Search results for: hybrid fiber

Authors: Zory Marantz

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Hybrid flexible (HyFlex) is a pedagogical methodology whereby an instructor delivers content in three modalities, i.e. live in-person (LIP), live online synchronous (LOS), and non-live online asynchronous (nLOaS). HyFlex is focused on providing the largest level of flexibility needed to achieve a cohesive environment across all modalities and incorporating four basic principles – learner’s choice, reusability, accessibility, and equivalency. Much literature has focused on the advantages of this methodology in providing students with the flexibility to choose their learning modality as best suits their schedules and learning styles. Initially geared toward graduate-level students, the concept has been applied to undergraduate studies, particularly during our national pedagogical response to the COVID19 pandemic. There is still little literature about the practicality and feasibility of HyFlex for hardware laboratory intensive engineering technology programs, particularly in dense, urban commuter institutions of higher learning. During a semester of engineering, a lab-based course was taught in the HyFlex modality, and students were asked to complete a survey about their experience. The data demonstrated that there is no single mode that is preferred by a majority of students and the usefulness of any modality is limited to how familiar the student and instructor are with the technology being applied. The technology is only as effective as our understanding and comfort with its functionality. For HyFlex to succeed in its implementation in an engineering technology environment within an urban commuter institution, faculty and students must be properly introduced to the technology being used.

Keywords: education, HyFlex, technology, urban, commuter, pedagogy

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: Mumtaz Khan, Adeel Shahid, Waqas Khan

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Heavy metals presence in water streams is a big danger for aquatic life and ultimately effects human health. Removal of copper (Cu) by ispaghula husk, maize fibre, and maize oil cake from synthetic solution in batch conditions was studied. Different experimental parameters such as contact time, initial solution pH, agitation rate, initial Cu concentration, biosorbent concentration, and biosorbent particle size has been studied to quantify the Cu biosorption. The rate of adsorption of metal ions was very fast at the beginning and became slow after reaching the saturation point, followed by a slower active metabolic uptake of metal ions into the cells. Up to a certain point, (pH=4, concentration of Cu = ~ 640 mg/l, agitation rate = ~ 400 rpm, biosorbent concentration = ~ 0.5g, 3g, 3g for ispaghula husk, maize fiber and maize oil cake, respectively) increasing the pH, concentration of Cu, agitation rate, and biosorbent concentration, increased the biosorption rate; however the sorption capacity increased by decreasing the particle size. At optimized experimental parameters, the maximum Cu biosorption by ispaghula husk, maize fibre and maize oil cake were 86.7%, 59.6% and 71.3%, respectively. Moreover, the results of the kinetics studies demonstrated that the biosorption of copper on ispaghula husk, maize fibre, and maize oil cake followed pseudo-second order kinetics. The results of adsorption were fitted to both the Langmuir and Freundlich models. The Langmuir model represented the sorption process better than Freundlich, and R² value ~ 0.978. Optimizations of physical and environmental parameters revealed, ispaghula husk as more potent copper biosorbent than maize fibre, and maize oil cake. The sorbent is cheap and available easily, so this study can be applied to remove Cu impurities on pilot and industrial scale after certain modifications.

Keywords: biosorption, copper, ispaghula husk, maize fibre, maize oil cake, purification

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Authors: Yogesh C. Sharma, A. Seetharaman

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The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision-making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation, and workplace motivation. Hybrid human-AI systems require the development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.

Keywords: employee decision making, artificial intelligence (AI) environment, human trust, technology innovation, psychological safety

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Authors: Panpan Fan, Bo Ming, Niels Anten, Jochem Evers, Yaoyao Li, Shaokun Li, Ruizhi xie

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Nitrogen (N) utilization for crop production under N deficiency conditions is subject to a trade-off between maintaining specific leaf N content (SLN), important for radiation-use efficiency (RUE), versus maintaining leaf area (LA) development, important for light capture. This paper aims to explore how maize deals with this trade-off through responses in SLN, LA and their underlying traits during the vegetative and reproductive growth stages. In a ten-year N fertilization trial in Jilin province, Northeast China, three N fertilizer levels have been maintained: N-deficiency (N0), low N supply (N1), and high N supply (N2). We analyzed data from years 8 and 10 of this experiment for two common hybrids. Under N deficiency, maize plants maintained LA and decreased SLN during vegetative stages, while both LA and SLN decreased comparably during reproductive stages. Canopy-average specific leaf area (SLA) decreased sharply during vegetative stages and slightly during reproductive stages, mainly because senesced leaves in the lower canopy had a higher SLA. In the vegetative stage, maize maintained leaf area at low N by maintaining leaf biomass (albeit hence having N content/mass) and slightly increasing SLA. These responses to N deficiency were stronger in maize hybrid XY335 than in ZD958. We conclude the main strategy of maize to cope with low N is to maintain plant growth, mainly by increasing SLA throughout the plant during early growth. N was too limiting for either strategy to be followed during later growth stages.

Keywords: leaf N content per unit leaf area, N deficiency, specific leaf area, maize strateg

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Authors: Rowan Moore, Kai Scheffler, Eugen Damoc, Jennifer Sutton, Aaron Bailey, Stephane Houel, Simon Cubbon, Jonathan Josephs

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Purpose: MS analysis of monoclonal antibodies (mAbs) at the protein and peptide levels is critical during development and production of biopharmaceuticals. The compositions of current generation therapeutic proteins are often complex due to various modifications which may affect efficacy. Intact proteins analyzed by MS are detected in higher charge states that also provide more complexity in mass spectra. Protein analysis in native or native-like conditions with zero or minimal organic solvent and neutral or weakly acidic pH decreases charge state value resulting in mAb detection at higher m/z ranges with more spatial resolution. Methods: Three commercially available mAbs were used for all experiments. Intact proteins were desalted online using size exclusion chromatography (SEC) or reversed phase chromatography coupled on-line with a mass spectrometer. For streamlined use of the LC- MS platform we used a single SEC column and alternately selected specific mobile phases to perform separations in either denaturing or native-like conditions: buffer A (20 % ACN, 0.1 % FA) with Buffer B (100 mM ammonium acetate). For peptide analysis mAbs were proteolytically digested with and without prior reduction and alkylation. The mass spectrometer used for all experiments was a commercially available Thermo Scientific™ hybrid Quadrupole-Orbitrap™ mass spectrometer, equipped with the new BioPharma option which includes a new High Mass Range (HMR) mode that allows for improved high mass transmission and mass detection up to 8000 m/z. Results: We have analyzed the profiles of three mAbs under reducing and native conditions by direct infusion with offline desalting and with on-line desalting via size exclusion and reversed phase type columns. The presence of high salt under denaturing conditions was found to influence the observed charge state envelope and impact mass accuracy after spectral deconvolution. The significantly lower charge states observed under native conditions improves the spatial resolution of protein signals and has significant benefits for the analysis of antibody mixtures, e.g. lysine variants, degradants or sequence variants. This type of analysis requires the detection of masses beyond the standard mass range ranging up to 6000 m/z requiring the extended capabilities available in the new HMR mode. We have compared each antibody sample that was analyzed individually with mixtures in various relative concentrations. For this type of analysis, we observed that apparent native structures persist and ESI is benefited by the addition of low amounts of acetonitrile and formic acid in combination with the ammonium acetate-buffered mobile phase. For analyses on the peptide level we analyzed reduced/alkylated, and non-reduced proteolytic digests of the individual antibodies separated via reversed phase chromatography aiming to retrieve as much information as possible regarding sequence coverage, disulfide bridges, post-translational modifications such as various glycans, sequence variants, and their relative quantification. All data acquired were submitted to a single software package for analysis aiming to obtain a complete picture of the molecules analyzed. Here we demonstrate the capabilities of the mass spectrometer to fully characterize homogeneous and heterogeneous therapeutic proteins on one single platform. Conclusion: Full characterization of heterogeneous intact protein mixtures by improved mass separation on a quadrupole-Orbitrap™ mass spectrometer with extended capabilities has been demonstrated.

Keywords: disulfide bond analysis, intact analysis, native analysis, mass spectrometry, monoclonal antibodies, peptide mapping, post-translational modifications, sequence variants, size exclusion chromatography, therapeutic protein analysis, UHPLC

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Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

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This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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Authors: Rodrigo Antunes, Olga Borisevich, David Demange

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The Tritium Laboratory Karlsruhe (TLK) has identified zeolite membranes as most promising for tritium processes in the future fusion reactors. Tritium diluted in purge gases or gaseous effluents, and present in both molecular and oxidized forms, can be pre-concentrated by a stage of zeolite membranes followed by a main downstream recovery stage (e.g., catalytic membrane reactor). Since 2011 several membrane zeolite samples have been tested to measure the membrane performances in the separation of hydrogen and water vapor from helium streams. These experiments were carried out in the ZIMT (Zeolite Inorganic Membranes for Tritium) facility where mass spectrometry and cold traps were used to measure the membranes’ performances. The membranes were tested at temperatures ranging from 25 °C up to 130 °C, at feed pressures between 1 and 3 bar, and typical feed flows of 2 l/min. During this experimental campaign, several zeolite-type membranes were studied: a hollow-fiber MFI nanocomposite membrane purchased from IRCELYON (France), and tubular MFI-ZSM5, NaA and H-SOD membranes purchased from Institute for Ceramic Technologies and Systems (IKTS, Germany). Among these membranes, only the MFI-based showed relevant performances for the H2/He separation, with rather high permeances (~0.5 – 0.7 μmol/sm2Pa for H2 at 25 °C for MFI-ZSM5), however with a limited ideal selectivity of around 2 for H2/He regardless of the feed concentration. Both MFI and NaA showed higher separation performances when water vapor was used instead; for example, at 30 °C, the separation factor for MFI-ZSM5 is approximately 10 and 38 for 0.2% and 10% H2O/He, respectively. The H-SOD evidenced to be considerably defective and therefore not considered for further experiments. In this contribution, a comprehensive analysis of the experimental methods and results obtained for the separation performance of different zeolite membranes during the past four years in inactive environment is given. These results are encouraging for the experimental campaign with molecular and oxidized tritium that will follow in 2017.

Keywords: gas separation, nuclear fusion, tritium processes, zeolite membranes

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Authors: Asaiel Mubark Al Hadi

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Background: A frequent anorectal condition known as hemorrhoids, sometimes known as piles, is characterized by a weakening of the anal cushion and the supporting tissue as well as spasms of the internal sphincter. Hemorrhoids are most frequently identified by painless bright red bleeding, prolapse, annoying grape-like tissue prolapse, itching, or a combination of symptoms. digital rectal examination (DRE) and anoscope are used to diagnose it. Constipation, a low-fiber diet, a high body- mass index (BMI), pregnancy, and a reduced physical activity are among the factors that are typically thought to increase the risk of hemorrhoids. Golighers is the most commonly used hemorrhoid classification scheme It is 4 degrees, which determines the degree of the event. The purpose of this study is to assess knowledge and awareness level of the causes and stages of Hemorrhoids in the public of Saudi Arabia. Method: This cross-sectional study was conducted in the Saudi Arabia between Oct 2022- Dec 2022. The study group included at least 384 aged above 18 years. The outcomes of this study were analyzed using the SPSS program using a pre-tested questionnaire. Results: The study included 1410 participants, 69.9% of them were females and 30.1% were males. 53.7% of participants aged 20- 30 years old. 17% of participants had hemorrhoids and 42% had a relative who had hemorrhoids. 42.8% of participants could identify stage 1 of hemorrhoids correctly, 44.7% identified stage 2 correctly, 46.7% identified stage 3 correctly and 58.1% identified stage 4 correctly. Only 28.9% of participants had high level of knowledge about hemorrhoids, 62.7% had moderate knowledge and 8.4% had low knowledge. Conclusion: In conclusion, Saudi general population has poor knowledge of hemorrhoids, their causes and their management approach. There was a significant association between knowledge scores of hemorrhoids with age, gender, residence area and employment.

Keywords: hemorrhoids, external hemorrhoid, internal hemorrhoid, anal fissure, hemorrhoid stages, prolapse, rectal bleeding

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Authors: K. Almi, S. Lakel, A. Benchabane, A. Kriker

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Several researches are focused on natural resources for the production of biomaterials intended for technical applications. Date palm wood present one of the world’s most important natural resource. Its use as insulating materials will help to solve the severe environmental and recycling problems which other artificial insulating materials caused. This paper reports the results of an experimental investigation on the thermal proprieties of date palm wood from Algeria. A study of physical, chemical, and mechanical properties is also carried out. The goal is to use this natural material in the manufacture of thermal insulation materials for buildings. The local natural resources used in this study are the date palm fibers from Biskra oasis in Algeria. The results have shown that there is no significant difference in the morphological proprieties of the four types of residues. Their chemical composition differed slightly; with the lowest amounts of cellulose and lignin content belong to Petiole. Water absorption study proved that Rachis has a low value of sorption whereas Petiole and Fibrillium have a high value of sorption what influenced their mechanical properties. It is seen that the Rachis and leaflets exhibit high tensile strength values compared to the other residue. On the other hand, the low value of the bulk density of Petiole and Fibrillium leads to a high value of specific tensile strength and young modulus. It was found that the specific young modulus of Petiole and Fibrillium was higher than that of Rachis and Leaflets and that of other natural fibers or even artificial fibers. Compared to the other materials date palm wood provide a good thermal proprieties thus, date palm wood will be a good candidate for the manufacturing efficient and safe insulating materials.

Keywords: composite materials, date palm fiber, natural fibers, tensile tests, thermal proprieties

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Authors: Amine Rezzoug, Selsabil Rokia Laraba, Mourad Ancer, Said Abdi

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Composite materials are taking center stage in different fields thanks to their mechanical characteristics and their ease of preparation. Environmental constraints have led to the development of composite with natural reinforcements. The sandwich structure has the advantage to have good flexural proprieties for low density, which is why it was chosen in this work. The development of these materials is related to an energy saving strategy and environmental protection. The present work refers to the study of the development and characterization of sandwiches composites based on hybrids laminates with natural reinforcements (Alfa and Jute), a metal fabric was introduced into composite in order to have a compromise between weight and properties. We use different configurations of reinforcements (jute, metallic fabric) to develop laminates in order to use them as thin facings for sandwiches materials. While the core was an epoxy matrix reinforced with Alfa short fibers, a chemical treatment sodium hydroxide was cared to improve the adhesion of the Alfa fibers. The mechanical characterization of our materials was made by the tensile and bending test, to highlight the influence of jute and Alfa. After testing, the fracture surfaces are observed by scanning electron microscopy (SEM). Optical microscopy allowed us to calculate the degree of porosity and to observe the morphology of the individual layers. Laminates based on jute fabric have shown better results in tensile test as well as to bending, compared to those of the metallic fabric (100%, 65%). Sandwich Panels were also characterized in terms of bending test. Results we had provide, shows that this composite has sufficient properties for possible replacing conventional composite materials by considering the environmental factors.

Keywords: bending test, bio-composites, sandwiches, tensile test

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Authors: Gabriel Sanjo Aruwajoye, E. B. Gueguim Kana

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Agricultural residues present a low-cost feedstock for bioenergy production around the world. Cassava peels waste are rich in organic molecules that can be readily converted to value added products such as biomaterials and biofuels. However, due to the presence of high proportion of structural carbohydrates and lignin, the hydrolysis of this feedstock is imperative to achieve maximum substrate utilization and energy yield. This study model and optimises the release of Fermentable Sugar (FS) from cassava peels waste using the Response Surface Methodology. The investigated pretreatment input parameters consisted of soaking temperature (oC), soaking time (hours), autoclave duration (minutes), acid concentration (% v/v), substrate solid loading (% w/v) within the range of 30 to 70, 0 to 24, 5 to 20, 0 to 5 and 2 to 10 respectively. The Box-Behnken design was used to generate 46 experimental runs which were investigated for FS release. The obtained data were used to fit a quadratic model. A coefficient of determination of 0.87 and F value of 8.73 was obtained indicating the good fitness of the model. The predicted optimum pretreatment conditions were 69.62 oC soaking temperature, 2.57 hours soaking duration, 5 minutes autoclave duration, 3.68 % v/v HCl and 9.65 % w/v solid loading corresponding to FS yield of 91.83g/l (0.92 g/g cassava peels) thus 58% improvement on the non-optimised pretreatment. Our findings demonstrate an efficient pretreatment model for fermentable sugar release from cassava peels waste for various bioprocesses.

Keywords: feedstock pretreatment, cassava peels, fermentable sugar, response surface methodology

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Authors: Ahmad Afif, Teuku Yuri M. Zagloel

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Sustainable supply chain management is a new pattern that has emerged recently in industry and companies. The procurement process is one of the key factors for efficiency in supply chain management practices. Partnership is one of the procurement strategies for strategic items. The success factors of the partnership must be determined to avoid things that endanger the financial and operational status of the company. The current supplier partnership research focuses on the selection of general criteria and sustainable supplier selection. Currently, there is still limited research on the success factors of supplier partnerships that focus on strategic items in the coal mining industry. Meanwhile, the procurement of coal mining has its own characteristics, and there are regulations related to the procurement of goods. Therefore, this research was conducted to determine the categories of goods that are included in the strategic items and to design the success factors of supplier partnerships. The main factors studied are general, financial, production, reputation, synergies, and sustainable. The research was conducted using the Kraljic method to determine the categories of goods that are included in the strategic items. To design a supplier partnership success factor using the Hybrid Multi Criteria Decision Making method. Integrated Fuzzy AHP-Fuzzy TOPSIS is used to determine the weight of the success factors of supplier partnerships and to rank suppliers on the factors used.

Keywords: supplier, partnership, strategic item, success factors, and coal mining industry

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Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

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Authors: Sinsze Koo, Benjin Luo, Matthew Henry

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In order to increase the performance of an automatic transmission, the automatic transmission fluid is required to be warm up to an optimal operating temperature. In a conventional vehicle, cold starts result in friction loss occurring in the gear box and engine. The stop and go nature of city driving dramatically affect the warm-up of engine oil and automatic transmission fluid and delay the time frame needed to reach an optimal operating temperature. This temperature phenomenon impacts both engine and transmission performance but also increases fuel consumption and CO2 emission. The aim of this study is to develop know-how of the thermal behavior in order to identify thermal impacts and functional principles in automatic transmissions. Thermal behavior was studied using models and simulations, developed using GT-Suit, on a one-dimensional thermal and flow transport. A power train of a conventional vehicle was modeled in order to emphasis the thermal phenomena occurring in the various components and how they impact the automatic transmission performance. The simulation demonstrates the thermal model of a transmission fluid cooling system and its component parts in warm-up after a cold start. The result of these analyses will support the future designs of transmission systems and components in an attempt to obtain better fuel efficiency and transmission performance. Therefore, these thermal analyses could possibly identify ways that improve existing thermal management techniques with prioritization on fuel efficiency.

Keywords: thermal management, automatic transmission, hybrid, and systematic approach

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Authors: Anna Ivanovskaya, Alexandra E. L. Overland, Swetha Chandrasekaran, Buddhinie S. Jayathilake

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Iron-based redox flow batteries (IRFB) are promising for grid-scale storage because of their low-cost and environmental safety. Earth-abundant iron can enable affordable grid-storage to meet DOE’s target material cost <$20/kWh and levelized cost for storage $0.05/kWh. In conventional redox flow batteries, energy is stored in external electrolyte tanks and electrolytes are circulated through the cell units to achieve electrochemical energy conversions. However, IRFBs are hybrid battery systems where metallic iron deposition at the negative side of the battery controls the storage capacity. This adds complexity to the design of a porous structure of 3D-electrodes to achieve a desired high storage capacity. In addition, there is a need to control parasitic hydrogen evolution reaction which accompanies the metal deposition process, increases the pH, lowers the energy efficiency, and limits the durability. To achieve sustainable operation of IRFBs, electrolyte pH, which affects the solubility of reactants and the rate of parasitic reactions, needs to be dynamically readjusted. In the present study we explore the impact of complexing agents on maintaining solubility of the reactants and find the optimal electrolyte conditions and battery operating regime, which are specific for IRFBs with additives, and demonstrate the robust operation.

Keywords: flow battery, iron-based redox flow battery, IRFB, energy storage, electrochemistry

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Authors: Sapan Bhatnagar

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Micron size particles emitted from different sources and produced by combustion have serious negative effects on human health and environment. They can penetrate deep into our lungs through the respiratory system. Determination of the amount of particulates present in the atmosphere per cubic meter is necessary to monitor, regulate and model atmospheric particulate levels. Cascade impactor is used to collect the atmospheric particulates and by gravimetric analysis, their concentration in the atmosphere of different size ranges can be determined. Cascade impactors have been used for the classification of particles by aerodynamic size. They operate on the principle of inertial impaction. It consists of a number of stages each having an impaction plate and a nozzle. Collection plates are connected in series with smaller and smaller cutoff diameter. Air stream passes through the nozzle and the plates. Particles in the stream having large enough inertia impact upon the plate and smaller particles pass onto the next stage. By designing each successive stage with higher air stream velocity in the nozzle, smaller diameter particles will be collected at each stage. Particles too small to be impacted on the last collection plate will be collected on a backup filter. Impactor consists of 4 stages each made of steel, having its cut-off diameters less than 10 microns. Each stage is having collection plates, soaked with oil to prevent bounce and allows the impactor to function at high mass concentrations. Even after the plate is coated with particles, the incoming particle will still have a wet surface which significantly reduces particle bounce. The particles that are too small to be impacted on the last collection plate are then collected on a backup filter (microglass fiber filter), fibers provide larger surface area to which particles may adhere and voids in filter media aid in reducing particle re-entrainment.

Keywords: aerodynamic diameter, cascade, environment, particulates, re-entrainment

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Authors: Mirvat Shamseddine, Issam Lakkis

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We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.

Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows

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Authors: Saad Chahba, Rabia Sehab, Ahmad Akrad, Cristina Morel

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Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit (OC) fault diagnosis, artificial neural network

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Authors: Gramza-Michalowska Anna, Skrety Joanna, Kobus-Cisowska Joanna, Kmiecik Dominik, Korczak Jozef, Anna Zywica

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Background: Recent research presented many evidences confirming that food besides its basic nutritional function, possess significant therapeutic and prophylactic potential. Conscious consumer is aware of diet habits and well being lifestyle influencing a proper functioning that is why there is a need of new pro-health products. Objective: Proposition of the technology of unsweetened almond drinks enriched with plant extracts for pro-health oriented individuals. Research investigated the influence of selected plant extracts addition on antioxidative activity and consumer’s acceptance of drinks as all day diet product representatives. Methods: The analysis of the basic composition and antioxidant properties of the almond drink was conducted. Research included analysis of basic composition (protein, lipids and fiber content) and antioxidant capacity of drink (DPPH, ABTS, ORAC value, and FRAP). Proposed drink was also characterized with sensory analysis, including color, aroma, taste, consistency, and overall acceptance. Results: Results showed that addition of plant extracts into an almond drink allowed to improve its antioxidant capacity and sensory value of the drinks. Profitable composition and pro-health properties of designed drink permits offering healthy product for all day consumption. Conclusion: Designed almond drink would be a significant supplement for pro-healthy life style of the consumers. Results showed that plant extracts enriched almond drink would be a good source of antioxidants and accepted by the consumers.

Keywords: phytonutrients, pro-health, almond, wellbeing, antioxidant potential, sensory value

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Authors: S. O. Ayansina, R. A. Oyeyinka, K. K. Bolarinwa

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There is an increasing demand for a functional extension delivery services in Nigeria with a view to meet up with the food and fiber needs of the ever growing population of human and animal respectively. This study was designed to examine farmers’ involvement in public and private extension services in southwestern Nigeria, specifically to explore the farmers’ participation in the two types of organizations involved. It also evaluates the performances of personnel in the organizations. A multi-stage random sampling technique was used to select 30 respondents from each of the three selected organizations in Ogun, Osun and Oyo states in Southwestern Nigeria. Data was collected with interview schedule and analyzed both at descriptive and inferential levels. Kruskal Wallis one-way Analysis of variance was used to test the differences between the participation of beneficiaries who are farmers under the public and private extension services and the level of benefit accrued to them from the various extension organizations involved in the study. Results revealed that private extension organizations were performing better and were more preferred by the beneficiaries. Results of the tested hypotheses as shown by Kruskal Wallis test of difference (x2 = 0.709) S no significant difference between farmers’ participation in the extension services of public and private organizations but however showed significant difference (X2 =12.074) in the benefits achieved by respondents in the two organizations. These include: increased quantity of crop produced, farm income, skill acquisition, and improved education in private extension organizations. Based on this result, it could be inferred that beneficiaries generally preferred private extension organizations because of their effectiveness and vibrancy in programme administration. Public extension is therefore recommended for general overhauling and possibly privatization in order to cater for teeming population of farmers demanding for efficient and functional extension services to better their lots in production, processing and marketing of agricultural produce.

Keywords: public and private involvement, extension services, farmers' participation

Procedia PDF Downloads 375

Authors: Tie-Gang Wang, De-Qiang Meng, Yan-Mei Liu

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Ternary AlCrN coatings were widely used to prolong cutting tool life because of their high hardness and excellent abrasion resistance. However, the friction between the workpiece and cutter surface was increased remarkably during machining difficult-to-cut materials (such as superalloy, titanium, etc.). As a result, a lot of cutting heat was generated and cutting tool life was shortened. In this work, an appropriate amount of solid lubricant MoS₂ was added into the AlCrN coating to reduce the friction between the tool and the workpiece. A series of Al-Cr-N/MoS₂ self-lubricating coatings with different MoS₂ contents were prepared by high power impulse magnetron sputtering (HiPIMS) and pulsed direct current magnetron sputtering (Pulsed DC) compound system. The MoS₂ content in the coatings was changed by adjusting the sputtering power of the MoS₂ target. The composition, structure and mechanical properties of the Al-Cr-N/MoS2 coatings were systematically evaluated by energy dispersive spectrometer, scanning electron microscopy, X-ray photoelectron spectroscopy, X-ray diffractometer, nano-indenter tester, scratch tester, and ball-on-disk tribometer. The results indicated the lubricant content played an important role in the coating properties. As the sputtering power of the MoS₂ target was 0.1 kW, the coating possessed the highest hardness 14.1GPa, the highest critical load 44.8 N, and the lowest wear rate 4.4×10−3μm2/N.

Keywords: self-lubricating coating, Al-Cr-N/MoS₂ coating, wear rate, friction coefficient

Procedia PDF Downloads 101

Authors: G. K. Sruthi, Sila Bhattacharya

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Sorghum is an important food crop in the dry tropical areas of the world, and possesses significant levels of phytochemicals and dietary fiber to offer health benefits. However, the absence of gluten is a limitation for converting the sorghum dough into sheeted/flattened/rolled products. Chapathi/roti (flat unleavened bread prepared conventionally from whole wheat flour dough) was attempted from sorghum as wheat gluten causes allergic reactions leading to celiac disease. Dynamic oscillatory rheology of sorghum flour dough (control sample) and enzyme treated sorghum doughs were studied and linked to the attributes of the finished ready-to-eat product. Enzymes like amylase, xylanase, and a mix of amylase and xylanase treated dough affected drastically the rheological behaviour causing a lowering of dough consistency. In the case of amylase treated dough, marked decrease of the storage modulus (G') values from 85513 Pa to 23041 Pa and loss modulus (G") values from 8304 Pa to 7370 Pa was noticed while the phase angle (δ) increased from 5.6 to 10.1o for treated doughs. There was a 2 and 3 fold increase in the total sugar content after α-amylase and xylanase treatment, respectively, with simultaneous changes in the structure of the dough and finished product. Scanning electron microscopy exhibited enhanced extent of changes in starch granules. Amylase and mixed enzyme treatment produced a sticky dough which was difficult to roll/flatten. The dough handling properties were improved by the use of xylanase and quality attributes of the chapath/roti. It is concluded that enzyme treatment can offer improved rheological status of gluten free doughs and products.

Keywords: sorghum dough, amylase, xylanase, dynamic oscillatory rheology, sensory assessment

Procedia PDF Downloads 373

Authors: Jung-Il Kang, Jeon Eon Park, Yu-Jin Moon, Young-Seok Ahn, Eun-Sook Yoo, Hee-Kyoung Kang

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This study was conducted to evaluate the effect of Undariopsis peterseniana, a seaweed native to Jeju Island, Korea, on the growth of hair. The dermal papilla cells (DPCs) have known to regulate hair growth cycle and length of hair follicle through interact with epithelial cells. When immortalized vibrissa DPCs were treated with the U. peterseniana extract, the U. peterseniana extract significantly increased the proliferation of DPCs. The effect of U. peterseniana extract on the growth of vibrissa follicles was also examined. U. peterseniana extract significantly increased the hair-fiber lengths of the vibrissa follicles. Hair loss is partly caused by dihydrotestosterone (DHT) binding to androgen receptor in hair follicles, and the inhibition of 5α-reductase activity can prevent hair loss through the decrease of DHT level. The U. peterseniana extract inhibited 5α-reductase activity. Minoxidil, a potent hair-growth agent, can induce proliferation in NIH3T3 fibroblasts by opening KATP channels. We thus examined the proliferative effects of U. peterseniana extract in NIH3T3 fibroblasts. U. peterseniana extract significantly increased the proliferation of NIH3T3 fibroblasts. Tetraethylammonium chloride (TEA), a K+ channel blocker, inhibited U. peterseniana-induced proliferation in NIH3T3 fibroblasts. These results suggest that U. peterseniana could have the potential to treat alopecia through the proliferation of DPCs, the inhibition of 5α-reductase activity and the opening of KATP channels. [Acknowledgement] This research was supported by The Leading Human Resource Training Program of Regional Neo industry through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and future Planning (2016H1D5A1908786).

Keywords: hair growth, Undariopsis peterseniana, vibrissa follicles, dermal papilla cells, 5α-reductase, KATP channels

Procedia PDF Downloads 268

Authors: Asnate Kirse, Daina Karklina, Sandra Muizniece-Brasava, Ruta Galoburda

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Pulses are high in plant protein and dietary fiber, and contain slowly digestible starches. Innovative products from pulses could increase their consumption and benefit consumer health. This study was conducted to evaluate physicochemical stability of processed cowpea (Vigna unguiculata (L.) Walp. cv. Fradel) and maple pea (Pisum sativum var. arvense L. cv. Bruno) spreads at 5 °C temperature during 62-day storage. Physicochemical stability of pulse spreads was compared after sous vide treatment (80 °C/15 min) and high pressure processing (700 MPa/10 min/20 °C). Pulse spreads were made by homogenizing cooked pulses in a food processor together with salt, citric acid, oil, and bruschetta seasoning. A total of four different pulse spreads were studied: Cowpea spread without and with seasoning, maple pea spread without and with seasoning. Transparent PA/PE and light proof PET/ALU/PA/PP film pouches were used for packaging of pulse spreads under vacuum. The parameters investigated were pH, water activity and mass losses. Pulse spreads were tested on days 0, 15, 29, 42, 50, 57 and 62. The results showed that sous-vide treatment and high pressure processing had an insignificant influence on pH, water activity and mass losses after processing, irrespective of packaging material did not change (p>0.1). pH and water activity of sous-vide treated and high pressure processed pulse spreads in different packaging materials proved to be stable throughout the storage. Mass losses during storage accounted to 0.1% losses. Chosen sous-vide treatment and high pressure processing regimes and packaging materials are suitable to maintain consistent physicochemical quality of the new products during 62-day storage.

Keywords: cowpea, flexible packaging, maple pea, water activity

Procedia PDF Downloads 253

Authors: Eric Yi-Hsiu Huang, Meng-Chun Kao, Wen-Chuan Kuo

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For every laparoscopic surgery, a safe pneumoperitoneumcreation (gaining access to the peritoneal cavity) is the first and essential step. However, closed pneumoperitoneum is usually obtained by blind insertion of a Veress needle into the peritoneal cavity, which may carry potential risks suchas bowel and vascular injury.Until now, there remains no definite measure to visually confirm the position of the needle tip inside the peritoneal cavity. Therefore, this study established an image-guided Veress needle method by combining a fiber probe with optical coherence tomography (OCT). An algorithm was also proposed for determining the exact location of the needle tip through the acquisition of OCT images. Our method not only generates a series of “live” two-dimensional (2D) images during the needle puncture toward the peritoneal cavity but also can eliminate operator variation in image judgment, thus improving peritoneal access safety. This study was approved by the Ethics Committee of Taipei Veterans General Hospital (Taipei VGH IACUC 2020-144). A total of 2400 in vivo OCT images, independent of each other, were acquired from experiments of forty peritoneal punctures on two piglets. Characteristic OCT image patterns could be observed during the puncturing process. The ROC curve demonstrates the discrimination capability of these quantitative image features of the classifier, showing the accuracy of the classifier for determining the inside vs. outside of the peritoneal was 98% (AUC=0.98). In summary, the present study demonstrates the ability of the combination of our proposed automatic identification method and OCT imaging for automatically and objectively identifying the location of the needle tip. OCT images translate the blind closed technique of peritoneal access into a visualized procedure, thus improving peritoneal access safety.

Keywords: pneumoperitoneum, optical coherence tomography, automatic identification, veress needle

Procedia PDF Downloads 97

Authors: Waqas Shafqat Chattha, Muhammad Iqbal, Amir Shakeel

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Transcriptional factors are proteins that play a vital role in regulating the transcription of target genes in different biological processes and are being widely studied in different plant species. In the current era of genomics, plant genomes sequencing has directed to the genome-wide identification, analyses and categorization of diverse transcription factor families and hence provide key insights into their structural as well as functional diversity. The DNA-binding with One Finger (DOF) proteins belongs to C2-C2-type zinc finger protein family. DOF proteins are plant-specific transcription factors implicated in diverse functions including seed maturation and germination, phytohormone signalling, light-mediated gene regulation, cotton-fiber elongation and responses of the plant to biotic as well as abiotic stresses. In this context, a genome-wide in-silico analysis of DOF TF family in diploid cotton species i.e. Gossypium raimondii has enabled us to identify 55 non-redundant genes encoding DOF proteins renamed as GrDofs (Gossypium raimondii Dof). Gene distribution studies have shown that all of the GrDof genes are unevenly distributed across 12 out of 13 G. raimondii chromosomes. The gene structure analysis illustrated that 34 out of 55 GrDof genes are intron-less while remaining 21 genes have a single intron. Protein sequence-based phylogenetic analysis of putative 55 GrDOFs has divided these proteins into 5 major groups with various paralogous gene pairs. Molecular evolutionary studies aided with the conserved domain as well as gene structure analysis suggested that segmental duplications were the principal contributors for the expansion of Dof genes in G. raimondii.

Keywords: diploid cotton , G. raimondii, phylogenetic analysis, transcription factor

Procedia PDF Downloads 119

Authors: R. Chedid, R. Ghajar

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Lebanon electricity crisis continues to escalate. Rationing hours still apply across the country but with different rates. The capital Beirut is subjected to 3 hours cut while other cities, town and villages may endure 9 to 14 hours of power shortage. To mitigate this situation, private diesel generators distributed illegally all over the country are being used to bridge the gap in power supply. Almost each building in large cities has its own generator and individual villages may have more than one generator supplying their loads. These generators together with their private networks form incomplete and ill-designed and managed microgrids (MG) but can be further developed to become renewable energy-based MG operating in island- or grid-connected modes. This paper will analyze the potential of introducing MG to help resolve the energy crisis in Lebanon. It will investigate the usefulness of developing MG under the prevailing situation of existing private power supply service providers and in light of the developed national energy policy that supports renewable energy development. A case study on a distribution feeder in a rural area will be analyzed using HOMER software to demonstrate the usefulness of introducing photovoltaic (PV) arrays along the existing diesel generators for all the stakeholders; namely, the developers, the customers, the utility and the community at large. Policy recommendations regarding MG development in Lebanon will be presented on the basis of the accumulated experience in private generation and the privatization and public-private partnership laws.

Keywords: decentralized systems, distributed generation, microgrids, renewable energy

Procedia PDF Downloads 109

Authors: Marinos Xagoraris, Elisavet Lazarou, Eleftherios Alissandrakis, Christos S. Pappas, Petros A. Tarantilis

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Strawberry tree (Arbutus unedo L.) and autumn heather (Erica manipuliflora Salisb.) are important beekeeping plants of Greece. Six monofloral honeys (four strawberry tree, two autumn heather) were analyzed by means of Solid Phase Micro-Extraction (SPME, 60 min, 60 oC) followed by Gas Chromatography coupled to Mass Spectrometry (GC-MS) for the purpose of assessing the botanical origin. A Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) fiber was employed, and benzophenone was used as internal standard. The volatile compounds with higher concentration (μg/ g of honey expressed as benzophenone) from strawberry tree honey samples, were α-isophorone (2.50-8.12); 3,4,5-trimethyl-phenol (0.20-4.62); 2-hydroxy-isophorone (0.06-0.53); 4-oxoisophorone (0.38-0.46); and β-isophorone (0.02-0.43). Regarding heather honey samples, the most abundant compounds were 1-methoxy-4-propyl-benzene (1.22-1.40); p-anisaldehyde (0.97-1.28); p-anisic acid (0.35-0.58); 2-furaldehyde (0.52-0.57); and benzaldehyde (0.41-0.56). Norisoprenoids are potent floral markers for strawberry-tree honey. β-isophorone is found exclusively in the volatile fraction of this type of honey, while also α-isophorone, 4-oxoisophorone and 2-hydroxy-isophorone could be considered as additional marker compounds. The analysis of autumn heather honey revealed that phenolic compounds are the most abundant and p-anisaldehyde; 1-methoxy-4-propyl-benzene; and p-anisic acid could serve as potent marker compounds. In conclusion, marker compounds for the determination of the botanical origin for these honeys could be identified as several norisoprenoids and phenolic components were found exclusively or in higher concentrations compared to common Greek honey varieties.

Keywords: SPME/GC-MS, volatile compounds, heather honey, strawberry tree honey

Procedia PDF Downloads 163