Search results for: energy performance certificate EPBD

Authors: Xabier Barandiaran, Igone Guerra

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The economic and financial crisis that hit European countries in 2008 revealed the inability of governments to respond unilaterally to the so-called “wicked” problems that affect our societies. Closely linked to this, the increasing disaffection of citizens towards politics has resulted in growing distrust of the citizenry not only in the institutions in general but also in the political system, in particular. Precisely, these two factors provoked the action of the local government of Gipuzkoa (Basque Country) to move from old ways of “doing politics” to a new way of “thinking politics” based on a collaborative approach, in which innovative modes of public decision making are prominent. In this context, in 2015, the initiative Etorkizuna Eraikiz (Building the Future), a contemporary form of networked governance, was launched by the Provincial Government. The paper focuses on the Etorkizuna Eraikiz initiative, a sound commitment from a local government to build jointly with the citizens the future of the territory. This paper will present preliminary results obtained from three different experiences of co-creation developed within Etorkizuna Eraikiz in which the formulation of networked governance is a mandatory pre-requisite. These experiences show how the network building approach among the different agents of the territory as well as the co-creation of public policies is the cornerstone of this challenging mission. Through the analysis of the information and documentation gathered during the four years of Etorkizuna-Eraikiz, and, specifically by delving into the strategy promoted by the initiative, some emerging analytical conclusions resulting from the promotion of this collaborative culture will be presented. For example, some preliminary results have shown a significant positive relationship between shared leadership and the formulation of the public good. In the period 2016-2018, a total of 73 projects were launched and funding by the Provincial Government of Gipuzkoa within the Etorkizuna Eraikiz initiative, that indicates greater engagement of the citizenry in the process of policy-making and therefore improving, somehow, the quality of the public policies. These statements have been supported by the last survey about the perspectives of the citizens toward politics and policies. Some of the more prominent results show us that there is still a high level of distrust in Politics (78,9% of respondents) but a greater trust in institutions such the Political Government of Gipuzkoa (40,8% of respondents declared as “good” the performance of this provincial institution). Regarding the Etorkizuna Eraikiz Initiative, it is being more readily recognized by citizens over this period of time (25,4% of the respondents in June 2018 agreed to know about the initiative giving it a mark of 5,89 ) and thus build trust and a sense of ownership. Although, there is a clear requirement for further research on the linkages between collaborative governance and level of trust, the paper, based on these findings, will provide some managerial and theoretical implications for collaborative governance in the territory.

Keywords: network governance, collaborative governance, public sector innovation, citizen participation, trust

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Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

Procedia PDF Downloads 80

Authors: Vanessa Roulet, Marc Turini, Juliane Hey, Stéphanie Bord-Romeu, Emilie Bonzom, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Vanessa Viotti, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. has recently developed fully automated assays for the detection of HBsAg on a new immunoassay platform. The objective of this European multicenter study was to evaluate the performance of the ACCESS HBsAg and ACCESS HBsAg Confirmatory assays† on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer. Methods: The clinical specificity of the ACCESS HBsAg and HBsAg Confirmatory assays was determined using HBsAg-negative samples from blood donors and hospitalized patients. The clinical sensitivity was determined using presumed HBsAg-positive samples. Sample HBsAg status was determined using a CE-marked HBsAg assay (Abbott ARCHITECT HBsAg Qualitative II, Roche Elecsys HBsAg II, or Abbott PRISM HBsAg assay) and a CE-marked HBsAg confirmatory assay (Abbott ARCHITECT HBsAg Qualitative II Confirmatory or Abbott PRISM HBsAg Confirmatory assay) according to manufacturer package inserts and pre-determined testing algorithms. False initial reactive rate was determined on fresh hospitalized patient samples. The sensitivity for the early detection of HBV infection was assessed internally on thirty (30) seroconversion panels. Results: Clinical specificity was 99.95% (95% CI, 99.86 – 99.99%) on 6047 blood donors and 99.71% (95%CI, 99.15 – 99.94%) on 1023 hospitalized patient samples. A total of six (6) samples were found false positive with the ACCESS HBsAg assay. None were confirmed for the presence of HBsAg with the ACCESS HBsAg Confirmatory assay. Clinical sensitivity on 455 HBsAg-positive samples was 100.00% (95% CI, 99.19 – 100.00%) for the ACCESS HBsAg assay alone and for the ACCESS HBsAg Confirmatory assay. The false initial reactive rate on 821 fresh hospitalized patient samples was 0.24% (95% CI, 0.03 – 0.87%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS HBsAg assay had equivalent sensitivity performances compared to the Abbott ARCHITECT HBsAg Qualitative II assay with an average bleed difference since first reactive bleed of 0.13. All bleeds found reactive in ACCESS HBsAg assay were confirmed in ACCESS HBsAg Confirmatory assay. Conclusion: The newly developed ACCESS HBsAg and ACCESS HBsAg Confirmatory assays from Beckman Coulter have demonstrated high clinical sensitivity and specificity, equivalent to currently marketed HBsAg assays, as well as a low false initial reactive rate. †Pending achievement of CE compliance; not yet available for in vitro diagnostic use. 2023-11317 Beckman Coulter and the Beckman Coulter product and service marks mentioned herein are trademarks or registered trademarks of Beckman Coulter, Inc. in the United States and other countries. All other trademarks are the property of their respective owners.

Keywords: dxi 9000 access immunoassay analyzer, hbsag, hbv, hepatitis b surface antigen, hepatitis b virus, immunoassay

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Authors: Adriana De Serio, Adrian Korek

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Aims: This experiential research work presents a Group-MusicTherapy-Theatre-Plan (MusThePlan) the authors have carried out to support the actors. The MusicTherapy gives rise to individual psychophysical feedback and influences the emotional centres of the brain and the subconsciousness. Therefore, the authors underline the effectiveness of the preventive, educational, and training goals of the MusThePlan to lead theatre students and actors to deal with anxiety and to overcome psychophysical weaknesses, shyness, emotional stress in stage performances, to increase flexibility, awareness of one's identity and resources for a positive self-development and psychophysical health, to develop and strengthen social bonds, increasing a network of subjects working for social inclusion and reduction of stigma. Materials-Methods: Thirty students from the University Theatre Faculty participated in weekly music therapy sessions for two months; each session lasted 120 minutes. MusThePlan: Each session began with a free group rhythmic-sonorous-musical-production by body-percussion, voice-canto, instruments, to stimulate communication. Then, a synchronized-structured bodily-rhythmic-sonorous-musical production also involved acting, dances, movements of hands and arms, hearing, and more sensorial perceptions and speech to balance motor skills and the muscular tone. Each student could be the director-leader of the group indicating a story to inspire the group's musical production. The third step involved the students in rhythmic speech and singing drills and in vocal exercises focusing on the musical pitch to improve the intonation and on the diction to improve the articulation and lead up it to an increased intelligibility. At the end of each musictherapy session and of the two months, the Musictherapy Assessment Document was drawn up by analysis of observation protocols and two Indices by the authors: Patient-Environment-Music-Index (time to - tn) to estimate the behavior evolution, Somatic Pattern Index to monitor subject’s eye and mouth and limb motility, perspiration, before, during and after musictherapy sessions. Results: After the first month, the students (non musicians) learned to play percussion instruments and formed a musical band that played classical/modern music on the percussion instruments with the musictherapist/pianist/conductor in a public concert. At the end of the second month, the students performed a public musical theatre show, acting, dancing, singing, and playing percussion instruments. The students highlighted the importance of the playful aspects of the group musical production in order to achieve emotional contact and harmony within the group. The students said they had improved kinetic and vocal and all the skills useful for acting activity and the nourishment of the bodily and emotional balance. Conclusions: The MusThePlan makes use of some specific MusicTherapy methodological models, techniques, and strategies useful for the actors. The MusThePlan can destroy the individual "mask" and can be useful when the verbal language is unable to undermine the defense mechanisms of the subject. The MusThePlan improves actor’s psychophysical activation, motivation, gratification, knowledge of one's own possibilities, and the quality of life. Therefore, the MusThePlan could be useful to carry out targeted interventions for the actors with characteristics of repeatability, objectivity, and predictability of results. Furthermore, it would be useful to plan a University course/master in “MusicTherapy for the Theatre”.

Keywords: musictherapy, sonorous-musical energy, quality of life, theatre

Procedia PDF Downloads 79

Authors: Elizaveta Korzhova, Sebastien Deon, Patrick Fievet, Dmitry Lopatin, Oleg Baranov

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Filtration with nanoporous ultrafiltration membranes is an attractive option to remove ionic pollutants from contaminated effluents. Unfortunately, commercial membranes are not necessarily suitable for specific applications, and their modification by polymer deposition is a fruitful way to adapt their performances accordingly. Many methods are usually used for surface modification, but a novel technique based on electrospray is proposed here. Various quantities of polymers were deposited on a commercial membrane, and the impact of the deposit is investigated on filtration performances and discussed in terms of charge and hydrophobicity. The electrospray deposition is a technique which has not been used for membrane modification up to now. It consists of spraying small drops of polymer solution under a high voltage between the needle containing the solution and the metallic support on which membrane is stuck. The advantage of this process lies in the small quantities of polymer that can be coated on the membrane surface compared with immersion technique. In this study, various quantities (from 2 to 40 μL/cm²) of solutions containing two charged polymers (13 mmol/L of monomer unit), namely polyethyleneimine (PEI) and polystyrene sulfonate (PSS), were sprayed on a negatively charged polyethersulfone membrane (PLEIADE, Orelis Environment). The efficacy of the polymer deposition was then investigated by estimating ion rejection, permeation flux, zeta-potential and contact angle before and after the polymer deposition. Firstly, contact angle (θ) measurements show that the surface hydrophilicity is notably improved by coating both PEI and PSS. Moreover, it was highlighted that the contact angle decreases monotonously with the amount of sprayed solution. Additionally, hydrophilicity enhancement was proved to be better with PSS (from 62 to 35°) than PEI (from 62 to 53°). Values of zeta-potential (ζ were estimated by measuring the streaming current generated by a pressure difference on both sides of a channel made by clamping two membranes. The ζ-values demonstrate that the deposits of PSS (negative at pH=5.5) allow an increase of the negative membrane charge, whereas the deposits of PEI (positive) lead to a positive surface charge. Zeta-potentials measurements also emphasize that the sprayed quantity has little impact on the membrane charge, except for very low quantities (2 μL/m²). The cross-flow filtration of salt solutions containing mono and divalent ions demonstrate that polymer deposition allows a strong enhancement of ion rejection. For instance, it is shown that rejection of a salt containing a divalent cation can be increased from 1 to 20 % and even to 35% by deposing 2 and 4 μL/cm² of PEI solution, respectively. This observation is coherent with the reversal of the membrane charge induced by PEI deposition. Similarly, the increase of negative charge induced by PSS deposition leads to an increase of NaCl rejection from 5 to 45 % due to electrostatic repulsion of the Cl- ion by the negative surface charge. Finally, a notable fall in the permeation flux due to the polymer layer coated at the surface was observed and the best polymer concentration in the sprayed solution remains to be determined to optimize performances.

Keywords: ultrafiltration, electrospray deposition, ion rejection, permeation flux, zeta-potential, hydrophobicity

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Authors: Patrizia Firmani, Sara Perucchini, Irene Rapone, Raffella Borrelli, Stefano Chiaberge, Manuela Grande, Rosamaria Marrazzo, Alberto Savoini, Andrea Siviero, Silvia Spera, Fabio Vago, Davide Deriu, Sergio Fanutti, Alessandro Oldani

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According to the Renewable Energy Directive II, the use of palm oil in diesel will be gradually reduced from 2023 and should reach zero in 2030 due to the deforestation caused by its production. Eni aims at finding alternative feedstocks for its biorefineries to eliminate the use of palm oil by 2023. Therefore, the ideal vegetable oils to be used in bio-refineries are those obtainable from plants that grow in marginal lands and with low impact on food-and-feed chain; hence, Eni research is studying the possibility of using oleaginous seeds, such as castor, croton, and cotton, to extract the oils to be exploited as feedstock in bio-refineries. To verify their suitability for the upgrading processes, an analytical protocol for their characterization has been drawn up and applied. The analytical characterizations include a step of water and ashes content determination, elemental analysis (CHNS analysis, X-Ray Fluorescence, Inductively Coupled Plasma - Optical Emission Spectroscopy, ICP– Mass Spectrometry), and total acid number determination. Gas chromatography coupled to flame ionization detector (GC-FID) is used to quantify the lipid content in terms of free fatty acids, mono-, di- and triacylglycerols, and fatty acids composition. Eventually, Nuclear Magnetic Resonance and Fourier Transform-Infrared spectroscopies are exploited with GC-MS and Fourier Transform-Ion Cyclotron Resonance to study the composition of the oils. This work focuses on the GC-FID analysis of the lipid fraction of these oils, as the main constituent and of greatest interest for bio-refinery processes. Specifically, the lipid component of the extracted oil was quantified after sample silanization and transmethylation: silanization allows the elution of high-boiling compounds and is useful for determining the quantity of free acids and glycerides in oils, while transmethylation leads to a mixture of fatty acid esters and glycerol, thus allowing to evaluate the composition of glycerides in terms of Fatty Acids Methyl Esters (FAME). Cotton oil was extracted from cotton oilcake, croton oil was obtained by seeds pressing and seeds and oilcake ASE extraction, while castor oil comes from seed pressing (not performed in Eni laboratories). GC-FID analyses reported that the cotton oil is 90% constituted of triglycerides and about 6% diglycerides, while free fatty acids are about 2%. In terms of FAME, C18 acids make up 70% of the total and linoleic acid is the major constituent. Palmitic acid is present at 17.5%, while the other acids are in low concentration (<1%). Both analyzes show the presence of non-gas chromatographable compounds. Croton oils from seed pressing and extraction mainly contain triglycerides (98%). Concerning FAME, the main component is linoleic acid (approx. 80%). Oilcake croton oil shows higher abundance of diglycerides (6% vs ca 2%) and a lower content of triglycerides (38% vs 98%) compared to the previous oils. Eventually, castor oil is mostly constituted of triacylglycerols (about 69%), followed by diglycerides (about 10%). About 85.2% of total FAME is ricinoleic acid, as a constituent of triricinolein, the most abundant triglyceride of castor oil. Based on the analytical results, these oils represent feedstocks of interest for possible exploitation as advanced biofuels.

Keywords: analytical protocol, biofuels, biorefinery, gas chromatography, vegetable oil

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Authors: A. Chiker, A. Benamor, A. Haddad, Y. Hadji, M. Hadji

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Metal matrix composites (MMCs) have been of big interest for a few decades. Their major drawback lies in their enhanced mechanical performance over unreinforced alloys. They found ground in many engineering fields, such as aeronautics, aerospace, automotive, and other structural applications. One of the most used alloys as a matrix is nickel alloys, which meet the need for high-temperature mechanical properties; some attempts have been made to develop nickel base composites reinforced by high melt point and high modulus particulates. Among the carbides used as reinforcing particulates, chromium carbide is interesting for wear applications; it is widely used as a tribological coating material in high-temperature applications requiring high wear resistance and hardness. Moreover, a set of properties make it suitable for use in MMCs, such as toughness, the good corrosion and oxidation resistance of its three polymorphs -the cubic (Cr23C6), the hexagonal (Cr7C3), and the orthorhombic (Cr3C2)-, and it’s coefficient of thermal expansion that is almost equal to that of metals. The in-situ synthesis of CrC-reinforced Ni matrix composites could be achieved by the powder metallurgy route. To ensure the in-situ reactions during the sintering process, the use of phase precursors is necessary. Recently, new precursor materials have been proposed; these materials are called MAX phases. The MAX phases are thermodynamically stable nano-laminated materials displaying unusual and sometimes unique properties. These novel phases possess Mn+1AXn chemistry, where n is 1, 2, or 3, M is an early transition metal element, A is an A-group element, and X is C or N. Herein, the pressureless sintering method is used to elaborate Ni/Cr2AlC composites. Four composites were elaborated from 5, 10, 15 and 20 wt% of Cr2AlC MAX phase precursor which fully reacted with Ni-matrix at 1100 °C sintering temperature for 4 h in argon atmosphere. XRD results showed that Cr2AlC MAX phase was totally decomposed forming chromium carbide Cr7C3, and the released Al and Cr atoms diffused in Ni matrix giving rise to γ-Ni(Al,Cr) solid solution and γ’-Ni3(Al,Cr) intermetallic. Scanning Electron Microscopy (SEM) of the elaborated samples showed the presence of nanosized Cr7C3 reinforcing particles embedded in the Ni metal matrix, which have a direct impact on the tribological properties of the composites and their hardness. All the composites exhibited higher hardness than pure Ni; whereas adding 15 wt% of Cr2AlC gives the highest hardness (1.85 GPa). Using a ball-on-disc tribometer, dry sliding tests for the elaborated composites against 100Cr6 steel ball were studied under different applied loads. The microstructures and worn surface characteristics were then analyzed using SEM and Raman spectroscopy. The results show that all the composites exhibited better wear resistance compared to pure Ni, which could be explained by the formation of a lubricious tribo-layer during sliding and the good bonding between the Ni matrix and the reinforcing phases.

Keywords: composites, microscopy, sintering, wear

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Authors: Xiaoyong He

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The manipulation of THz waves is still a challenging task due to lack of natural materials interacted with it strongly. Designed by tailoring the characters of unit cells (meta-molecules), the advance of metamaterials (MMs) may solve this problem. However, because of Ohmic and radiation losses, the performance of MMs devices is subjected to the dissipation and low quality factor (Q-factor). This dilemma may be circumvented by Fano resonance, which arises from the destructive interference between a bright continuum mode and dark discrete mode (or a narrow resonance). Different from symmetric Lorentz spectral curve, Fano resonance indicates a distinct asymmetric line-shape, ultrahigh quality factor, steep variations in spectrum curves. Fano resonance is usually realized through symmetry breaking. However, if concentric double rings (DR) are placed closely to each other, the near-field coupling between them gives rise to two hybridized modes (bright and narrowband dark modes) because of the local asymmetry, resulting into the characteristic Fano line shape. Furthermore, from the practical viewpoint, it is highly desirable requirement that to achieve the modulation of Fano spectral curves conveniently, which is an important and interesting research topics. For current Fano systems, the tunable spectral curves can be realized by adjusting the geometrical structural parameters or magnetic fields biased the ferrite-based structure. But due to limited dispersion properties of active materials, it is still a tough work to tailor Fano resonance conveniently with the fixed structural parameters. With the favorable properties of extreme confinement and high tunability, graphene is a strong candidate to achieve this goal. The DR-structure possesses the excitation of so-called “trapped modes,” with the merits of simple structure and high quality of resonances in thin structures. By depositing graphene circular DR on the SiO2/Si/ polymer substrate, the tunable Fano resonance has been theoretically investigated in the terahertz regime, including the effects of graphene Fermi level, structural parameters and operation frequency. The results manifest that the obvious Fano peak can be efficiently modulated because of the strong coupling between incident waves and graphene ribbons. As Fermi level increases, the peak amplitude of Fano curve increases, and the resonant peak position shifts to high frequency. The amplitude modulation depth of Fano curves is about 30% if Fermi level changes in the scope of 0.1-1.0 eV. The optimum gap distance between DR is about 8-12 μm, where the value of figure of merit shows a peak. As the graphene ribbon width increases, the Fano spectral curves become broad, and the resonant peak denotes blue shift. The results are very helpful to develop novel graphene plasmonic devices, e.g. sensors and modulators.

Keywords: graphene, metamaterials, terahertz, tunable

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Authors: Chales Mumbere Musavandalo, Lucie B. Mugherwa, Gloire Kayitoghera Mulondi, Naanson Bweya, Muyisa Musongora, Francis Lelo Nzuzi

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The landscape of the Okapi Wildlife Reserve in the Democratic Republic of Congo harbors a large community of Mbuti indigenous peoples, often described as the guardians of nature. Living in and off the forest has long been a sustainable strategy for preserving natural resources. This strategy, seen as a form of eco-responsible citizenship, draws upon ethnobotanical knowledge passed down through generations. However, these indigenous communities are facing socio-cultural upheaval, which impacts their traditional way of life. This study aims to assess the relationship between the Mbuti indigenous people’s way of life and the preservation of the Okapi Wildlife Reserve. The study was conducted under the assumption that, despite socio-cultural upheavals, the forest and its resources remain central to the Mbuti way of life. The study was conducted in six encampments, three of which were located inside the forest and two in the anthropized zone. The methodological approach initially involved group interviews in six Mbuti encampments. The objective of these interviews was to determine how these people perceive the various services provided by the forest and the resources obtained from this habitat. The technique of using pebbles was adopted to adapt the exercise of weighting services and resources to the understanding of these people. Subsequently, the study carried out ethnobotanical surveys to identify the wood resources frequently used by these communities. This survey was completed in third position by a transect inventory of 1000 m length and 25 m width in order to enhance the understanding of the abundance of these resources around the camps. Two transects were installed in each camp to carry out this inventory. Traditionally, the Mbuti communities sustain their livelihood through hunting, fishing, gathering for self-consumption, and basketry. The Manniophyton fulvum-based net remains the main hunting tool. The primary forest and the swamp are two habitats from which these peoples derive the majority of their resources. However, with the arrival of the Bantu people, who introduced agriculture based on cocoa production, the Mbuti communities started providing services to the Bantu in the form of labor and field guarding. This cultural symbiosis between Mbute and Bantu has also led to non-traditional practices, such as the use of hunting rifles instead of nets and fishing nets instead of creels. The socio-economic and ecological environment in which Mbuti communities live is changing rapidly, including the resources they depend on. By incorporating the time factor into their perception of ecosystem services, only their future (p-value = 0, 0,121), the provision of wood for energy (p-value = 0,1976), and construction (p-value = 0,2548) would be closely associated with the forest in their future. For other services, such as food supply, medicine, and hunting, adaptation to Bantu customs is conceivable. Additionally, the abundance of wood used by the Mbuti people has been high around encampments located in intact forests and low in those in anthropized areas. The traditional way of life of the Mbuti communities is influenced by the cultural symbiosis, reflected in their habits and the availability of resources. The land tenure security of Mbuti areas is crucial to preserve their tradition and forest biodiversity. Conservation efforts in the Okapi Wildlife Reserve must consider this cultural dynamism and promote positive values for the flagship species. The oversight of subsistence hunting is imperative to curtail the transition of these communities to poaching.

Keywords: traditional life, conservation, Indigenous people, cultural symbiosis, forest

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Authors: Bailey Houghtaling, Elena Serrano, Vivica Kraak, Samantha Harden, George Davis, Sarah Misyak

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United States (U.S.) Department of Agriculture Supplemental Nutrition Assistance Program (SNAP) participants are low-income Americans receiving federal dollars for supplemental food and beverage purchases. Participants use a variety of (traditional/non-traditional) SNAP-authorized stores for household dietary purchases - also representing food access points for all Americans. Importantly consumers' food and beverage purchases from non-traditional store formats tend to be higher in saturated fats, added sugars, and sodium when compared to purchases from traditional (e.g., grocery/supermarket) formats. Overconsumption of energy-dense and low-nutrient food and beverage products contribute to high obesity rates and adverse health outcomes that differ in severity among urban/rural U.S. locations and high/low-income populations. Little is known about the SNAP-authorized food store format landscape nationally, regionally, or by urban-rural status, as traditional formats are currently used as the gold standard in food access research. This research utilized publicly available U.S. databases to fill this large literature gap and to provide insight into modes of food access for vulnerable U.S. populations: (1) SNAP Retailer Locator which provides a list of all authorized food stores in the U.S., and; (2) Rural-Urban Continuum Codes (RUCC) that categorize U.S. counties as urban (RUCC 1-3) or rural (RUCC 4-9). Frequencies were determined for the highest occurring food store formats nationally and within two regionally diverse U.S. states – Virginia in the east and California in the west. Store format codes were assigned (e.g., grocery, drug, convenience, mass merchandiser, supercenter, dollar, club, or other). RUCC was applied to investigate state-level differences in urbanity-rurality regarding prevalent food store formats and Chi Square test of independence was used to determine if food store format distributions significantly (p < 0.05) differed by region or rurality. The resulting research sample that represented highly prevalent SNAP-authorized food stores nationally included 41.25% of all SNAP stores in the U.S. (N=257,839), comprised primarily of convenience formats (31.94%) followed by dollar (25.58%), drug (19.24%), traditional (10.87%), supercenter (6.85%), mass merchandiser (1.62%), non-food store or restaurant (1.81%), and club formats (1.09%). Results also indicated that the distribution of prevalent SNAP-authorized formats significantly differed by state. California had a lower proportion of traditional (9.96%) and a higher proportion of drug (28.92%) formats than Virginia- 11.55% and 19.97%, respectively (p < 0.001). Virginia also had a higher proportion of dollar formats (26.11%) when compared to California (10.64%) (p < 0.001). Significant differences were also observed for rurality variables (p < 0.001). Prominently, rural Virginia had a significantly higher proportion of dollar formats (41.71%) when compared to urban Virginia (21.78%) and rural California (21.21%). Non-traditional SNAP-authorized formats are highly prevalent and significantly differ in distribution by U.S. region and rurality. The largest proportional difference was observed for dollar formats where the least nutritious consumer purchases are documented in the literature. Researchers/practitioners should investigate non-traditional food stores at the local level using these research findings and similar applied methodologies to determine how access to various store formats impact obesity prevalence. For example, dollar stores may be prime targets for interventions to enhance nutritious consumer purchases in rural Virginia while targeting drug formats in California may be more appropriate.

Keywords: food access, food store format, nutrition interventions, SNAP consumers

Procedia PDF Downloads 141

Authors: Farideh Namvar, Rosfarizan Mohamed

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In the field of nanotechnology, the use of various biological units instead of toxic chemicals for the reduction and stabilization of nanoparticles, has received extensive attention. This use of biological entities to create nanoparticles has designated as “Green” synthesis and it is considered to be far more beneficial due to being economical, eco-friendly and applicable for large-scale synthesis as it operates on low pressure, less input of energy and low temperatures. The lack of toxic byproducts and consequent decrease in degradation of the product renders this technique more preferable over physical and classical chemical methods. The variety of biomass having reduction properties to produce nanoparticles makes them an ideal candidate for fabrication. Metal oxide nanoparticles have been said to represent a "fundamental cornerstone of nanoscience and nanotechnology" due to their variety of properties and potential applications. However, this also provides evidence of the fact that metal oxides include many diverse types of nanoparticles with large differences in chemical composition and behaviour. In this study, iron oxide nanoparticles (Fe3O4-NPs) were synthesized using a rapid, single step and completely green biosynthetic method by reduction of ferric chloride solution with brown seaweed (Sargassum muticum) water extract containing polysaccharides as a main factor which acts as reducing agent and efficient stabilizer. Antimicrobial activity against six microorganisms was tested using well diffusion method. The resulting S-IONPs are crystalline in nature, with a cubic shape. The average particle diameter, as determined by TEM, was found to be 18.01 nm. The S-IONPs were efficiently inhibited the growth of Listeria monocytogenes, Escherichia coli and Candida species. Our favorable results suggest that S-IONPs could be a promising candidate for development of future antimicrobial therapies. The nature of biosynthesis and the therapeutic potential by S-IONPs could pave the way for further research on design of green synthesis therapeutic agents, particularly nanomedicine, to deal with treatment of infections. Further studies are needed to fully characterize the toxicity and the mechanisms involved with the antimicrobial activity of these particles. Antioxidant activity of S-IONPs synthesized by green method was measured by ABTS (2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (IC50= 1000µg) radical scavenging activity. Also, with the increasing concentration of S-IONPs, catalase gene expression compared to control gene GAPDH increased. For anti-angiogenesis study the Ross fertilized eggs were divided into four groups; the control and three experimental groups. The gelatin sponges containing albumin were placed on the chorioalantoic membrane and soaked with different concentrations of S-IONPs. All the cases were photographed using a photo stereomicroscope. The number and the lengths of the vessels were measured using Image J software. The crown rump (CR) and weight of the embryo were also recorded. According to the data analysis, the number and length of the blood vessels, as well as the CR and weight of the embryos reduced significantly compared to the control (p < 0.05), dose dependently. The total hemoglobin was quantified as an indicator of the blood vessel formation, and in the treated samples decreased, which showed its inhibitory effect on angiogenesis.

Keywords: anti-angiogenesis, antimicrobial, antioxidant, biosynthesis, iron oxide (fe3o4) nanoparticles, sargassum muticum, seaweed

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Authors: Gabriel Acha Ekobi

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Fathers play a crucial role in meeting family needs such as affection, protection, and socio-economic needs of children in the world in general and South Africa in particular. Fathers’ role in children’s lives is important in providing socialization, leadership skills, and teaching societal norms. Fathers influence is very significant for children’s well-being and development as it provides the child with moral lessons, guidance, and economic support. However, there is a paucity of information regarding the effects of fathers on children. In addition, despite legal frameworks such as the African Charter on the Rights and Welfare of the child (1999) introduced by the African Union to promote child rights nevertheless, it appears maltreatment, abuse, and poor health care continue to face children. Also, the Constitution of 1996 of the Republic of South Africa (Section 28 of the Bill of Rights) and the Children’s Act 38 of 2005 were introduced by the South African government to foster the rights of children. Nevertheless, these legal frameworks remain ineffective as children’s rights are still neglected by resident fathers. This paper explores the impact of resident fathers on children in the Golf View, Alice town of the Eastern Cape Province, South Africa. A qualitative research method and an exploratory research design were utilized, and 30 participants took part in the study. The participants comprised of single mothers or caregivers of children, resident fathers and social workers. Eighteen (18) single mothers or caregivers, 10 resident fathers, and two (2) social workers participated in the study. Data was collected using semi-structured and unstructured interviews and analysed thematically. Two main themes were identified: the role of fathers on children and the effects of resident fathers on children. The study found that the presence of fathers in the lives of children prevented psychosocial issues such as stress, depression, violence, and substance abuse. A father’s presence in a household was crucial in instilling moral values in children. This allowed them to build positive characters such as respect, kindness, humility, and compassion. Children with more involved fathers tend to have fewer impulse control problems, longer attention spans, and a higher level of sociability. The study concludes that the fathers’ role prevented anxiety, depression, and stress and led to the improvement of children’s education performance. Nevertheless, the absence of a father as a role model to act as a leader by instilling moral values hinders positive behaviours in children. This study recommended that occupational training and life skills programmes should be introduced by the government and other stakeholders to empower the fathers as this might provide the platform for them to bring up their children properly.

Keywords: children, fathering, household, resident, single parent

Procedia PDF Downloads 55

Authors: Tak Mau Simon Chan

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While there is growing reflection of the adverse impacts instigated by the flourishing gaming industry on the physical health and job satisfaction of those who work in Macau casinos, there is also a critical void in our understanding of the mental health of croupiers and how casino employment interacts with the family system. From a systemic approach, it would be most effective to examine the ‘dealer issues’ collectively and offer assistance to both the individual dealer and the family system of dealers. Therefore, with the use of a mixed method study design, the levels of anxiety, depression and sleeping quality of a sample of 1124 dealers who are working in Macau casinos have been measured in the present study, and 113 dealers have been interviewed about the impacts of casino employment on their family life. This study presents some very important findings. First, the quantitative study indicates that gender is a significant predictor of depression and anxiety levels, whilst lower income means less quality sleep. The Pearson’s correlation coefficients show that as the Zung Self-rating Anxiety Scale (ZSAS) scores increase, the Zung Self-rating Depression Scale (ZSDS) and Pittsburgh Sleep Quality Index (PSQI) scores will also simultaneously increase. Higher income, therefore, might partly explain for the reason why mothers choose to work in the gaming industry even with shift work involved and a stressful work environment. Second, the findings from the qualitative study show that aside from the positive impacts on family finances, the shift work and job stress to some degree negatively affect family responsibilities and relationships. There are resultant family issues, including missed family activities, and reduced parental care and guidance, marital intimacy, and communication with family members. Despite the mixed views on the gender role differences, the respondents generally agree that female dealers have more family and child-minding responsibilities at home, and thus it is more difficult for them to balance work and family. Consequently, they may be more vulnerable to stress at work. Thirdly, there are interrelationships between work and family, which are based on a systemic inquiry that incorporates work- individual- family. Poor physical and psychological health due to shift work or a harmful work environment could affect not just work performance, but also life at home. Therefore, a few practice points about 1) work-family conflicts in Macau; 2) families-in- transition in Macau; and 3) gender and class sensitivity in Macau; are provided for social workers and family practitioners who will greatly benefit these families, especially whose family members are working in the gaming industry in Macau. It is concluded that in addressing the cultural phenomenon of “dealer’s complex” in Macau, a systemic approach is recommended that addresses both personal psychological needs and family issue of dealers.

Keywords: family, work stress, mental health, Macau, dealers, gaming industry

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Authors: Tomohiko Utsuki, Kyoka Sato

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In emergency medicine, it is recognized that brain resuscitation is very important for the reduction of mortality rate and neurological sequelae. Especially, the control of brain temperature (BT), intracranial pressure (ICP), and cerebral blood flow (CBF) are most required for stabilizing brain’s physiological state in the treatment for such as brain injury, stroke, and encephalopathy. However, the manual control of BT, ICP, and CBF frequently requires the decision and operation of medical staff, relevant to medication and the setting of therapeutic apparatus. Thus, the integration and the automation of the control of those is very effective for not only improving therapeutic effect but also reducing staff burden and medical cost. For realizing such integration and automation, a mathematical model of brain physiological state is necessary as the controlled object in simulations, because the performance test of a prototype of the control system using patients is not ethically allowed. A model of cerebral blood circulation has already been constructed, which is the most basic part of brain physiological state. Also, a migration model of extracellular fluid in brain has been constructed, however the condition that the total volume of intracranial cavity is almost changeless due to the hardness of cranial bone has not been considered in that model. Therefore, in this research, the dynamic migration model of extracellular fluid in brain was constructed on the consideration of the changelessness of intracranial cavity’s total volume. This model is connectable to the cerebral blood circulation model. The constructed model consists of fourteen compartments, twelve of which corresponds to perfused area of bilateral anterior, middle and posterior cerebral arteries, the others corresponds to cerebral ventricles and subarachnoid space. This model enable to calculate the migration of tissue fluid from capillaries to gray matter and white matter, the flow of tissue fluid between compartments, the production and absorption of cerebrospinal fluid at choroid plexus and arachnoid granulation, and the production of metabolic water. Further, the volume, the colloid concentration, and the tissue pressure of/in each compartment are also calculable by solving 40-dimensional non-linear simultaneous differential equations. In this research, the obtained model was analyzed for its validation under the four condition of a normal adult, an adult with higher cerebral capillary pressure, an adult with lower cerebral capillary pressure, and an adult with lower colloid concentration in cerebral capillary. In the result, calculated fluid flow, tissue volume, colloid concentration, and tissue pressure were all converged to suitable value for the set condition within 60 minutes at a maximum. Also, because these results were not conflict with prior knowledge, it is certain that the model can enough represent physiological state of brain under such limited conditions at least. One of next challenges is to integrate this model and the already constructed cerebral blood circulation model. This modification enable to simulate CBF and ICP more precisely due to calculating the effect of blood pressure change to extracellular fluid migration and that of ICP change to CBF.

Keywords: dynamic model, cerebral extracellular migration, brain resuscitation, automatic control

Procedia PDF Downloads 157

Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

Procedia PDF Downloads 530

Authors: Giacoma Pace

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The research seeks to evaluate whether students with impairments can achieve enhanced academic progress by actively engaging in collaborative problem-solving activities with teachers and peers, to overcome the obstacles rooted in socio-economic disparities. Furthermore, the research underscores the significance of fostering students' self-awareness regarding their learning process and encourages teachers to adopt a more interactive teaching approach. The research also posits that reducing conventional face-to-face lessons can motivate students to explore alternative learning methods, such as collaborative teamwork and peer education within the classroom. To address socio-cultural barriers it is imperative to assess their internet access and possession of technological devices, as these factors can contribute to a digital divide. The research features a case study of a Flipped Classroom Learning Unit, administered to six third-year high school classes: Scientific Lyceum, Technical School, and Vocational School, within the city of Turin, Italy. Data are about teachers and the students involved in the case study, some impaired students in each class, level of entry, students’ performance and attitude before using Flipped Classrooms, level of motivation, family’s involvement level, teachers’ attitude towards Flipped Classroom, goal obtained, the pros and cons of such activities, technology availability. The selected schools were contacted; meetings for the English teachers to gather information about their attitude and knowledge of the Flipped Classroom approach. Questionnaires to teachers and IT staff were administered. The information gathered, was used to outline the profile of the subjects involved in the study and was further compared with the second step of the study made up of a study conducted with the classes of the selected schools. The learning unit is the same, structure and content are decided together with the English colleagues of the classes involved. The pacing and content are matched in every lesson and all the classes participate in the same labs, use the same materials, homework, same assessment by summative and formative testing. Each step follows a precise scheme, in order to be as reliable as possible. The outcome of the case study will be statistically organised. The case study is accompanied by a study on the literature concerning EFL approaches and the Flipped Classroom. Document analysis method was employed, i.e. a qualitative research method in which printed and/or electronic documents containing information about the research subject are reviewed and evaluated with a systematic procedure. Articles in the Web of Science Core Collection, Education Resources Information Center (ERIC), Scopus and Science Direct databases were searched in order to determine the documents to be examined (years considered 2000-2022).

Keywords: flipped classroom, impaired, inclusivity, peer instruction

Procedia PDF Downloads 53

Authors: Eniola Akande

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Introduction: English vocabulary and reading comprehension are core to academic achievement in many school subjects. Deficiency in both accounts for dismal performance in internal and external examinations among primary school pupils in Ibadan Metropolis, Nigeria. Previous studies largely focused on factors influencing pupils’ achievement in English vocabulary and reading comprehension. In spite of what literature has shown, the problem still persists, implying the need for other kinds of intervention. This study was therefore carried out to determine the effect of two transactional strategies Picture Walk (PW) and Know-Want to Learn-Learnt (KWL) on primary four pupils’ achievement in English vocabulary and reading comprehension in Ibadan Metropolis. The moderating effects of gender and learning style were also examined. Methodology: The study was anchored on Rosenblatt’s Transactional Reading and Piaget’s Cognitive Development theories; pretest-posttest control group quasi-experimental design with 3x2x3 factorial matrix was adopted. Six public primary schools were purposively selected based on the availability of qualified English language teachers in Primary Education Studies. Six intact classes (one per school) with a total of 101 primary four pupils (48 males and 53 females) participated. The intact classes were randomly assigned to PW (27), KWL (44) and conventional (30) groups. Instruments used were English Vocabulary (r=0.83), Reading Comprehension (r=0.84) achievement tests, Pupils’ Learning Style Preference Scale (r=0.93) and instructional guides. Treatment lasted six weeks. Data were analysed using the Descriptive statistics, Analysis of Covariance and Bonferroni post-hoc test at 0.05 level of significance. The mean age was 8.86±0.84 years. Result: Treatment had a significant main effect on pupils’ reading comprehension (F(2,82)=3.17), but not on English vocabulary. Participants in KWL obtained the highest post achievement means score in reading comprehension (8.93), followed by PW (8.06) and control (7.21) groups. Pupils’ learning style had a significant main effect on pupils’ achievement in reading comprehension (F(2,82)=4.41), but not on English vocabulary. Pupils with preference for tactile learning style had the highest post achievement mean score in reading comprehension (9.40), followed by the auditory (7.43) and the visual learning style (7.37) groups. Gender had no significant main effect on English vocabulary and reading comprehension. There was no significant two-way interaction effect of treatment and gender on pupils’ achievement in English vocabulary and reading comprehension. The two-way interaction effect of treatment and learning style on pupils’ achievement in reading comprehension was significant (F(4,82)=3.37), in favour of pupils with tactile learning style in PW group. There was no significant two-way interaction effect of gender and learning style on pupils’ achievement in English vocabulary and reading comprehension. The three-way interaction effects were not significant on English vocabulary and reading comprehension. Conclusion: Picture Walk and Know-Want to learn-Learnt instructional strategies were effective in enhancing pupils’ achievement in reading comprehension but not on English vocabulary. Learning style contributed considerably to achievement in reading comprehension but not to English vocabulary. Primary school, English language teachers, should put into consideration pupils’ learning style when adopting both strategies in teaching reading comprehension for improved achievement in the subject.

Keywords: comprehension-based intervention, know-want to learn-learnt, learning style, picture walk, primary school pupils

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Authors: Boris Nemzer, Nebiyu Abshiru, Z. B. Pietrzkowski

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Coffee cherry is one of the most ubiquitous agricultural commodities which possess nutritional and human health beneficial properties. Between the two most widely used coffee cherries Coffea arabica (Arabica) and Coffea canephora (Robusta), Coffea arabica remains superior due to its sensory properties and, therefore, remains in great demand in the global coffee market. In this study, the phytochemical contents and pharmacokinetics of Coffeeberry® Energy (CBE), a commercially available Arabica whole coffee fruit caffeine extract, are investigated. For phytochemical screening, 20 mg of CBE was dissolved in an aqueous methanol solution for analysis by mass spectrometry (MS). Quantification of caffeine and chlorogenic acids (CGAs) contents of CBE was performed using HPLC. For the bioavailability study, serum samples were collected from human subjects before and after 1, 2 and 3 h post-ingestion of 150mg CBE extract. Protein precipitation and extraction were carried out using methanol. Identification of compounds was performed using an untargeted metabolomic approach on Q-Exactive Orbitrap MS coupled to reversed-phase chromatography. Data processing was performed using Thermo Scientific Compound Discover 3.3 software. Phytochemical screening identified a total of 170 compounds, including organic acids, phenolic acids, CGAs, diterpenoids and hydroxytryptamine. Caffeine & CGAs make up more than, respectively, 70% & 9% of the total CBE composition. For serum samples, a total of 82 metabolites representing 32 caffeine- and 50 phenolic-derived metabolites were identified. Volcano plot analysis revealed 32 differential metabolites (24 caffeine- and 8 phenolic-derived) that showed an increase in serum level post-CBE dosing. Caffeine, uric acid, and trimethyluric acid isomers exhibited 4- to 10-fold increase in serum abundance post-dosing. 7-Methyluric acid, 1,7-dimethyluric acid, paraxanthine and theophylline exhibited a minimum of 1.5-fold increase in serum level. Among the phenolic-derived metabolites, iso-feruloyl quinic acid isomers (3-, 4- and 5-iFQA) showed the highest increase in serum level. These compounds were essentially absent in serum collected before dosage. More interestingly, the iFQA isomers were not originally present in the CBE extract, as our phytochemical screen did not identify these compounds. This suggests the potential formation of the isomers during the digestion and absorption processes. Pharmacokinetics parameters (Cmax, Tmax and AUC0-3h) of caffeine- and phenolic-derived metabolites were also investigated. Caffeine was rapidly absorbed, reaching a maximum concentration (Cmax) of 10.95 µg/ml in just 1 hour. Thereafter, caffeine level steadily dropped from the peak level, although it did not return to baseline within the 3-hour dosing period. The disappearance of caffeine from circulation was mirrored by the rise in the concentration of its methylxanthine metabolites. Similarly, serum concentration of iFQA isomers steadily increased, reaching maximum (Cmax: 3-iFQA, 1.54 ng/ml; 4-iFQA, 2.47 ng/ml; 5-iFQA, 2.91 ng/ml) at tmax of 1.5 hours. The isomers remained well above the baseline during the 3-hour dosing period, allowing them to remain in circulation long enough for absorption into the body. Overall, the current study provides evidence of the potential health benefits of a uniquely formulated whole coffee fruit product. Consumption of this product resulted in a distinct serum profile of bioactive compounds, as demonstrated by the more than 32 metabolites that exhibited a significant change in systemic exposure.

Keywords: phytochemicals, mass spectrometry, pharmacokinetics, differential metabolites, chlorogenic acids

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Authors: Fatma Refaat Ahmed, Sally Mohamed Farghaly

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Context: Intensive care unit (ICU) nurses often face pressure and constraints in their work, leading to the rationing of care when demands exceed available time and resources. Observations suggest that ICU nurses are frequently distracted from their core nursing roles by non-core tasks. This study aims to provide evidence on ICU nurses' multitasking activities and explore the association between nurses' personal and clinical characteristics and their time allocation. Research Aim: The aim of this study is to quantify the time spent by ICU nurses on multitasking activities and investigate the relationship between their personal and clinical characteristics and time allocation. Methodology: A self-observation form utilizing the "Diary" recording method was used to record the number of tasks performed by ICU nurses and the time allocated to each task category. Nurses also reported on the distractions encountered during their nursing activities. A convenience sample of 60 ICU nurses participated in the study, with each nurse observed for one nursing shift (6 hours), amounting to a total of 360 hours. The study was conducted in two ICUs within a university teaching hospital in Alexandria, Egypt. Findings: The results showed that ICU nurses completed 2,730 direct patient-related tasks and 1,037 indirect tasks during the 360-hour observation period. Nurses spent an average of 33.65 minutes on ventilator care-related tasks, 14.88 minutes on tube care-related tasks, and 10.77 minutes on inpatient care-related tasks. Additionally, nurses spent an average of 17.70 minutes on indirect care tasks per hour. The study identified correlations between nursing time and nurses' personal and clinical characteristics. Theoretical Importance: This study contributes to the existing research on ICU nurses' multitasking activities and their relationship with personal and clinical characteristics. The findings shed light on the significant time spent by ICU nurses on direct care for mechanically ventilated patients and the distractions that require attention from ICU managers. Data Collection: Data were collected using self-observation forms completed by participating ICU nurses. The forms recorded the number of tasks performed, the time allocated to each task category, and any distractions encountered during nursing activities. Analysis Procedures: The collected data were analyzed to quantify the time spent on different tasks by ICU nurses. Correlations were also examined between nursing time and nurses' personal and clinical characteristics. Question Addressed: This study addressed the question of how ICU nurses allocate their time across multitasking activities and whether there is an association between nurses' personal and clinical characteristics and time allocation. Conclusion: The findings of this study emphasize the need for a lean evaluation of ICU nurses' activities to identify and address potential gaps in patient care and distractions. Implementing lean techniques can improve efficiency, safety, clinical outcomes, and satisfaction for both patients and nurses, ultimately enhancing the quality of care and organizational performance in the ICU setting.

Keywords: motion study, ICU nurse, lean, nursing time, multitasking activities

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Authors: Mikko Salminen, Simo Järvelä, Niklas Ravaja

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One of the central models of emotional intelligence (EI) is that of Mayer and Salovey’s, which includes ability to monitor own feelings and emotions and those of others, ability to discriminate different emotions, and to use this information to guide thinking and actions. There is vast amount of previous research where positive links between EI and, for example, leadership successfulness, work outcomes, work wellbeing and organizational climate have been reported. EI has also a role in the effectiveness of work teams, and the effects of EI are especially prominent in jobs requiring emotional labor. Thus, also the organizational context must be taken into account when considering the effects of EI on work outcomes. Based on previous research, it is suggested that EI can also protect managers from the negative consequences of stress. Stress may have many detrimental effects on the manager’s performance in essential work tasks. Previous studies have highlighted the effects of stress on, not only health, but also, for example, on cognitive tasks such as decision-making, which is important in managerial work. The motivation for the current study came from the notion that, unfortunately, many stressed individuals may not be aware of the circumstance; periods of stress-induced physiological arousal may be prolonged if there is not enough time for recovery. To tackle this problem, physiological stress levels of managers were collected using recording of heart rate variability (HRV). The goal was to use this data to provide the managers with feedback on their stress levels. The managers could access this feedback using a www-based learning environment. In the learning environment, in addition to the feedback on stress level and other collected data, also developmental tasks were provided. For example, those with high stress levels were sent instructions for mindfulness exercises. The current study focuses on the relation between the measured physiological stress levels and EI of the managers. In a pilot study, 33 managers from various fields wore the Firstbeat Bodyguard HRV measurement devices for three consecutive days and nights. From the collected HRV data periods (minutes) of stress and recovery were detected using dedicated software. The effects of EI on HRV-calculated stress indexes were studied using Linear Mixed Models procedure in SPSS. There was a statistically significant effect of total EI, defined as an average score of Schutte’s emotional intelligence test, on the percentage of stress minutes during the whole measurement period (p=.025). More stress minutes were detected on those managers who had lower emotional intelligence. It is suggested, that high EI provided managers with better tools to cope with stress. Managing of own emotions helps the manager in controlling possible negative emotions evoked by, e.g., critical feedback or increasing workload. High EI managers may also be more competent in detecting emotions of others, which would lead to smoother interactions and less conflicts. Given the recent trend to different quantified-self applications, it is suggested that monitoring of bio-signals would prove to be a fruitful direction to further develop new tools for managerial and leadership coaching.

Keywords: emotional intelligence, leadership, heart rate variability, personality, stress

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Authors: D. Pogliana, A. Maso, N. Milani, D. Panzin, S. Rivaroli, J. Konin

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This case aims to identify the role of movement quality during the final stage of return to sport (RTS) in a male amateur football player 13 years old after passing the acute phase of the bilateral Osgood-Schlatter disease (OSD). The patient, after a year from passing the acute phase of OSD with the abstention of physical activity, reports bilateral anterior knee pain at the beginning of the football sport activity. Interventions: After the orthopedist check, who recommended physiotherapy sessions for the correction of motor patterns and the isometric reinforcement of the muscles of the quadriceps, the rehabilitation intervention was developed in 7 weeks through 14 sessions of neuro-motor training (NMT) with a frequency of two weekly sessions and six sessions of muscle-strengthening with a frequency of one weekly session. The sessions of NMT were carried out through free body exercises (or with overloads) with visual bio-feedback with the help of two cameras (one with anterior vision and one with lateral vision of the subject) and a big touch screen. The aim of these sessions of NMT was to modify the dysfunctional motor patterns evaluated by the 2D motion analysis test. The test was carried out at the beginning and at the end of the rehabilitation course and included five movements: single-leg squat (SLS), drop jump (DJ), single-leg hop (SLH), lateral shuffle (LS), and change of direction (COD). Each of these movements was evaluated through the video analysis of dynamic valgus knee, pelvic tilt, trunk control, shock absorption, and motor strategy. A free image analysis software (Kinovea) was then used to calculate scores. Results: Baseline assessment of the subject showed a total score of 59% on the right limb and 64% on the left limb (considering an optimal score above 85%) with large deficits in shock absorption capabilities, the presence of dynamic valgus knee, and dysfunctional motor strategies defined “quadriceps dominant.” After six weeks of training, the subject achieved a total score of 80% on the right limb and 86% on the left limb, with significant improvements in shock absorption capabilities, the presence of dynamic knee valgus, and the employment of more hip-oriented motor strategies on both lower limbs. The improvements shown in dynamic knee valgus, greater hip-oriented motor strategies, and improved shock absorption identified through six weeks of the NMT program can help a teenager amateur football player to manage the anterior knee pain during sports activity. In conclusion, NMT was a good choice to help a 13 years old male amateur football player to return to performance without pain after OSD and can also be used with all this type of athletes of the other teams' sports.

Keywords: movement analysis, neuro-motor training, knee pain, movement strategies

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Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique for the incompressible two-phase flow simulations. This technique is known as observable method due to the understanding of observability that any feature smaller than the actual resolution (physical or numerical), i.e., the size of wire in hotwire anemometry or the grid size in numerical simulations, is not able to be captured or observed. Differ from most regularization techniques that applies on the numerical discretization, the observable method is employed at PDE level during the derivation of equations. Difficulties in the simulation and analysis of realistic fluid flow often result from discontinuities (or near-discontinuities) in the calculated fluid properties or state. Accurately capturing these discontinuities is especially crucial when simulating flows involving shocks, turbulence or sharp interfaces. Over the past several years, the properties of this new regularization technique have been investigated that show the capability of simultaneously regularizing shocks and turbulence. The observable method has been performed on the direct numerical simulations of shocks and turbulence where the discontinuities are successfully regularized and flow features are well captured. In the current paper, the observable method will be extended to two-phase interfacial flows. Multiphase flows share the similar features with shocks and turbulence that is the nonlinear irregularity caused by the nonlinear terms in the governing equations, namely, Euler equations. In the direct numerical simulation of two-phase flows, the interfaces are usually treated as the smooth transition of the properties from one fluid phase to the other. However, in high Reynolds number or low viscosity flows, the nonlinear terms will generate smaller scales which will sharpen the interface, causing discontinuities. Many numerical methods for two-phase flows fail at high Reynolds number case while some others depend on the numerical diffusion from spatial discretization. The observable method regularizes this nonlinear mechanism by filtering the convective terms and this process is inviscid. The filtering effect is controlled by an observable scale which is usually about a grid length. Single rising bubble and Rayleigh-Taylor instability are studied, in particular, to examine the performance of the observable method. A pseudo-spectral method is used for spatial discretization which will not introduce numerical diffusion, and a Total Variation Diminishing (TVD) Runge Kutta method is applied for time integration. The observable incompressible Euler equations are solved for these two problems. In rising bubble problem, the terminal velocity and shape of the bubble are particularly examined and compared with experiments and other numerical results. In the Rayleigh-Taylor instability, the shape of the interface are studied for different observable scale and the spike and bubble velocities, as well as positions (under a proper observable scale), are compared with other simulation results. The results indicate that this regularization technique can potentially regularize the sharp interface in the two-phase flow simulations

Keywords: Euler equations, incompressible flow simulation, inviscid regularization technique, two-phase flow

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Authors: Nan Xu

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In airlines, the crew scheduling problem is usually decomposed into two stages: crew pairing and crew rostering. In the crew pairing stage, pairings are generated such that each flight is covered by exactly one pairing and the overall cost is minimized. In the crew rostering stage, the pairings generated in the crew pairing stage are combined with off days, training and other breaks to create individual work schedules. The paper focuses on cabin crew rostering problem, which is challenging due to the extremely large size and the complex working rules involved. In our approach, the objective of rostering consists of two major components. The first is to minimize the number of unassigned pairings and the second is to ensure the fairness to crew members. There are two measures of fairness to crew members, the number of overnight duties and the total fly-hour over a given period. Pairings should be assigned to each crew member so that their actual overnight duties and fly hours are as close to the expected average as possible. Deviations from the expected average are penalized in the objective function. Since several small deviations are preferred than a large deviation, the penalization is quadratic. Our model of the airline crew rostering problem is based on column generation. The problem is decomposed into a master problem and subproblems. The mater problem is modeled as a set partition problem and exactly one roster for each crew is picked up such that the pairings are covered. The restricted linear master problem (RLMP) is considered. The current subproblem tries to find columns with negative reduced costs and add them to the RLMP for the next iteration. When no column with negative reduced cost can be found or a stop criteria is met, the procedure ends. The subproblem is to generate feasible crew rosters for each crew member. A separate acyclic weighted graph is constructed for each crew member and the subproblem is modeled as resource constrained shortest path problems in the graph. Labeling algorithm is used to solve it. Since the penalization is quadratic, a method to deal with non-additive shortest path problem using labeling algorithm is proposed and corresponding domination condition is defined. The major contribution of our model is: 1) We propose a method to deal with non-additive shortest path problem; 2) Operation to allow relaxing some soft rules is allowed in our algorithm, which can improve the coverage rate; 3) Multi-thread techniques are used to improve the efficiency of the algorithm when generating Line-of-Work for crew members. Here a column generation based algorithm for the airline cabin crew rostering problem is proposed. The objective is to assign a personalized roster to crew member which minimize the number of unassigned pairings and ensure the fairness to crew members. The algorithm we propose in this paper has been put into production in a major airline in China and numerical experiments show that it has a good performance.

Keywords: aircrew rostering, aircrew scheduling, column generation, SPPRC

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Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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Authors: Mindaugas Liaudanskas, Darius Kviklys, Kristina Zymonė, Raimondas Raudonis, Jonas Viškelis, Norbertas Uselis, Pranas Viškelis, Valdimaras Janulis

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Apples are among the most commonly consumed fruits in the world. Based on data from the year 2014, approximately 84.63 million tons of apples are grown per annum. Apples are widely used in food industry to produce various products and drinks (juice, wine, and cider); they are also used unprocessed. Apples in human diet are an important source of different groups of biological active compounds that can positively contribute to the prevention of various diseases. They are a source of various biologically active substances – especially vitamins, organic acids, micro- and macro-elements, pectins, and phenolic, triterpenic, and other compounds. Triterpenic compounds, which are characterized by versatile biological activity, are the biologically active compounds found in apples that are among the most promising and most significant for human health. A specific analytical procedure including sample preparation and High Performance Liquid Chromatography (HPLC) analysis was developed, optimized, and validated for the detection of triterpenic compounds in the samples of different apples, their peels, and flesh from widespread apple cultivars 'Aldas', 'Auksis', 'Connel Red', 'Ligol', 'Lodel', and 'Rajka' grown in Lithuanian climatic conditions. The conditions for triterpenic compound extraction were optimized: the solvent of the extraction was 100% (v/v) acetone, and the extraction was performed in an ultrasound bath for 10 min. Isocratic elution (the eluents ratio being 88% (solvent A) and 12% (solvent B)) for a rapid separation of triterpenic compounds was performed. The validation of the methodology was performed on the basis of the ICH recommendations. The following characteristics of validation were evaluated: the selectivity of the method (specificity), precision, the detection and quantitation limits of the analytes, and linearity. The obtained parameters values confirm suitability of methodology to perform analysis of triterpenic compounds. Using the optimised and validated HPLC technique, four triterpenic compounds were separated and identified, and their specificity was confirmed. These compounds were corosolic acid, betulinic acid, oleanolic acid, and ursolic acid. Ursolic acid was the dominant compound in all the tested apple samples. The detected amount of betulinic acid was the lowest of all the identified triterpenic compounds. The greatest amounts of triterpenic compounds were detected in whole apple and apple peel samples of the 'Lodel' cultivar, and thus apples and apple extracts of this cultivar are potentially valuable for use in medical practice, for the prevention of various diseases, for adjunct therapy, for the isolation of individual compounds with a specific biological effect, and for the development and production of dietary supplements and functional food enriched in biologically active compounds. Acknowledgements. This work was supported by a grant from the Research Council of Lithuania, project No. MIP-17-8.

Keywords: apples, HPLC, triterpenic compounds, validation

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Authors: Ayla Hoeta

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In a post-colonial Aotearoa New Zealand, solutions by rangatahi (youth) for rangatahi are essential as is civic participation and building economic agency in an increasingly tough economic climate. Upsouth was an online community crowdsourcing platform developed by The Southern Initiative, in collaboration with Itsnoon that provides rangatahi and whānau (family) a safe space to share lived experience, thoughts and ideas about local kaupapa (issues/topics) of importance to them. The target participants were Māori indigenous peoples and Pacifica groups, aged 14 - 21 years. In the Aotearoa New Zealand context, this participant group is not likely to engage in traditional consultation processes despite being an essential constituent in helping shape better local communities, whānau and futures. The Upsouth platform was active for two years from 2018-2019 where it completed 42 callups with 4300+ participants. The web platform collates the ideas, voices, feedback, and content of users around a callup that has been commissioned by a sponsor, such as Auckland Council, Z Energy or Auckland Transport. A callup may be about a pressing challenge in a community such as climate change, a new housing development, homelessness etc. Each callup was funded by the sponsor with Upsouths main point of difference being that participants are given koha (money donation) through digital wallets for their ideas. Depending on the quality of what participants upload, the koha varies between small micropayments and larger payments. This encouraged participants to develop creative and critical thinking - upskilling for future focussed jobs, enterprise and democratic skills while earning pocket money at the same time. Upsouth enables youth-led action and voice, and empowers them to be a part of a reciprocal and creative economy. Rangatahi are encouraged to express themselves culturally, creatively, freely and in a way they are free to choose - for example, spoken word, song, dance, video, drawings, and/or poems. This challenges and changes what is considered acceptable as community engagement feedback by the local government. Many traditional engagement platforms are not as consultative, do not accept diverse types of feedback, nor incentivise this valuable expression of feedback. Upsouth is also empowering for rangatahi, since it allows them the opportunity to express their opinions directly to the government. Upsouth gained national and international recognition for the way it engages with youth: winning the Supreme Award and the Accessibility and Transparency Award at Auckland Council’s 2018 Engagement Awards, becoming a finalist in the 2018 Digital Equity and Accessibility category of International Data Corporation’s Smart City Asia and Pacific Awards. This paper will fully contextualize the challenges of rangatahi and whānau civic engagement in Aotearoa New Zealand and then present a reflective case study of the Upsouth project, with examples from some of the callups. This is intended to form part of the Divided Cities 22 conference New Ground sub-theme as a critical reflection on a design intervention, which was conceived and implemented by the lead author to overcome the post-colonial divisions of Māori, Pacifica and minority ethnic rangatahi in Aotearoa New Zealand.

Keywords: rangatahi, youth empowerment, civic engagement, enabling, relating, digital platform, participation

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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