%, as compared to the number of sector entry/exit points of range limit from 80%-100%. The subsequent analysis is able to determine the type and combination of traffic scenarios where imperfect matching is likely to occur.

Keywords: air traffic simulation, eye-tracking, visual monitoring, focus attention

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Authors: Mahbod Seyednia, Shidvash Vakilipour, Mehran Masdari

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Computations for two-dimensional flow past a stationary and harmonically pitching wind turbine airfoil at a moderate value of Reynolds number (400000) are carried out by progressively increasing the angle of attack for stationary airfoil and at fixed pitching frequencies for rotary one. The incompressible Navier-Stokes equations in conjunction with Unsteady Reynolds Average Navier-Stokes (URANS) equations for turbulence modeling are solved by OpenFOAM package to investigate the aerodynamic phenomena occurred at stationary and pitching conditions on a NACA 6-series wind turbine airfoil. The aim of this study is to enhance the accuracy of numerical simulation in predicting the aerodynamic behavior of an oscillating airfoil in OpenFOAM. Hence, for turbulence modelling, k-ω-SST with low-Reynolds correction is employed to capture the unsteady phenomena occurred in stationary and oscillating motion of the airfoil. Using aerodynamic and pressure coefficients along with flow patterns, the unsteady aerodynamics at pre-, near-, and post-static stall regions are analyzed in harmonically pitching airfoil, and the results are validated with the corresponding experimental data possessed by the authors. The results indicate that implementing the mentioned turbulence model leads to accurate prediction of the angle of static stall for stationary airfoil and flow separation, dynamic stall phenomenon, and reattachment of the flow on the surface of airfoil for pitching one. Due to the geometry of the studied 6-series airfoil, the vortex on the upper surface of the airfoil during upstrokes is formed at the trailing edge. Therefore, the pattern flow obtained by our numerical simulations represents the formation and change of the trailing-edge vortex at near- and post-stall regions where this process determines the dynamic stall phenomenon.

Keywords: CFD, moderate Reynolds number, OpenFOAM, pitching oscillation, unsteady aerodynamics, wind turbine

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: George Madalin Danila, Mihaiella Cretu, Cristian Puscasu

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Glycol-based anti-freeze liquids, commonly composed of ethylene glycol or propylene glycol, have important uses in automotive cooling, but they should be handled with care due to their toxicity; ethylene glycol is highly toxic to humans and animals. A fast, accurate, precise, and robust method was developed for the simultaneous quantification of 7 most important glycols and their isomers. Glycols were analyzed from diluted sample solution of coolants using gas-chromatography coupled with mass spectrometry in single ion monitoring mode. Results: The method was developed and validated for 7 individual glycols (ethylene glycol, diethylene glycol, triethylene glycol, tetraethylene glycol, propylene glycol, dipropylene glycol and tripropylene glycol). Limits of detection (1-2 μg/mL) and limit of quantification (10 μg/mL) obtained were appropriate. The present method was applied for the determination of glycols in 10 different anti-freeze liquids commercially available on the Romanian market, proving to be reliable. A method that requires only a two-step dilution of anti-freeze samples combined with direct liquid injection GC-MS was validated for the simultaneous quantification of 7 glycols (and their isomers) in 10 different types of anti-freeze liquids. The results obtained in the validation procedure proved that the GC-MS method is sensitive and precise for the quantification of glycols.

Keywords: glycols, anti-freeze, gas-chromatography, mass spectrometry, validation, recycle

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Authors: Kye Gilder, Kevin Shan, Amy Halseth, Steve Smith

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This study assessed the effect of prolonged-release naltrexone 32 mg/bupropion 360 mg (NB) on cardiovascular (CV) events in overweight/obese participants at elevated CV risk. Participants must lose ≥2% body weight at 16 wks, without a sustained increase in blood pressure, to continue drug. Only serious adverse events (SAE) and adverse events leading to discontinuation of study drug (AELDSD) were collected. The study was terminated early after second interim analysis with 50% of all CV events. Data on CV endpoints has been published. Current analyses focused on AEs in participants on antidepressants at baseline, as these individuals were excluded from Phase 3 trials. Intent-to-treat (ITT) population (placebo [PBO] N=4450, NB N=4455) was 54.5% female, 83.5% white, mean age of 61 yrs, mean BMI 37.3 kg/m2, 22.8% with a history of depression, 23.1% on antidepressants, including 15.4% on an SSRI. SAEs in participants receiving antidepressants was similar between NB (10.7%) and PBO (9.9%) and also similar to overall population (9.5% NB, 8.1% PBO). SAEs in those on SSRIs were similar, 10.1% NB and PBO 9.4%. For those on SSRIs or other antidepressants, AELDSDs were similar to overall population and were primarily GI disorders. Obesity increases the risk of developing depression. For participants taking NB and antidepressants, including SSRIs, there is a similar AE profile as the overall population and data revealed no evidence of an additional health risk with combined use.

Keywords: antidepressant, Contrave, Mysimba, obesity, pharmacotherapy

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Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

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The number of inpatient admissions in the UK has been significantly increasing over the past decade. These increases cause bed occupancy rates to exceed the target level (85%) set by the Department of Health in England. Therefore, hospital service managers are struggling to better manage key resource such as beds. On the other hand, this severe demand pressure might lead to confusion in wards. For example, patients can be admitted to the ward of another inpatient specialty due to lack of resources (i.e., bed). This study aims to develop a simulation-optimization model to reallocate the available number of beds in a mid-sized hospital in the UK. A hospital simulation model was developed to capture the stochastic behaviours of the hospital by taking into account the accident and emergency department, all outpatient and inpatient services, and the interactions between each other. A couple of outputs of the simulation model (e.g., average length of stay and revenue) were generated as inputs to be used in the optimization model. An integer linear programming was developed under a number of constraints (financial, demand, target level of bed occupancy rate and staffing level) with the aims of maximizing number of admitted patients. In addition, a sensitivity analysis was carried out by taking into account unexpected increases on inpatient demand over the next 12 months. As a result, the major findings of the approach proposed in this study optimally reallocate the available number of beds for each inpatient speciality and reveal that 74 beds are idle. In addition, the findings of the study indicate that the hospital wards will be able to cope with 14% demand increase at most in the projected year. In conclusion, this paper sheds a new light on how best to reallocate beds in order to cope with current and future demand for healthcare services.

Keywords: bed occupancy rate, bed reallocation, discrete event simulation, inpatient admissions, integer linear programming, projected usage

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Authors: Tso-Yen Mao, De-Yen Liu, Chun-Feng Huang

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Purpose: This research intends to investigate the reliability and validity of ventilatory threshold (VT) and respiratory compensation point (RCP) determined by skeletal muscle hemodynamic status. Methods: One hundred healthy male (age: 22±3 yrs; height: 173.1±6.0 cm; weight: 67.1±10.5 kg) performed graded cycling exercise test which ventilatory and skeletal muscle hemodynamic data were collected simultaneously. VT and RCP were determined by combined V-slope (VE vs. VCO2) and ventilatory efficiency (VE/VO2 vs. VE/VCO2) methods. Pearson correlation, paired t-test, and Bland-Altman plots were used to analyze reliability, validity, and similarities. Statistical significance was set at α =. 05. Results: There are high test-retest correlations of VT and RCP in ventilatory or near-infrared spectroscopy (NIRS) methods (VT vs. VTNIRS: 0.95 vs. 0.94; RCP vs. RCPNIRS: 0.93 vs. 0.93, p<. 05). There are high coefficient of determination at the first timing point of O2Hb decreased (R2 = 0.88, p<. 05) with VT, and high coefficient of determination at the second timing point of O2Hb declined (R2 = 0.89, p< .05) with RCP. VO2 of VT and RCP are not significantly different between ventilatory and NIRS methods (p>. 05). Conclusion: Using NIRS method to determine VT and RCP is reliable and valid in male individuals during graded exercise. Non-invasive skeletal muscle hemodynamics monitor also can be used for controlling training intensity in the future.

Keywords: anaerobic threshold, exercise intensity, hemodynamic, NIRS

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Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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Authors: Adar Pelah, Avraham Adelman, Amanda Balash, Jake Mitchell, Mattan J. Pelah, Viswadeep Sarangi, Xin Chen Cai, Zadok Storkey, Gregg B. Fields, Ximena Levy, Ali A. Danesh

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Introduction: Post-Acute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 infection (PASC), or Long COVID, while primarily a respiratory disorder, can also include dizziness, lasting weeks to months in individuals who had previously tested positive for COVID-19. This study utilized gait analysis to assess the potential vestibular effects of PASC on the presentation of gait anomalies. Materials and Methods: The study included 11 participants who tested positive for COVID-19, a mean of 2.8 months prior to gait testing (PP=11), and 8 control participants who did not test positive for COVID-19 (NP=8). Participants walked 7.5m at three self-selected speeds: ‘slow,’ ‘normal,’ and ‘fast.’ Mean walking speeds were determined for each speed and overall range from four laps on an instrumented walkway using video capture. Results: A Z-test at 0.05 significance was used for speed range, ‘normal’ and ‘fast’ at the lower tail, and for ‘slow’ at the higher tail. Average speeds (m/s) were: ‘slow’ (PP=0.709, NP=0.678), ‘normal’ (PP=1.141, NP=1.170), ‘fast’ (PP=1.529, NP=1.821), average range (PP=0.846, NP=1.143). Significant speed decreases between PP and NP were observed in ‘fast’ (-17.43%) and average range (-29.86%), while changes in ‘slow’ (+2.44%) and ‘normal’ (-4.39%) speeds were not significant. Conclusions: Long COVID is a recognized disability (Americans with Disabilities Act), and although it presents variably, dizziness, vertigo, and tinnitus are not uncommon in COVID-19 infection. These results suggest that potential inner-ear damage may persist and manifest in gait changes even after recovery from acute illness. Further research with a larger sample size may indicate the need for providers to consider PASC when diagnosing patients with vestibular dysfunction.

Keywords: gait analysis, long-COVID, vestibular dysfunction, walking speed

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Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik

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In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.

Keywords: growth management, land use externalities, land value, spatial panel dynamic

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Authors: Y. Chiang, J. R. Wang, J. H. Yang, Y. S. Tseng, C. Shih, S. W. Chen

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Kuosheng nuclear power plant (NPP) is a BWR/6 plant in Taiwan. There is more concern for the safety of Spent Fuel Pools (SFPs) in Taiwan after Fukushima event. In order to estimate the safety of Kuosheng NPP SFP, by using MELCOR2.1 and SNAP, the safety analysis of Kuosheng NPP SFP was performed combined with the mitigation strategy of NEI 06-12 report. There were several steps in this research. First, the Kuosheng NPP SFP models were established by MELCOR2.1/SNAP. Second, the Station Blackout (SBO) analysis of Kuosheng SFP was done by TRACE and MELCOR under the cooling system failure condition. The results showed that the calculations of MELCOR and TRACE were very similar in this case. Second, the mitigation strategy analysis was done with the MELCOR model by following the NEI 06-12 report. The results showed the effectiveness of NEI 06-12 strategy in Kuosheng NPP SFP. Finally, a sensitivity study of SFP quenching was done to check the differences of different water injection time and the phenomena during the quenching. The results showed that if the cladding temperature was over 1600 K, the water injection may have chance to cause the accident more severe with more hydrogen generation. It was because of the oxidation heat and the “Breakaway” effect of the zirconium-water reaction. An animation model built by SNAP was also shown in this study.

Keywords: MELCOR, SNAP, spent fuel pool, quenching

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Authors: Yun-An Chen, Hung-Jun Lin, Tai-Horng Young, Der-Zen Liu

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Decellularized brain extracellular matrix had been shown that it has the ability to influence on cell proliferation, differentiation and associated cell phenotype. However, this scaffold is thought to have poor mechanical properties and rapid degradation, it is hard for cell recellularization. In this study, we used decellularized brain extracellular matrix combined with chitosan, which is naturally occurring polysaccharide and non-cytotoxic polymer, forming a 3-D scaffold for neural stem/precursor cells (NSPCs) regeneration. HE staining and DAPI fluorescence staining confirmed decellularized process could effectively vanish the cellular components from the brain. GAGs and collagen I, collagen IV were be showed a great preservation by Alcain staining and immunofluorescence staining respectively. Decellularized brain extracellular matrix was well mixed in chitosan to form a 3-D scaffold (DB-C scaffold). The pore size was approximately 50±10 μm examined by SEM images. Alamar blue results demonstrated NSPCs had great proliferation ability in DB-C scaffold. NSPCs that were cultured in this complex scaffold differentiated into neurons and astrocytes, as reveled by NSPCs expression of microtubule-associated protein 2 (MAP2) and glial fibrillary acidic protein (GFAP). In conclusion, DB-C scaffold may provide bioinformatics cues for NSPCs generation and aid for CNS injury functional recovery applications.

Keywords: brain, decellularization, chitosan, scaffold, neural stem/precursor cells

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Authors: M. G. Mostafa, Manjushree Chowdhury, Tapan Kumar Biswas, , Ananda Kumar Saha

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This study focused on effluents characterization and treatment process to reduce of toxicity from tannery effluents. Tanning industry is one of the oldest industries in the world. It is typically characterized as pollutants generated industries which produce wide varieties of high strength toxic chemicals. The study was conducted during the year 2008 to 2009 and the tannery effluents were collected three times in a year from the outlet of some selected leather industries located in Hagaribagh industrial zone Dhaka, Bangladesh. The analysis results of the raw effluents reveal that the effluents were yellowish-brown color, having basic pH, very high value of BOD5¬¬, COD, TDS, TSS, TS, and high concentrations of Cr, Na, SO42-, Cl- and other organic and inorganic constituents. The tannery effluents were treated with various doses of FeCl3 after settling and a subsequent filtration through sand-stone. The study observed that coagulant (FeCl3) 150 mg/L dose around neutral pH showed the best removal efficiency for major physico-chemical parameters. The analysis results of illustrate that the most of the physical and chemical parameters were found well below the prescribed permissible limits for effluent discharged. The study suggests that tannery effluents could be treated by a combined process consisting of settling, filtering and coagulating with FeCl3.

Keywords: characterization, effluent, tannery, treatment

Procedia PDF Downloads 433