Search results for: modified simplex algorithm

Authors: Kamilia Mebarki

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The promotion of intercultural competence plays an important role in foreign language education. The outcome of intercultural educationalists‟ studies was the adoption of intercultural language learning and a modified version of the Communicative Competence that encompasses an intercultural component enabling language learners to communicate successfully interculturally. Intercultural Competencehas an even more central role in teaching English as a foreign language (EFL) since efforts are critical to preparing learners for intercultural communisation in our global world. In these efforts, EFL learning materials are a crucial stimulus for developing learners’ intercultural competence. There has been a continuous interest in the analysis of EFL textbooks by researcher all over the world. One specific area that has received prominent attention in recent years is a focus on how the cultural content of EFL materials promote intercultural competence. In the Algerian context, research on the locally produced EFL textbooks tend to focus on investigating the linguistic and communicative competence. The cultural content of the materials has not yet been systematically researched. Therefore, this study contributes to filling this gap by evaluating the locally published EFL textbook ‘New Prospects’ used at the high school level as well as investigating teachers’ views and attitudes on the cultural content of ‘New Prospects’ alongside two others locally produced EFL textbooks ‘Getting Through’ and ‘At the Crossroad’ used at high school level. To estimate the textbook’s potential of developing intercultural competence, mixed methods, a combination of quantitative and qualitative data collection, was used in the material evaluation analysed via content analysis and in the survey questionnaire and interview with teachers.Data collection and analysis were supported by the frameworks developed by the researcher for analysing the textbook, questionnaire, and interview. Indeed, based on the literature, three frameworks/ models are developed in this study to analyse, on one hand, the cultural contexts and themes discussed in the material that play an important role in fostering learners’ intercultural awareness. On the other hand, to evaluate the promotion of developing intercultural competence.

Keywords: intercultural communication, intercultural communicative competence, intercultural competence, EFL materials

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Authors: Rachit Ahuja, Ayush Chugh

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Aerodynamic forces and moments, as well as tire-road forces largely affects the maneuverability of the vehicle. Car manufacturers are largely fascinated and influenced by various aerodynamic improvements made in formula cars. There is constant effort of applying these aerodynamic improvements in road vehicles. In motor racing, the key differentiating factor in a high performance car is its ability to maintain highest possible acceleration in appropriate direction. One of the main areas of concern in motor racing is balance of aerodynamic forces and stream line the flow of air across the body of the vehicle. At present, formula racing cars are regulated by stringent FIA norms, there are constrains for dimensions of the vehicle, engine capacity etc. So one of the fields in which there is a large scope of improvement is aerodynamics of the vehicle. In this project work, an attempt has been made to design a formula- student (FS) car, improve its aerodynamic characteristics through steady state CFD simulations and simultaneously calculate its lap time. Initially, a CAD model of a formula student car is made using SOLIDWORKS as per the given dimensions and a steady-state external air-flow simulation is performed on the baseline model of the formula student car without any add on device to evaluate and analyze the air-flow pattern around the car and aerodynamic forces using FLUENT Solver. A detailed survey on different add-on devices used in racing application like: - front wing, diffuser, shark pin, T- wing etc. is made and geometric model of these add-on devices are created. These add-on devices are assembled with the baseline model. Steady state CFD simulations are done on the modified car to evaluate the aerodynamic effects of these add-on devices on the car. Later comparison of lap time simulation of the formula student car with and without the add-on devices is done with the help of MATLAB. Aerodynamic performances like: - lift, drag and their coefficients are evaluated for different configuration and design of the add-on devices at different speed of the vehicle. From parametric CFD simulations on formula student car attached with add-on devices, there is a considerable amount of drag and lift force reduction besides streamlining the airflow across the car. The best possible configuration of these add-on devices is obtained from these CFD simulations and also use of these add-on devices have shown an improvement in performance of the car which can be compared by various lap time simulations of the car.

Keywords: aerodynamic performance, front wing, laptime simulation, t-wing

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Authors: Sungmin Park, Gyungmok Nam, Seungpyo Woo, Young Choi, Sangheon Park, Sang-Hee Yoon

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Puncturing human skin with microneedles is critically important for microneedle-mediate drug delivery. Despite of extensive efforts in the past decades, the scale-up fabrication of sharp-tipped and high-aspect-ratio microneedles, especially made of biodegradable polymers, is still a long way off. Here, we present a UV dose insensitive and cost-effective microfabrication method for the biodegradable polymer microneedles with sharp tips and long lengths which can pierce human skin with low insertion force. The biodegradable polymer microneedles are fabricated with the polymer solution casting where a poly(lactic-co-glycolic acid) (PLGA, 50:50) solution is coated onto a SU-8 mold prepared with a reverse, ramped, and rotational (R3) UV exposure. The R3 UV exposure is modified from the multidirectional UV exposure both to suppress UV reflection from the bottom surface without anti-reflection layers and to optimize solvent concentration in the SU-8 photoresist, therefore achieving robust (i.e., highly insensitive to UV dose) and cost-effective fabrication of biodegradable polymer microneedles. An optical model for describing the spatial distribution of UV irradiation dose of the R3 UV exposure is also developed to theoretically predict the microneedle geometry fabricated with the R3 UV exposure and also to demonstrate the insensitiveness of microneedle geometry to UV dose. In the experimental characterization, the microneedles fabricated with the R3 UV exposure are compared with those fabricated with a conventional method (i.e., multidirectional UV exposure). The R3 UV exposure-based microfabrication reduces the end-tip radius by a factor of 5.8 and the deviation from ideal aspect ratio by 74.8%, compared with conventional method-based microfabrication. The PLGA microneedles fabricated with the R3 UV exposure pierce full-thickness porcine skins successfully and are demonstrated to completely dissolve in PBS (phosphate-buffered saline). The findings of this study will lead to an explosive growth of the microneedle-mediated drug delivery market.

Keywords: R³ UV exposure, optical model, UV dose, reflection, solvent concentration, biodegradable polymer microneedle

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Authors: Boumaraf Malak

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The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: Sarre Nzaba, Bulelwa Ntsendwana, Bekkie Mamba, Alex Kuvarega

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The discharge of azo dyes such as Brilliant black (BB) into the water bodies has carcinogenic and mutagenic effects on humankind and the ecosystem. Conventional water treatment techniques fail to degrade these dyes completely thereby posing more problems. Advanced oxidation processes (AOPs) are promising technologies in solving the problem. Anatase type nitrogen-platinum (N, Pt) co-doped TiO₂ photocatalysts were prepared by a modified sol-gel method using amine terminated polyamidoamine generation 1 (PG1) as a template and source of nitrogen. The resultant photocatalysts were characterized by X‐ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X‐ray photoelectron spectroscopy (XPS), UV‐Vis diffuse reflectance spectroscopy, photoluminescence spectroscopy (PL), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy (RS), thermal gravimetric analysis (TGA). The results showed that the calcination atmosphere played an important role in the morphology, crystal structure, spectral absorption, oxygen vacancy concentration, and visible light photocatalytic performance of the catalysts. Anatase phase particles ranging between 9- 20 nm were also confirmed by TEM, SEM, and analysis. The origin of the visible light photocatalytic activity was attributed to both the elemental N and Pd dopants and the existence of oxygen vacancies. Co-doping imparted a shift in the visible region of the solar spectrum. The visible light photocatalytic activity of the samples was investigated by monitoring the photocatalytic degradation of brilliant black dye. Co-doped TiO₂ showed greater photocatalytic brilliant black degradation efficiency compared to singly doped N-TiO₂ or Pd-TiO₂ under visible light irradiation. The highest reaction rate constant of 3.132 x 10-2 min⁻¹ was observed for N, Pd co-doped TiO₂ (2% Pd). The results demonstrated that the N, Pd co-doped TiO₂ (2% Pd) sample could completely degrade the dye in 3 h, while the commercial TiO₂ showed the lowest dye degradation efficiency (52.66%).

Keywords: brilliant black, Co-doped TiO₂, polyamidoamine generation 1 (PAMAM G1), photodegradation

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Authors: Ilse Kreme

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To the best of this author’s knowledge, no studies have been identified on the connection between a refusal to engage in health-protective behaviors and a basic understanding of viral biology among community college students, faculty, and staff during the COVID-19 pandemic. Lack of scientific knowledge could prevent understanding of why these behaviors are important to prevent the community spread of COVID-19, even when they are not shown to offer much individual protection. In this study, a possible correlation was examined between a basic knowledge level of viral disease that comes from having taken a college biology course and disease perceptions of COVID-19. In particular, disease risk perception, disease severity percept and mask-wearing behaviors were examined as they correlated with having taken an undergraduate biology course. The effect of covariates of age, gender, and education level were investigated along with the main dependent variables. A representative sample of the population included students, faculty, and staff at Paradise Valley Community College (PVCC) in Phoenix, Arizona. Participants were recruited by an email sent to all students, faculty, and staff at PVCC using an all-college email distribution. Disease risk and severity perception were assessed with the Brief Illness Perception Questionnaire 5 (BIP-Q5), which was modified to include questions measuring participant age, education level, and whether they took or ever took a college biology course. Two additional questions measured compliance of willingness to wear a face mask. The results showed an effect of gender on mask-wearing behavior and a correlation between having taken a biology course and disease severity perception. No differences were seen in mask-wearing behavior and disease risk perception as a result of having taken a biology course. These findings suggest that taking an undergraduate biology course leads to a greater awareness of COVID-19 disease severity through an understanding of the basic biological principles of viral disease transmission. The results can be used to modify existing health education strategies. Further research is needed on how to best reach target audiences in all education brackets.

Keywords: COVID-19, education, gender, mask wearing, disease risk perception, disease severity perception

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Authors: Rashid Javed, Hardy Lehmkuehler, Franz Josef-Behr

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Web Processing Services (WPS) have up growing concern in geoinformation research. However, teaching about them is difficult because of the generally complex circumstances of their use. They limit the possibilities for hands- on- exercises on Web Processing Services. To support understanding however a Training Tools Collection was brought on the way at University of Applied Sciences Stuttgart (HFT). It is limited to the scope of Geostatistical Interpolation of sample point data where different algorithms can be used like IDW, Nearest Neighbor etc. The Tools Collection aims to support understanding of the scope, definition and deployment of Web Processing Services. For example it is necessary to characterize the input of Interpolation by the data set, the parameters for the algorithm and the interpolation results (here a grid of interpolated values is assumed). This paper reports on first experiences using a pilot installation. This was intended to find suitable software interfaces for later full implementations and conclude on potential user interface characteristics. Experiences were made with Deegree software, one of several Services Suites (Collections). Being strictly programmed in Java, Deegree offers several OGC compliant Service Implementations that also promise to be of benefit for the project. The mentioned parameters for a WPS were formalized following the paradigm that any meaningful component will be defined in terms of suitable standards. E.g. the data output can be defined as a GML file. But, the choice of meaningful information pieces and user interactions is not free but partially determined by the selected WPS Processing Suite.

Keywords: deegree, interpolation, IDW, web processing service (WPS)

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Mohamed I. D. Helal, Mohamed M. El-Mogy, Hassan A. Khater, Muhammad A. Fathy, Fatma E. Ibrahim, Yuncong C. Li, Zhaohui Tong, Karima F. Abdelgawad

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Minimizing the consumption of agrochemicals, particularly nitrogen, is the ultimate goal for achieving sustainable agricultural production with low cost and high economic and environmental returns. The use of biopolymers instead of petroleum-based synthetic polymers for CRFs can significantly improve the sustainability of crop production since biopolymers are biodegradable and not harmful to soil quality. Lignin is one of the most abundant biopolymers that naturally exist. In this study, controlled-release fertilizers were developed using a biobased nanocomposite of lignin and bentonite clay mineral as a coating material for urea to increase nitrogen use efficiency. Five types of controlled-release urea (CRU) were prepared using two ratios of modified bentonite as well as techniques. The efficiency of the five controlled-release nano-urea (CRU) fertilizers in improving the growth of tomato plants was studied under field conditions. The CRU was applied to the tomato plants at three N levels representing 100, 50, and 25% of the recommended dose of conventional urea. The results showed that all CRU treatments at the three N levels significantly enhanced plant growth parameters, including plant height, number of leaves, fresh weight, and dry weight, compared to the control. Additionally, most CRU fertilizers increased total yield and fruit characteristics (weight, length, and diameter) compared to the control. Additionally, marketable yield was improved by CRU fertilizers. Fruit firmness and acidity of CRU treatments at 25 and 50% N levels were much higher than both the 100% CRU treatment and the control. The vitamin C values of all CRU treatments were lower than the control. Nitrogen uptake efficiencies (NUpE) of CRU treatments were 47–88%, which is significantly higher than that of the control (33%). In conclusion, all CRU treatments at an N level of 25% of the recommended dose showed better plant growth, yield, and fruit quality of tomatoes than the conventional fertilizer.

Keywords: nitrogen use efficiency, quality, urea, nano particles, ecofriendly

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Authors: M. A. Ashour

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As it is known Egypt is one of the countries having oldest sugarcane industry, which goes back to the year 710 AD. Cane plantations are the main agricultural product in five governorates in Upper Egypt (El-Menia, Sohag, Qena, Luxor, and Aswan), producing not less than 16 million tons a year. Eight factories (Abou-korkas, Gena, Nagaa-Hamadi, Deshna, Kous, Armant, Edfuo, and Komombo), located in such upper Egypt governorates generates huge amount of wastes during the manufacturing stage, the so called bagasse which is the fibrous, and cellulosic materials remaining after the era of the sugarcane and the juice extraction, presents about 30% of such wastes. The amount of bagasse generated yearly through the manufacturing stage of the above mentioned 8 factories is approximately about 2.8 million tons, getting red safely of such huge amount, presents a serious environmental problem. Storage of that material openly in the so hot climate in upper Egypt, may cause its self-ignition under air temperature reaches 50 degrees centigrade in summer, due to the remained residual content of sugar. At the same time preparing places for safely storage for such amount is very expensive with respect to the valueless of it. So the best way for getting rid of bagasse is converting it into an added value environmentally friendly material, especially till now the utilization of it is so limited. Since oil pollution became a serious concern, the issue of environmental cleaning arises. With the structure of sugarcane bagasse, which contains fiber and high content of carbon, it can be an adsorbent to adsorb the oil contamination from the water. The present study is a trail to introduce a new material for the purification of water systems to score two goals at once, the first is getting rid of that harmful waste safely, the second is converting it to a commercial valuable material for cleaning, and purifying the water from oil spills, and petroleum pollution. Introduced the new material proved very good performance, and higher efficiency than other similar materials available in the local market, in both closed and open systems. The introduced modified material can absorb 10 times its weight of oil, while don't absorb any water.

Keywords: environment, water resources, agricultural wastes, oil pollution control, sugarcane

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Authors: Yash Bingi, Yiqiao Yin

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Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

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Authors: John Olorunfemi Abe, Olawale Muhammed Popoola, Abimbola Patricia Idowu Popoola

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Hydrogen is an appealing alternative to fossil fuels because of its abundance, low weight, high energy density, and relative lack of contaminants. However, its low density presents a number of storage challenges. Therefore, this work studies the influence of refractory nitride additives consisting of 5 wt. % each of hexagonal boron nitride (h-BN), titanium nitride (TiN), and aluminum nitride (AlN) on hydrogen storage and electrochemical characteristics of Ti6Al4V-based materials produced by spark plasma sintering. The microstructure and phase constituents of the sintered materials were characterized using scanning electron microscopy (in conjunction with energy-dispersive spectroscopy) and X-ray diffraction, respectively. Pressure-composition-temperature (PCT) measurements were used to assess the hydrogen absorption/desorption behavior, kinetics, and storage capacities of the sintered materials, respectively. The pure Ti6Al4V alloy displayed a two-phase (α+β) microstructure, while the modified composites exhibited apparent microstructural modifications with the appearance of nitride-rich secondary phases. It is found that the diffusion process controls the kinetics of the hydrogen absorption. Thus, a faster rate of hydrogen absorption at elevated temperatures ensued. The additives acted as catalysts, lowered the activation energy and accelerated the rate of hydrogen sorption in the composites relative to the monolithic alloy. Ti6Al4V-5 wt. % h-BN appears to be the most promising candidate for hydrogen storage (2.28 wt. %), followed by Ti6Al4V-5 wt. % TiN (2.09 wt. %), whereas Ti6Al4V-5 wt. % AlN shows the least hydrogen storage performance (1.35 wt. %). Accordingly, the developed hydride system (Ti6Al4V-5h-BN) may be competitive for use in applications involving short-range continuous vehicles (~50-100km) as well as stationary applications such as electrochemical devices, large-scale storage cylinders in hydrogen production locations, and hydrogen filling stations.

Keywords: hydrogen storage, Ti6Al4V hydride system, pressure-composition-temperature measurements, refractory nitride additives, spark plasma sintering, Ti6Al4V-based materials

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Authors: Jordan Chamarande, Lisiane Cunat, Corentine Alauzet, Catherine Cailliez-Grimal

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Gut microbiota (GM) is now considered a new organ mainly due to the microorganism’s specific biochemical interaction with its host. Although mechanisms underlying host-microbiota interactions are not fully described, it is now well-defined that cell surface molecules and structures of the GM play a key role in such relation. The study of surface structures of GM members is also fundamental for their role in the establishment of species in the versatile and competitive environment of the digestive tract and as a potential virulence factor. Among these structures are capsular polysaccharides (CPS), fimbriae, pili and lipopolysaccharides (LPS), all well-described for their central role in microorganism colonization and communication with host epithelium. The health-promoting Parabacteroides distasonis, which is part of the core microbiome, has recently received a lot of attention, showing beneficial properties for its host and as a new potential biotherapeutic product. However, to the best of the authors’ knowledge, the cell surface molecules and structures of P. distasonis that allow its maintain within the GM are not identified. Moreover, although P. distasonis is strongly recognized as intestinal commensal species with benefits for its host, it has also been recognized as an opportunistic pathogen. In this study, we reported gene clusters potentially involved in the synthesis of the capsule, fimbriae-like and pili-like cell surface structures in 26 P. distasonis genomes and applied the new RfbA-Typing classification in order to better understand and characterize the beneficial/pathogenic behaviour related to P. distasonis strains. In context, 2 different types of fimbriae, 3 of pilus and up to 14 capsular polysaccharide loci, have been identified over the 26 genomes studied. Moreover, the addition of data to the rfbA-Type classification modified the outcome by rearranging rfbA genes and adding a fifth group to the classification. In conclusion, the strain variability in terms of external proteinaceous structure could explain the inter-strain differences previously observed in P. distasonis adhesion capacities and its potential pathogenicity.

Keywords: gut microbiota, Parabacteroides distasonis, capsular polysaccharide, fimbriae, pilus, O-antigen, pathogenicity, probiotic, comparative genomics

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Authors: Hee-Young Song

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Background and objectives: In 2011, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations proposed a multidimensional assessment of patients’ conditions that included both functional parameters and patient-reported outcomes, with the aim to provide a comprehensive assessment of the disease, thus meeting both the needs of the patient and the role of the physician. However, few studies have evaluated patient-reported outcomes as well as objective functional assessments among individuals with chronic obstructive pulmonary disease (COPD) in clinical practice in Korea. This study was undertaken to explore the relationship between functional status assessed by the 6-minute walking distance (MWD) test and subjective health status reported by stable patients with COPD residing in community. Methods: A cross-sectional descriptive study was conducted with 118 stable COPD patients aged 69.4 years old and selected by a convenient sampling from an outpatient department of pulmonology in a tertiaryhospitals. The 6-MWD test was conducted according to standardized instructions. Participants also completed a constructed questionnaire including general characteristics, smoking history, dyspnea by modified medical research council (mMRC) scale, and health status by COPD assessment test (CAT). Anthropometric measurements were performed for body mass index (BMI). Medical records were reviewed to obtain disease-related characteristics including duration of the disease and forced expiratory volume in 1 second (FEV1). Data were analyzed using PASW statistics 20.0. Results: Mean FEV1% of participants was 63.51% and mean 6-MWD and CAT scores were 297.54m and 17.7, respectively. The 6-MWD and CAT showed significant negative correlations (r= -.280, p=.002); FEV1 and CAT did as well correlations (r= -.347, p < .001). Conclusions: Findings suggest that the better functional status an individual with COPD has, the better subjective health status is, and provide the support for using patient-reported outcomes along with functional parameters to facilitate comprehensive assessment of COPD patients in real clinical practices.

Keywords: chronic obstructive pulmonary disease, COPD assessment test, functional status, patient-reported outcomes

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Authors: Abdul Mutalib Md Jani, Abdul Hadi Mahmud, Mohd Tajuddin Mohd Ali

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The rapid growth of interest in surface modification of nanostructures materials that exhibit improved structural and functional properties is attracting more researchers. The unique properties of highly ordered nanoporous anodic aluminium oxide (NAAO) membrane have been proposed as a platform for biosensing applications. They exhibit excellent physical and chemical properties with high porosity, high surface area, tunable pore sizes and excellent chemical resistance. In this study, NAAO was functionalized with 3-aminopropyltriethoxysilane (APTES) to prepared silane-modified NAAO. Amine functional groups are formed on the surface of NAAO during silanization and were characterized using Fourier Transform Infrared spectroscopy (FTIR). The synthesis of multi segment of peptide on NAAO surfaces can be realized by changing the surface chemistry of the NAAO membrane via click chemistry. By click reactions, utilizing alkyne terminated with amino group, various peptides tagged on NAAO can be envisioned from chiral natural or unnatural amino acids using standard coupling methods (HOBt, EDCI and HBTU). This strategy seemly versatile since coupling strategy of dipeptide with another amino acids, leading to tripeptide, tetrapeptide or pentapeptide, can be synthesized without purification. When an appropriate terminus is selected, multiple segments of amino acids can be successfully synthesized on the surfaces. The immobilized NAAO should be easily separated from the reaction medium by conventional filtration, thus avoiding complicated purification methods. Herein, we proposed to synthesize multi fragment peptide as a model for capturing and attaching various small biomolecules on NAAO surfaces and can be also applied as biosensing device, drug delivery systems and biocatalyst.

Keywords: nanoporous anodic aluminium oxide, silanization, peptide synthesise, click chemistry

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Authors: Victoria L. Malakhova

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The research is devoted to multimodal content and its effectiveness in developing students’ linguistic and intercultural communicative competences as an indefeasible constituent of their future professional activity. Description of multimodal content both as a linguistic and didactic phenomenon makes the study relevant. The objective of the article is the analysis of creolized texts and the effect they have on fostering higher education students’ skills and their productivity. The main methods used are linguistic text analysis, qualitative and quantitative methods, deduction, generalization. The author studies texts with full and partial creolization, their features and role in composing multimodal textual space. The main verbal and non-verbal markers and paralinguistic means that enhance the linguo-pragmatic potential of creolized texts are covered. To reveal the efficiency of multimodal content application in English teaching, the author conducts an experiment among both undergraduate students and teachers. This allows specifying main functions of creolized texts in the process of language learning, detecting ways of enhancing students’ competences, and increasing their motivation. The described stages of using creolized texts can serve as an algorithm for work with multimodal content in teaching English as a foreign language. The findings contribute to improving the efficiency of the academic process.

Keywords: creolized text, English language learning, higher education, language and communication competences, multimodal content

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Authors: Samer Muthana Sarsam, Abdul Samad Shibghatullah, Chit Su Mon, Abd Aziz Alias, Hosam Al-Samarraie

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Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education. However, their specific role within the educational context and the level of legal support for their implementation remain unclear. Therefore, this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. To achieve this objective, English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the collected tweets. User sentiments, including disgust, surprise, sadness, anger, fear, joy, anticipation, and trust, as well as positive and negative sentiments, were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

Keywords: generative artificial intelligence chatbots, bard, higher education, topic modelling, sentiment analysis

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: Godfrey Muiya Mukala

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This research looks at an array of fields in Sub-Saharan Africa comprising agriculture, food enterprises, medicine, organisms genetically modified, microbiology, and nanotechnology that can be gained from biotechnological research and development. Findings into dangerous organisms, mainly bacterial germs, rickettsia, fungi, parasites, or organisms that are genetically engineered, have immensely posed questions attributed to the biological danger they bring forth to human beings and the environment because of their uncertainties. In addition, the recurrence of previously managed diseases or the inception of new diseases are connected to biosafety challenges, especially in rural set-ups in low and middle-income countries. Notably, biotechnology laboratories are required to adopt biosafety measures to protect their workforce, community, environment, and ecosystem from unforeseen materials and organisms. Sensitization and inclusion of educational frameworks for laboratory workers are essential to acquiring a solid knowledge of harmful biological agents. This is in addition to human pathogenicity, susceptibility, and epidemiology to the biological data used in research and development. This article reviews and analyzes research intending to identify the proper implementation of universally accepted practices in laboratory safety and biological hazards. This research identifies ideal microbiological methods, adequate containment equipment, sufficient resources, safety barriers, specific training, and education of the laboratory workforce to decrease and contain biological hazards. Subsequently, knowledge of standardized microbiological techniques and processes, in addition to the employment of containment facilities, protective barriers, and equipment, is far-reaching in preventing occupational infections. Similarly, reduction of risks and prevention may be attained by training, education, and research on biohazards, pathogenicity, and epidemiology of the relevant microorganisms. In this technique, medical professionals in rural setups may adopt the knowledge acquired from the past to project possible concerns in the future.

Keywords: sub-saharan africa, biotechnology, laboratory, infections, health

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: R. N. Pateriya, T. K. Bhattacharya

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In India, rice-wheat cropping system occupies the major area and contributes about 40% of the country’s total food grain production. It is necessary that production of rice and wheat must keep pace with growing population. However, various factors such as degradation in natural resources, shift in cropping pattern, energy constraints etc. are causing reduction in the productivity of these crops. Seedbed for rice after wheat is difficult to prepare due to presence of straw and stubbles, and require excessive tillage operations to bring optimum tilth. In addition, delayed sowing and transplanting of rice is mainly due to poor crop residue management, multiplicity of tillage operations and non-availability of the power source. With increasing concern for fuel conservation and energy management, farmers might wish to estimate the best cultivation system for more productivity. The widest spread method of tilling land is ploughing with mould board plough. However, with the mould board plough upper layer of soil is neither always loosened at the desired extent nor proper mixing of different layers are achieved. Therefore, additional operations carried out to improve tilth. The farmers are becoming increasingly aware of the need for minimum tillage by minimizing the use of machines. Soil management can be achieved by using the combined active-passive tillage machines. A study was therefore, undertaken in wheat-harvested field to study the impact of conventional and modified tillage practices on paddy crop cultivation. Tillage treatments with tractor as a power source were selected during the experiment. The selected level of tillage treatments of tractor machinery management were (T1:- Direct Sowing of Rice), (T2:- 2 to 3 harrowing and no Puddling with manual transplanting), (T3:- 2 to 3 harrowing and Puddling with paddy harrow with manual transplanting), (T4:- 2 to 3 harrowing and Puddling with Rotavator with manual transplanting). The maximum output was obtained with treatment T1 (7.85 t/ha)) followed by T4 (6.4 t/ha), T3 (6.25 t/ha) and T2 (6.0 t/ha)) respectively.

Keywords: crop residues, cropping system, minimum tillage, yield

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Authors: Kemal Polat

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In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

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Authors: Anamika Choudhary, Neha Qurrat Ain

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Background: Congenital agenesis of uterine cervix is a rare anomaly often associated with partial or complete agenesis of vagina. Here is a case report of a 14 year old girl who presented with primary amenorrhea and cyclical abdominal pain since last one year with suprapubic mass palpable. On examination complete absence of a vagina was found, and ultrasound along with magnetic resonance imaging (MRI) suggested cervicovaginal agenesis associated with cryptomenorrhea, which resulted in hematometra and b/l hematosalpinx with pelvic endometriosis. After proper counseling regarding anastomosis failure and the need for future laprotomy or hysterectomy, the patient planned for laparoscopic uterovaginal anastomosis with modified McIndoe vaginoplasty with split skin graft. Case Summary: Chief complaint: The 14 year old girl presented with primary amenorrhea and cyclical abdominal pain. Diagnosis:On history, examination and investigations we made differential diagnoses of cervicovaginal agenesis, cervicovaginal atresia. Post operatively, we concluded it’s a cervicovaginal agenesis. Intervention: Laparoscopic uterovaginal anastomosis was done, and neovagina was created using split skin graft from the thigh and silicone stent. The graft was kept patent, and restenosis was prevented using a dental mould as vaginal dilator. Outcome: Postoperatively 1 year follow-up has been done. We have observed successful uterovaginal anastomosis and good uptake of graft. We also observed the resumption of normal menstrual bleeding. Currently, there has been no restenosis, abnormal vaginal discharge and decreased dysmenorrhea. Conclusion: Laparoscopic-assisted uterovaginal anastomosis can be the treatment of choice in patients with cervical agenesis and atresia instead of hysterectomy, thereby preserving the reproductive function. This conservative approach has better outcomes, as stated in the procedure below. The procedure is successful insofar as the resumption of menstrual function. However, long-term reproductive outcomes, progression of endometriosis, functioning of fallopian tubes, and sexual life in these girls will require further follow-up.

Keywords: cervicovaginal agenesis, uterovaginal anastomosis, dental mould, silicon stent

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Authors: Lingxiao Yang, Xin Wang, Bo Xu, Zhenqian Chen

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Due to its outstanding environmental performance, higher heating temperature and excellent low-temperature performance, transcritical carbon dioxide (CO₂) heat pumps are receiving more and more attention. However, improperly set operating parameters have a serious negative impact on the performance of the transcritical CO₂ heat pump due to the properties of CO₂. In this study, the heat transfer characteristics of the gas cooler are studied based on the modified “three-stage” gas cooler, then the effect of three operating parameters, compressor speed, gas cooler water-inlet flowrate and gas cooler water-inlet temperature, on the heating process of the system are investigated from the perspective of thermal quality and heat capacity. The results shows that: In the heat transfer process of gas cooler, the temperature distribution of CO₂ and water shows a typical “two region” and “three zone” pattern; The rise in the cooling pressure of CO₂ serves to increase the thermal quality on the CO₂ side of the gas cooler, which in turn improves the heating temperature of the system; Nevertheless, the elevated thermal quality on the CO₂ side can exacerbate the mismatch of heat capacity on both sides of the gas cooler, thereby adversely affecting the system coefficient of performance (COP); Furthermore, increasing compressor speed mitigates the mismatch in heat capacity caused by elevated thermal quality, which is exacerbated by decreasing gas cooler water-inlet flowrate and rising gas cooler water-inlet temperature; As a delegate, the varying compressor speed results in a 7.1°C increase in heating temperature within the experimental range, accompanied by a 10.01% decrease in COP and an 11.36% increase in heating capacity. This study can not only provide an important reference for the theoretical analysis and control strategy of the transcritical CO₂ heat pump, but also guide the related simulation and the design of the gas cooler. However, the range of experimental parameters in the current study is small and the conclusions drawn are not further analysed quantitatively. Therefore, expanding the range of parameters studied and proposing corresponding quantitative conclusions and indicators with universal applicability could greatly increase the practical applicability of this study. This is also the goal of our next research.

Keywords: transcritical CO₂ heat pump, gas cooler, heat capacity, thermal quality

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Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

Procedia PDF Downloads 161

Authors: Sengly Sroy, Elodie Arnaud, Adrien Servent, Sokneang In, Sylvie Avallone

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In Cambodia, fish plays an important role for local community in term of food habits, preference and contribution to several nutritional intakes. Consumed on a daily basis, fishes and their derivatives products are good sources of proteins, essential fatty acids and fat-soluble vitamins. They mainly obtain from the Tonle Sap Lake but, during the last decade, the fish population decreased drastically due to climate change and human activities as well. Contamination by agricultural residues and heavy metals were identified. However, fishes are currently used in several nutrition programs for children and pregnant women to improve their nutritional status. The aim of our work was to characterize the nutritional profile and contamination of 10 fish species consumed near the Tonle Sap Lake with a special attention to fatty acid and fat-soluble vitamin profiles. Fish samples were analyzed for their nutritional profiles (AOAC methods for macronutrients and micronutrients), their lipid content (Folch modified method), their Fatty acid (FAME method), their vitamin A (HPLC) and their heavy metals (ICP-MS). The total lipid contents ranged from 1.43 to 10.00% according to fish species. Lipid profile was mainly dominated by saturated fat (from 47.95 to 57.32%) but some fish species were particularly rich in ω-3 and ω-6 especially eicosapentaenoic acid EPA (3.05%) and docosahexaenoic acid DHA (2.82%). The more the fishes were fats, the more they contained vitamin A, DHA and EPA. Vitamin A is particularly abundant in small fishes (250.10 μg RE/100 g) compare to big ones (13.77 μg RE/100 g) because they are consumed as a whole with their organs (liver) and head. However, the contents of heavy metal in some species are higher than the maximum permitted level (MPL) from codex alimentarius, especially Mn. The results obtained provided important information on the most interesting fish in term of human nutrition and the potential risk of contaminants. The fatty acids are important for child development and pregnant women. These data are useful for supply chain stakeholders and the people in charge of nutrition program.

Keywords: fat-soluble vitamin, fatty acid, freshwater fish, lipid content, Tonle Sap Lake

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Authors: Ambra Giovannelli, Coriolano Salvini

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Many efforts have been spent in the design and development of Concentrated Solar Power (CPS) Plants worldwide. Most of them are for on-grid electricity generation and they are large plants which can benefit from the economies of scale. Nevertheless, several potential applications for Small and Medium-Scale CSP plants can be relevant in the industrial sector as well as for off-grid purposes (i.e. in rural contexts). In a wide range of industrial processes, CSP technologies can be used for heat generation replacing conventional primary sources. For such market, proven technologies (usually hybrid solutions) already exist: more than 100 installations, especially in developing countries, are in operation and performance can be verified. On the other hand, concerning off-grid applications, solar technologies are not so mature. Even if the market offers a potential deployment of such systems, especially in countries where the access to grid is strongly limited, optimized solutions have not been developed yet. In this context, steam power plants can be taken into consideration for medium scale installations, due to the recent results achieved with direct steam generation systems based on paraboloidal dish or Fresnel lens solar concentrators. Steam at 4.0-4.5 MPa and 500°C can be produced directly by means of innovative solar receivers (some prototypes already exist). Although it could seem a promising technology, presently, steam turbines commercially available do not cover the required cycle specifications. In particular, while low-pressure turbines already exist on the market, high-pressure groups, necessary for the abovementioned applications, are not available. The present paper deals with the preliminary design of a high-pressure steam turbine group for a medium-scale CSP plant (200-1000 kWe). Such a group is arranged in a single geared package composed of four radial expander wheels. Such wheels have been chosen on the basis of automotive turbocharging technology and then modified to take the new requirements into account. Results related to the preliminary geometry selection and to the analysis of the high-pressure turbine group performance are reported and widely discussed.

Keywords: concentrated solar power (CSP) plants, steam turbine, radial turbine, medium-scale power plants

Procedia PDF Downloads 217