Search results for: stage performance

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

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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: Aysen Caliskan, Hanzade Haykiri-Acma, Serdar Yaman

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Co-firing of coal and biomass blends is an effective method to reduce carbon dioxide emissions released by burning coals, thanks to the carbon-neutral nature of biomass. Besides, usage of biomass that is renewable and sustainable energy resource mitigates the dependency on fossil fuels for power generation. However, most of the biomass species has negative aspects such as low calorific value, high moisture and volatile matter contents compared to coal. Torrefaction is a promising technique in order to upgrade the fuel properties of biomass through thermal treatment. That is, this technique improves the calorific value of biomass along with serious reductions in the moisture and volatile matter contents. In this context, several woody biomass materials including Rhododendron, hybrid poplar, and ash-tree were subjected to torrefaction process in a horizontal tube furnace at 200°C under nitrogen flow. In this way, the solid residue obtained from torrefaction that is also called as 'biochar' was obtained and analyzed to monitor the variations taking place in biomass properties. On the other hand, some Turkish lignites from Elbistan, Adıyaman-Gölbaşı and Çorum-Dodurga deposits were chosen as coal samples since these lignites are of great importance in lignite-fired power stations in Turkey. These lignites were blended with the obtained biochars for which the blending ratio of biochars was kept at 10 wt% and the lignites were the dominant constituents in the fuel blends. Burning tests of the lignites, biomasses, biochars, and blends were performed using a thermogravimetric analyzer up to 900°C with a heating rate of 40°C/min under dry air atmosphere. Based on these burning tests, properties relevant to burning characteristics such as the burning reactivity and burnout yields etc. could be compared to justify the effects of torrefaction and blending. Besides, some characterization techniques including X-Ray Diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM) were also conducted for the untreated biomass and torrefied biomass (biochar) samples, lignites and their blends to examine the co-combustion characteristics elaborately. Results of this study revealed the fact that blending of lignite with 10 wt% biochar created synergistic behaviors during co-combustion in comparison to the individual burning of the ingredient fuels in the blends. Burnout and ignition performances of each blend were compared by taking into account the lignite and biomass structures and characteristics. The blend that has the best co-combustion profile and ignition properties was selected. Even though final burnouts of the lignites were decreased due to the addition of biomass, co-combustion process acts as a reasonable and sustainable solution due to its environmentally friendly benefits such as reductions in net carbon dioxide (CO2), SOx and hazardous organic chemicals derived from volatiles.

Keywords: burnout performance, co-combustion, thermal analysis, torrefaction pretreatment

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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: 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: Ming-Chan Chung, Wen-Ming Huang, Yi-Chu Liu, Li-Hui Yang, Ming-Jyh Chen

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introduction: Hospital buildings require considerable energy, including air conditioning, lighting, elevators, heating, and medical equipment. Energy consumption in hospitals is expected to increase significantly due to innovative equipment and continuous development plans. Consequently, the environment and climate will be adversely affected. Hospitals should therefore consider transforming from their traditional role of saving lives to being at the forefront of global efforts to reduce carbon dioxide emissions. As healthcare providers, it is our responsibility to provide a high-quality environment while using as little energy as possible. Purpose / Methods: Compare the energy-saving benefits of solar photovoltaic systems and solar hot water systems. The proportion of electricity consumption effectively reduced after the installation of solar photovoltaic systems. To comprehensively assess the potential benefits of utilizing solar energy for both photovoltaic (PV) and solar thermal applications in hospitals, a solar PV system was installed covering a total area of 28.95 square meters in 2021. Approval was obtained from the Taiwan Power Company to integrate the system into the hospital's electrical infrastructure for self-use. To measure the performance of the system, a dedicated meter was installed to track monthly power generation, which was then converted into area output using an electric energy conversion factor. This research aims to compare the energy efficiency of solar PV systems and solar thermal systems. Results: Using the conversion formula between electrical and thermal energy, we can compare the energy output of solar heating systems and solar photovoltaic systems. The comparative study draws upon data from February 2021 to February 2023, wherein the solar heating system generated an average of 2.54 kWh of energy per panel per day, while the solar photovoltaic system produced 1.17 kWh of energy per panel per day, resulting in a difference of approximately 2.17 times between the two systems. Conclusions: After conducting statistical analysis and comparisons, it was found that solar thermal heating systems offer higher energy and greater benefits than solar photovoltaic systems. Furthermore, an examination of literature data and simulations of the energy and economic benefits of solar thermal water systems and solar-assisted heat pump systems revealed that solar thermal water systems have higher energy density values, shorter recovery periods, and lower power consumption than solar-assisted heat pump systems. Through monitoring and empirical research in this study, it has been concluded that a heat pump-assisted solar thermal water system represents a relatively superior energy-saving and carbon-reducing solution for medical institutions. Not only can this system help reduce overall electricity consumption and the use of fossil fuels, but it can also provide more effective heating solutions.

Keywords: sustainable development, energy conservation, carbon reduction, renewable energy, heat pump system

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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

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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

Procedia PDF Downloads 302

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 152

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 528

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

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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: Soumyadeep Bhaduri, Rahul Ghosh, Rahul Shukla, Manaswini Behera

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The textile industry consumes a substantial amount of water throughout the processing and production of textile fabrics. The water eventually turns into wastewater, where it acts as an immense damaging nuisance due to its dye content. Wastewater streams contain a percentage ranging from 2.0% to 50.0% of the total weight of dye used, depending on the dye class. The management of dye effluent in textile industries presents a formidable challenge to global sustainability. The current focus is on implementing wastewater treatment technology that enable the recycling of wastewater, reduce energy usage and offset carbon emissions. Microbial fuel cell (MFC) is a device that utilizes microorganisms as a bio-catalyst to effectively treat wastewater while also producing electricity. The MFC harnesses the chemical energy present in wastewater by oxidizing organic compounds in the anodic chamber and reducing an electron acceptor in the cathodic chamber, thereby generating electricity. This research investigates the potential of MFCs to tackle this challenge of azo dye removal with simultaneously generating electricity. Although MFCs are well-established for wastewater treatment, their application in dye decolorization with concurrent electricity generation remains relatively unexplored. This study aims to address this gap by assessing the effectiveness of MFCs as a sustainable solution for treating wastewater containing azo dyes. By harnessing microorganisms as biocatalysts, MFCs offer a promising avenue for environmentally friendly dye effluent management. The performance of MFCs in treating azo dyes and generating electricity was evaluated by optimizing the Chemical Oxygen Demand (COD) and Hydraulic Retention Time (HRT) of influent. COD and HRT values ranged from 1600 mg/L to 2400 mg/L and 5 to 9 days, respectively. Results showed that the maximum open circuit voltage (OCV) reached 648 mV at a COD of 2400 mg/L and HRT of 5 days. Additionally, maximum COD removal of 98% and maximum color removal of 98.91% were achieved at a COD of 1600 mg/L and HRT of 9 days. Furthermore, the study observed a maximum power density of 19.95 W/m3 at a COD of 2400 mg/L and HRT of 5 days. Electrochemical analysis, including linear sweep voltammetry (LSV), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were done to find out the response current and internal resistance of the system. To optimize pH and dye concentration, pH values were varied from 4 to 10, and dye concentrations ranged from 25 mg/L to 175 mg/L. The highest voltage output of 704 mV was recorded at pH 7, while a dye concentration of 100 mg/L yielded the maximum output of 672 mV. This study demonstrates that MFCs offer an efficient and sustainable solution for treating azo dyes in textile industry wastewater, while concurrently generating electricity. These findings suggest the potential of MFCs to contribute to environmental remediation and sustainable development efforts on a global scale.

Keywords: textile wastewater treatment, microbial fuel cell, renewable energy, sustainable wastewater treatment

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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

Procedia PDF Downloads 221

Authors: Ahlam Said Al Azkawi, Nallusamy Sivakumar, Saif Nasser Al Bahri

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Diverse approaches and pathways are under development with the determination to develop cellulosic biofuels and other bio-products eventually at commercial scale in “bio-refineries”; however, the key challenge is mainly the high level of complexity in processing the feedstock which is complicated and energy consuming. To overcome the complications in utilizing the naturally occurring lignocellulose biomass, using waste paper as a feedstock for bio-production may solve the problem. Besides being abundant and cheap, bioprocessing of waste paper has evolved in response to the public concern from rising landfill cost from shrinking landfill capacity. Cardboard (CB) is one of the major components of municipal solid waste and one of the most important items to recycle. Although 50-70% of cardboard constitute is known to be cellulose and hemicellulose, the presence of lignin around them cause hydrophobic cross-link which physically obstructs the hydrolysis by rendering it resistant to enzymatic cleavage. Therefore, pretreatment is required to disrupt this resistance and to enhance the exposure of the targeted carbohydrates to the hydrolytic enzymes. Several pretreatment approaches have been explored, and the best ones would be those can influence cellulose conversion rates and hydrolytic enzyme performance with minimal or less cost and downstream processes. One of the promising strategies in this field is the application of surfactants, especially non-ionic surfactants. In this study, triton-X 100 was used as surfactants to treat cardboard prior enzymatic hydrolysis and compare it with acid treatment using 0.1% H2SO4. The effect of the surfactant enhancement was evaluated through its effect on hydrolysis rate in respect to time in addition to evaluating the structural changes and modification by scanning electron microscope (SEM) and X-ray diffraction (XRD) and through compositional analysis. Further work was performed to produce ethanol from CB treated with triton-X 100 via separate hydrolysis and fermentation (SHF) and simultaneous saccharification and fermentation (SSF). The hydrolysis studies have demonstrated enhancement in saccharification by 35%. After 72 h of hydrolysis, a saccharification rate of 98% was achieved from CB enhanced with triton-X 100, while only 89 of saccharification achieved from acid pre-treated CB. At 120 h, the saccharification % exceeded 100 as reducing sugars continued to increase with time. This enhancement was not supported by any significant changes in the cardboard content as the cellulose, hemicellulose and lignin content remained same after treatment, but obvious structural changes were observed through SEM images. The cellulose fibers were clearly exposed with very less debris and deposits compared to cardboard without triton-X 100. The XRD pattern has also revealed the ability of the surfactant in removing calcium carbonate, a filler found in waste paper known to have negative effect on enzymatic hydrolysis. The cellulose crystallinity without surfactant was 73.18% and reduced to 66.68% rendering it more amorphous and susceptible to enzymatic attack. Triton-X 100 has proved to effectively enhance CB hydrolysis and eventually had positive effect on the ethanol yield via SSF. Treating cardboard with only triton-X 100 was a sufficient treatment to enhance the enzymatic hydrolysis and ethanol production.

Keywords: cardboard, enhancement, ethanol, hydrolysis, treatment, Triton-X 100

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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: 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: Taher Abofol, Eldad Yechiam, Thorsten Pachur

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In four studies, we examined whether seller and buyers differ not only in subjective price levels for objects (i.e., the endowment effect) but also in their relative accuracy given objects varying in expected value. If, as has been proposed, sellers stand to accrue a more substantial loss than buyers do, then their pricing decisions should be more sensitive to expected-value differences between objects. This is implied by loss aversion due to the steeper slope of prospect theory’s value function for losses than for gains, as well as by loss attention account, which posits that losses increase the attention invested in a task. Both accounts suggest that losses increased sensitivity to relative values of different objects, which should result in better alignment of pricing decisions to the objective value of objects on the part of sellers. Under loss attention, this characteristic should only emerge under certain boundary conditions. In Study 1 a published dataset was reanalyzed, in which 152 participants indicated buying or selling prices for monetary lotteries with different expected values. Relative EV sensitivity was calculated for participants as the Spearman rank correlation between their pricing decisions for each of the lotteries and the lotteries' expected values. An ANOVA revealed a main effect of perspective (sellers versus buyers), F(1,150) = 85.3, p < .0001 with greater EV sensitivity for sellers. Study 2 examined the prediction (implied by loss attention) that the positive effect of losses on performance emerges particularly under conditions of time constraints. A published dataset was reanalyzed, where 84 participants were asked to provide selling and buying prices for monetary lotteries in three deliberations time conditions (5, 10, 15 seconds). As in Study 1, an ANOVA revealed greater EV sensitivity for sellers than for buyers, F(1,82) = 9.34, p = .003. Importantly, there was also an interaction of perspective by deliberation time. Post-hoc tests revealed that there were main effects of perspective both in the condition with 5s deliberation time, and in the condition with 10s deliberation time, but not in the 15s condition. Thus, sellers’ EV-sensitivity advantage disappeared with extended deliberation. Study 3 replicated the design of study 1 but administered the task three times to test if the effect decays with repeated presentation. The results showed that the difference between buyers and sellers’ EV sensitivity was replicated in repeated task presentations. Study 4 examined the loss attention prediction that EV-sensitivity differences can be eliminated by manipulations that reduce the differential attention investment of sellers and buyers. This was carried out by randomly mixing selling and buying trials for each participant. The results revealed no differences in EV sensitivity between selling and buying trials. The pattern of results is consistent with an attentional resource-based account of the differences between sellers and buyers. Thus, asking people to price, an object from a seller's perspective rather than the buyer's improves the relative accuracy of pricing decisions; subtle changes in the framing of one’s perspective in a trading negotiation may improve price accuracy.

Keywords: decision making, endowment effect, pricing, loss aversion, loss attention

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Authors: Shayma Mohammed, Adel Trabelsi

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Radiopharmacy is the art of preparing high-quality, radioactive, medicinal products for use in diagnosis and therapy. Radiopharmaceuticals unlike normal medicines, this dual aspect (radioactive, medical) makes their management highly critical. One of the most convincing applications of modern technologies is the ability to delegate the execution of repetitive tasks to programming scripts. Automation has found its way to the most skilled jobs, to improve the company's overall performance by allowing human workers to focus on more important tasks than document filling. This project aims to contribute to implement a comprehensive system to insure rigorous management of radiopharmaceuticals through the use of a platform that links the Nuclear Medicine Service Management System to the Nuclear Radio-pharmacy Management System in accordance with the recommendations of World Health Organization (WHO) and International Atomic Energy Agency (IAEA). In this project we attempt to build a web application that targets radiopharmacies, the platform is built atop the inherently compatible web stack which allows it to work in virtually any environment. Different technologies are used in this project (PHP, Symfony, MySQL Workbench, Bootstrap, Angular 7, Visual Studio Code and TypeScript). The operating principle of the platform is mainly based on two parts: Radiopharmaceutical Backoffice for the Radiopharmacian, who is responsible for the realization of radiopharmaceutical preparations and their delivery and Medical Backoffice for the Doctor, who holds the authorization for the possession and use of radionuclides and he/she is responsible for ordering radioactive products. The application consists of sven modules: Production, Quality Control/Quality Assurance, Release, General Management, References, Transport and Stock Management. It allows 8 classes of users: The Production Manager (PM), Quality Control Manager (QCM), Stock Manager (SM), General Manager (GM), Client (Doctor), Parking and Transport Manager (PTM), Qualified Person (QP) and Technical and Production Staff. Digital platform bringing together all players involved in the use of radiopharmaceuticals and integrating the stages of preparation, production and distribution, Web technologies, in particular, promise to offer all the benefits of automation while requiring no more than a web browser to act as a user client, which is a strength because the web stack is by nature multi-platform. This platform will provide a traceability system for radiopharmaceuticals products to ensure the safety and radioprotection of actors and of patients. The new integrated platform is an alternative to write all the boilerplate paperwork manually, which is a tedious and error-prone task. It would minimize manual human manipulation, which has proven to be the main source of error in nuclear medicine. A codified electronic transfer of information from radiopharmaceutical preparation to delivery will further reduce the risk of maladministration.

Keywords: automated system, management, radiopharmacy, technical papers

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Authors: Lina Psarra, Manogj Sundaresan, Purjeet Sutar

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In response to the global imperative for sustainable solutions, this article proposes the development of a comprehensive circularity index applicable to a wide range of products across various industries. The absence of a consensus on using a universal metric to assess circularity performance presents a significant challenge in prioritizing and effectively managing sustainable initiatives. This circularity index serves as a quantitative measure to evaluate the adherence of products, processes, and systems to the principles of a circular economy. Unlike traditional distinct metrics such as recycling rates or material efficiency, this index considers the entire lifecycle of a product in one single metric, also incorporating additional factors such as reusability, scarcity of materials, reparability, and recyclability. Through a systematic approach and by reviewing existing metrics and past methodologies, this work aims to address this gap by formulating a circularity index that can be applied to diverse product portfolio and assist in comparing the circularity of products on a scale of 0%-100%. Project objectives include developing a formula, designing and implementing a pilot tool based on the developed Product Circularity Index (PCI), evaluating the effectiveness of the formula and tool using real product data, and assessing the feasibility of integration into various sustainability initiatives. The research methodology involves an iterative process of comprehensive research, analysis, and refinement where key steps include defining circularity parameters, collecting relevant product data, applying the developed formula, and testing the tool in a pilot phase to gather insights and make necessary adjustments. Major findings of the study indicate that the PCI provides a robust framework for evaluating product circularity across various dimensions. The Excel-based pilot tool demonstrated high accuracy and reliability in measuring circularity, and the database proved instrumental in supporting comprehensive assessments. The PCI facilitated the identification of key areas for improvement, enabling more informed decision-making towards circularity and benchmarking across different products, essentially assisting towards better resource management. In conclusion, the development of the Product Circularity Index represents a significant advancement in global sustainability efforts. By providing a standardized metric, the PCI empowers companies and stakeholders to systematically assess product circularity, track progress, identify improvement areas, and make informed decisions about resource management. This project contributes to the broader discourse on sustainable development by offering a practical approach to enhance circularity within industrial systems, thus paving the way towards a more resilient and sustainable future.

Keywords: circular economy, circular metrics, circularity assessment, circularity tool, sustainable product design, product circularity index

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Authors: James G. Matthew, Seonmin Huh, Frank X. Bennett

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English for Specific Purposes, ESP, aims to equip learners with necessary English language skills. Many ESP programs address language skills for job performance, including reading job related documents and oral proficiency. Within ESP is English for occupational purposes, EOP, which centers around developing communicative competence for the globalized workplace. Many ESP and EOP courses lack the content needed to assist students to progress at work, resulting in the need to create lexical compilation for different professions. It is important to teach communicative competence and soft skills for real job-related problem situations and address the complexities of the real world to help students to be successful in their professions. ESP and EOP research is therefore trying to balance both profession-specific educational contents as well as international multi-disciplinary language skills for the globalized workforce. The current study will build upon the existing discussion by developing pedagogy to assist students in their career through developing a strong practical command of relevant English vocabulary. Our research question focuses on the pedagogy two professors incorporated in their English for employment courses. The current study is a qualitative case study on the modes of teaching delivery for EOP in South Korea. Two foreign professors teaching at two different universities in South Korea volunteered for the study to explore their teaching practices. Both professors’ curriculums included the components of employment-related concept vocabulary, business presentations, CV/resume and cover letter preparation, and job interview preparation. All the pre-made recorded video lectures, live online class sessions with students, teachers’ lesson plans, teachers’ class materials, students’ assignments, and midterm and finals video conferences were collected for data analysis. The study then focused on unpacking representative patterns in their teaching methods. The professors used their strengths as native speakers to extend the class discussion from narrow and restricted conversations to giving students broader opportunities to practice authentic English conversation. The methods of teaching utilized three main steps to extend the conversation. Firstly, students were taught concept vocabulary. Secondly, the vocabulary was then combined in speaking activities where students had to solve scenarios, and the students were required to expand on the given forms of words and language expressions. Lastly, the students had conversations in English, using the language learnt. The conversations observed in both classes were those of authentic, expanded English communication and this way of expanding concept vocabulary lessons into extended conversation is one representative pedagogical approach that both professors took. Extended English conversation, therefore, is crucial for EOP education.

Keywords: concept vocabulary, english as a foreign language, english for employment, extended conversation

Procedia PDF Downloads 92

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 41

Authors: Arinze Ezieke, Antonio Serrano, William Clarke, Denys Villa-Gomez

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Berry cultivation results in discharge of high organic strength putrescible solid waste which potentially contributes to environmental degradation, making it imperative to assess options for its complete management. Anaerobic digestion (AD) could be an ideal option when the target is energy generation; however, due to berry fruit characteristics high carbohydrate composition, the technology could be limited by its high alkalinity requirement which suggests dosing of additives such as buffers and trace elements supplement. Overcoming this limitation in an economically viable way could entail replacement of synthetic additives with recycled by-product waste. Consequently, ash from co-smouldering of high COD characteristic AD digestate and coco-coir could be a promising material to be used to enhance the AD of berry fruit waste, given its characteristic high pH, alkalinity and metal concentrations which is typical of synthetic additives. Therefore, the aim of the research was to evaluate the stability and process performance from the AD of BFW when ash from co-smoldered digestate and coir are supplemented as alkalinity and trace elements (TEs) source. Series of batch experiments were performed to ascertain the necessity for alkalinity addition and to see whether the alkalinity and metals in the co-smouldered digestate ash can provide the necessary buffer and TEs for AD of berry fruit waste. Triplicate assays were performed in batch systems following I/S of 2 (in VS), using serum bottles (160 mL) sealed and placed in a heated room (35±0.5 °C), after creating anaerobic conditions. Control experiment contained inoculum and substrates only, and inoculum, substrate and NaHCO3 for optimal total alkalinity concentration and TEs assays, respectively. Total alkalinity concentration refers to alkalinity of inoculum and the additives. The alkalinity and TE potential of the ash were evaluated by supplementing ash (22.574 g/kg) of equivalent total alkalinity concentration to that of the pre-determined optimal from NaHCO3, and by dosing ash (0.012 – 7.574 g/kg) of varying concentrations of specific essential TEs (Co, Fe, Ni, Se), respectively. The result showed a stable process at all examined conditions. Supplementation of 745 mg/L CaCO3 NaHCO3 resulted to an optimum TAC of 2000 mg/L CaCO3. Equivalent ash supplementation of 22.574 g/kg allowed the achievement of this pre-determined optimum total alkalinity concentration, resulting to a stable process with a 92% increase in the methane production rate (323 versus 168 mL CH4/ (gVS.d)), but a 36% reduction in the cumulative methane production (103 versus 161 mL CH4/gVS). Addition of ashes at incremental dosage as TEs source resulted to a reduction in the Cumulative methane production, with the highest dosage of 7.574 g/kg having the highest effect of -23.5%; however, the seemingly immediate bioavailability of TE at this high dosage allowed for a +15% increase in the methane production rate. With an increased methane production rate, the results demonstrated that the ash at high dosages could be an effective supplementary material for either a buffered or none buffered berry fruit waste AD system.

Keywords: anaerobic digestion, alkalinity, co-smoldered digestate ash, trace elements

Procedia PDF Downloads 119

Authors: Alexander Huang

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Online learning sessions have become an indispensable complement to in-classroom-learning sessions in the past two years due to the emergence of Covid-19. Due to social distance requirements, many courses and interaction-intensive sessions, ranging from music classes to debate camps, are online. However, online learning imposes a significant challenge for engaging students effectively during the learning sessions. To resolve this problem, Project PWR, a non-profit organization formed by high school students, developed an online kid-teach-kid learning environment to boost students' learning interests and further improve students’ engagement during online learning. Fundamentally, the kid-teach-kid learning model creates an affinity space to form learning groups, where like-minded peers can learn and teach their interests. The role of the teacher can also help a kid identify the instructional task and set the rules and procedures for the activities. The approach also structures initial discussions to reveal a range of ideas, similar experiences, thinking processes, language use, and lower student-to-teacher ratio, which become enriched online learning experiences for upcoming lessons. In such a manner, a kid can practice both the teacher role and the student role to accumulate experiences on how to convey ideas and questions over the online session more efficiently and effectively. In this research work, we conducted two case studies involving a 3D-Design course and a Speech and Debate course taught by high-school kids. Through Project PWR, a kid first needs to design the course syllabus based on a provided template to become a student-teacher. Then, the Project PWR academic committee evaluates the syllabus and offers comments and suggestions for changes. Upon the approval of a syllabus, an experienced and voluntarily adult mentor is assigned to interview the student-teacher and monitor the lectures' progress. Student-teachers construct a comprehensive final evaluation for their students, which they grade at the end of the course. Moreover, each course requires conducting midterm and final evaluations through a set of surveyed replies provided by students to assess the student-teacher’s performance. The uniqueness of Project PWR lies in its established kid-teach-kids affinity space. Our research results showed that Project PWR could create a closed-loop system where a student can help a teacher improve and vice versa, thus improving the overall students’ engagement. As a result, Project PWR’s approach can train teachers and students to become better online learners and give them a solid understanding of what to prepare for and what to expect from future online classes. The kid-teach-kid learning model can significantly improve students' engagement in the online courses through the Project PWR to effectively supplement the traditional teacher-centric model that the Covid-19 pandemic has impacted substantially. Project PWR enables kids to share their interests and bond with one another, making the online learning environment effective and promoting positive and effective personal online one-on-one interactions.

Keywords: kid-teach-kid, affinity space, online learning, engagement, student-teacher

Procedia PDF Downloads 141