Search results for: automatic identification system

Authors: Peterson Thokozani Ngema, Paramespri Naidoo, Amir H. Mohammadi, Deresh Ramjugernath

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Phase equilibrium data (dissociation data) for clathrate hydrate (gas hydrate) were undertaken for systems involving fluorinated refrigerants with a single and mixed electrolytes (NaCl, CaCl₂, MgCl₂, and Na₂SO₄) aqueous solution at various salt concentrations in the absence and presence of cyclopentane (CP). The ternary systems for (R410a or R507) with the water system in the presence of CP were performed in the temperature and pressures ranges of (279.8 to 294.4) K and (0.158 to 1.385) MPa, respectively. Measurements for R410a with single electrolyte {NaCl or CaCl₂} solution in the presence of CP were undertaken at salt concentrations of (0.10, 0.15 and 0.20) mass fractions in the temperature and pressure ranges of (278.4 to 293.7) K and (0.214 to1.179) MPa, respectively. The temperature and pressure conditions for R410a with Na₂SO₄ aqueous solution system were investigated at a salt concentration of 0.10 mass fraction in the range of (283.3 to 291.6) K and (0.483 to 1.373) MPa respectively. Measurements for {R410a or R507} with mixed electrolytes {NaCl, CaCl₂, MgCl₂} aqueous solution was undertaken at various salt concentrations of (0.002 to 0.15) mass fractions in the temperature and pressure ranges of (274.5 to 292.9) K and (0.149 to1.119) MPa in the absence and presence of CP, in which there is no published data related to mixed salt and a promoter. The phase equilibrium measurements were performed using a non-visual isochoric equilibrium cell that co-operates the pressure-search technique. This study is focused on obtaining equilibrium data that can be utilized to design and optimize industrial wastewater, desalination process and the development of Hydrate Electrolyte–Cubic Plus Association (HE–CPA) Equation of State. The results show an impressive improvement in the presence of promoter (CP) on hydrate formation because it increases the dissociation temperatures near ambient conditions. The results obtained were modeled using a developed HE–CPA equation of state. The model results strongly agree with the measured hydrate dissociation data.

Keywords: association, desalination, electrolytes, promoter

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: A. T. Perez Fontenla, S. Sgobba, A. Bartkowska, Y. Askar, M. Dalemir Celuch, A. Newborough, M. Karppinen, H. Haalien, S. Deleval, S. Larcher, C. Charvet, L. Bruno, R. Trant

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The present study investigates the corrosion behavior of copper (Cu) based conducts predominantly brazed with Sil-Fos (self-fluxing copper-based filler with silver and phosphorus) within various cooling circuits of demineralized water across different particle accelerator components at CERN. The study covers a range of sample service time, from a few months to fifty years, and includes various accelerator components such as quadrupoles, dipoles, and bending magnets. The investigation comprises the established sample extraction procedure, examination methodology including non-destructive testing, evaluation of the corrosion phenomena, and identification of commonalities across the studied components as well as analysis of the environmental influence. The systematic analysis included computed microtomography (CT) of the joints that revealed distributed defects across all brazing interfaces. Some defects appeared to result from areas not wetted by the filler during the brazing operation, displaying round shapes, while others exhibited irregular contours and radial alignment, indicative of a network or interconnection. The subsequent dry cutting performed facilitated access to the conduct's inner surface and the brazed joints for further inspection through light and electron microscopy (SEM) and chemical analysis via Energy Dispersive X-ray spectroscopy (EDS). Brazing analysis away from affected areas identified the expected phases for a Sil-Fos alloy. In contrast, the affected locations displayed micrometric cavities propagating into the material, along with selective corrosion of the bulk Cu initiated at the conductor-braze interface. Corrosion product analysis highlighted the consistent presence of sulfur (up to 6 % in weight), whose origin and role in the corrosion initiation and extension is being further investigated. The importance of this study is paramount as it plays a crucial role in comprehending the underlying factors contributing to recently identified water leaks and evaluating the extent of the issue. Its primary objective is to provide essential insights for the repair of impacted brazed joints when accessibility permits. Moreover, the study seeks to contribute to the improvement of design and manufacturing practices for future components, ultimately enhancing the overall reliability and performance of magnet systems within CERN accelerator facilities.

Keywords: accelerator facilities, brazed copper conducts, demineralized water, magnets

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Authors: M. R. Rouhi, S. Shafiei, A. Taghavipour, H. Adibi-Asl, A. Doosthoseini

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This research targets at alleviating the problem of range anxiety associated with the battery electric vehicles (BEVs) by considering mechanical and control aspects of the powertrain. In this way, all the energy consuming components and their effect on reducing the range of the BEV and battery life index are identified. On the other hand, an appropriate control strategy is designed to guarantee the performance of the BEV and the extended electric range which is evaluated by an extensive simulation procedure and a real-world driving schedule.

Keywords: battery, electric vehicles, ultra-capacitor, model predictive control

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Fabricio Costa Silva, Samuel Xavier de Souza

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A Global Positioning System (GPS) receiver is responsible to determine position, velocity and timing information by using satellite information. To get this information's are necessary to combine an incoming and a locally generated signal. The procedure called acquisition need to found two information, the frequency and phase of the incoming signal. This is very time consuming, so there are several techniques to reduces the computational complexity, but each of then put projects issues in conflict. I this papers we present a method that can reduce the computational complexity by reducing the search space and paralleling the search.

Keywords: GPS, acquisition, low complexity, parallelism

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Authors: Meri Khakhutaishvili, Indira Djaparidze, Maia Vanidze, Aleko Kalandia

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Cultivation of blueberry in Georgia started in 21st century. There are more than 20 species of blueberry cultivated in this region from all other the world. The species are mostly planted on acidic soil, previously occupied by tea plantations. Many of the plantations have pretty good yield. It is known that changing the location of a plant to a new soil or climate effects chemical compositions of the plant. However, even though these plants are brought from other countries, no research has been conducted to fully examine the blueberry fruit cultivated in Georgia. Shota Rustaveli National Science Foundation Grant FR/335/10-160/14, gave us an opportunity to continue our previous works and conduct research on several berries, among them of course the chemical composition of stored Blueberry. We were able to conduct the first study that included examining qualitative and quantitative features of bioactive compounds in Georgian Blueberry. This experiments were held in the ‘West Georgia Regional Chromatography center’ (Grant AP/96/13) of our university, that is equipped with modern equipment like HPLC UV-Vis, RI-detector, HPLC-conductivity detector, UPLC-MS-detector. Biochemical analysis was conducted using different physico-chemical and instrumental methods. Separation-identification and quantitative analysis were conducted using UPLC-MS (Waters Acquity QDa detector), HPLC (Waters Brceze 1525, UV-Vis 2489 detectors), pH-meters (Mettler Toledo). Refractrometer -Misco , Spectrometer –Cuvette Changer (Mettler Toledo UV5A), C18 Cartridge Solid Phase Extraction (SPE) Waters Sep-Pak C18 (500 mg), Chemicals – stability radical- 2,2-Diphenil-1-picrilhydrazyl (Aldrich-germany), Acetonitrile, Methanol, Acetic Acid (Merck-Germany), AlCl3, Folin Ciocalteu reagent (preparation), Standarts –Callic acid, Quercetin. Carbohydrate HPLC-RI analysis used systems acetonitrile-water (80-20). UPLC-MS analysis used systems- solvent A- Water +1 % acetic acid და solvent -B Methanol +1% acetic acid). It was concluded that the amount of sugars was in range of 5-9 %, mostly glucose and fructose. Also, the amount of organic acids was 0.2-1.2% most of which was malic and citric acid. Anthocians were also present in the sample 200-550mg/100g. We were able to identify up to 15 different compounds, most of which were products of delphinidine and cyanide. All species have high antioxidant level(DPPH). By rapidly freezing the sample and then keeping it in specific conditions allowed us to keep the sample for 12 months.

Keywords: antioxidants, bioactive, blueberry, storage

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Authors: Hamzah Kamil Adeyemi, Oyesikun Abayomi Nathaniel

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The plural nature of Nigeria state has created a leadership gap in the 21st century. The leadership problem encapsulated socio-economic system has called for a reorientation in youth to channel a programme that will redeem the image (OT) the country among the committee of nations and chart a way forward in bailing the country out of bad governance unemployment corruption and other anti-development policies. The touth need to raise up to the challenges of nation building. This study engaged theoretical analysis, both written records was used to add value to its quality and recommendation was made with conclusion.

Keywords: youth, education, unempolyment, rebranding, Nigeria

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Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

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The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

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Authors: Catherine Constantinidis (Nee Tsacalos)

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This paper presents one aspect of the larger Masters qualitative study exploring the roles of married Greek Orthodox clergy, the Priest and Presbytera, under the wing of the Greek Orthodox Archdiocese of Australia. This ground breaking research necessitated the creation of primary data within a phenomenological paradigm drawing from lived experiences of the Priests and Presbyteres in contemporary society. As a Social Worker, a bilingual (Greek/English) Mental Health practitioner and a Presbytera, the questions constantly raised and pondered are: Who do the Priest and Presbytera turn to when they experience difficulties or problems? Where do they go for support? What is in place for their emotional and psychological health and well-being? Who cares for the spiritual carer? Who is there to catch our falling clergy and their wives? What is their 'safety net'? Identified phenomena of angst, stress, frustration and confusion experienced by the Priest and (by extension) the Presbytera, within their position, coupled with basic assumptions, perceptions and expectations about their roles, the role of the organisation (the Church), and their role as spouse often caused confusion and in some cases conflict. Unpacking this complex and multi-dimensional relationship highlighted not only the roller coaster of emotions, potentially affecting their physical and mental health, but also the impact on the interwoven relationships of marriage and ministry. The author considers these phenomena in the light of bilingual cultural and religious organisational practice frameworks, specifically the Greek Orthodox Church, whilst filtering these findings through a mental health lens. One could argue that it is an expectation that clergy (and by default their wives) take on the responsibility to be kind, nurturing and supportive to others. However, when it comes to taking care of self, they are not nearly as kind. This research looks at a recurrent theme throughout the interviews where all participants talked about limited support systems and poor self care strategies and the impact this has on their ministry, mental, emotional, and physical health and ultimately on their relationships with self and others. The struggle all participants encountered at some point in their ministry was physical, spiritual and psychological burn out. The overall aim of the researcher is to provide a voice for the Priest and the Presbytera painting a clearer picture of these roles and facilitating an awareness of struggles and dilemmas faced in their ministry. It is hoped these identified gaps in self care strategies and support systems will provide solid foundations for building a culturally sensitive, empathetic and effective support system framework, incorporating the spiritual and psychological well-being of the Priest and Presbytera, a ‘safety net’. A supplementary aim is to inform and guide ministry practice frameworks for clergy, spouses, the church hierarchy and religious organisations on a local and global platform incorporating some sort of self-care system.

Keywords: care for the carer, mental health, Priest, Presbytera, religion, support system

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Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: Michael Shandalov, Tzvi Templeman, Michael Schmidt, Itzhak Kelson, Eyal Yahel

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We present a new method to produce a model system for the study of radiation damage in non-radioactive materials. The method is based on homogeneously incorporating 228Th ions in PbS thin films using a small volume chemical bath deposition (CBD) technique. The common way to alloy metals with radioactive elements is by melting pure elements, which requires considerable amounts of radioactive material with its safety consequences such as high sample activity. Controlled doping of the thin films with (very) small amounts (100-200ppm) of radioactive elements such as thorium is expected to provide a unique path for studying radiation damage in materials due to decay processes without the need of sealed enclosure. As a first stage, we developed CBD process for controlled doping of PbS thin films (~100 nm thick) with the stable isotope (t1/2~106 years), 232Th. Next, we developed CBD process for controlled doping of PbS thin films with active 228Th isotope. This was achieved by altering deposition parameters such as temperature, pH, reagent concentrations and time. The 228Th-doped films were characterized using X-ray diffraction, which indicated a single phase material. Film morphology and thickness were determined using scanning electron microscopy (SEM). Energy dispersive spectroscopy (EDS) mapping in the analytical transmission electron microscope (A-TEM), X-ray photoelectron spectroscopy (XPS) depth profiles and autoradiography indicated that the Th ions were homogeneously distributed throughout the films, suggesting Pb substitution by Th ions in the crystal lattice. The properties of the PbS (228Th) film activity were investigated by using alpha-spectroscopy and gamma spectroscopy. The resulting films are applicable for isochronal annealing of resistivity measurements and currently under investigation. This work shows promise as a model system for the analysis of dilute defect systems in semiconductor thin films.

Keywords: thin films, doping, radiation damage, chemical bath deposition

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Authors: Niharika Kaushal, Minni Singh

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Citrus fruits contain an abundance of phytochemicals that can promote health. A substantial amount of agrowaste is produced from the juice processing industries, primarily peels and seeds. This leftover agrowaste is a reservoir of nutraceuticals, particularly bioflavonoids which render it antioxidant and potentially anticancerous. It is, therefore, favorable to utilize this biomass and contribute towards sustainability in a manner that value-added products may be derived from them, nutraceuticals, in this study. However, the pre-systemic metabolism of flavonoids in the gastric phase limits the effectiveness of these bioflavonoids derived from mandarin biomass. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was explored for its flavonoid profile. This work entails supercritical fluid extraction and identification of bioflavonoids from mandarin biomass. Furthermore, to overcome the limitations of these flavonoids in the gastrointestinal tract, a double-layered vehicular mechanism comprising the fabrication of nanoconjugates and edible hydrogels was adopted. Total flavonoids in the mandarin peel extract were estimated by the aluminum chloride complexation method and were found to be 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the abundance of polymethoxyflavones (PMFs), nobiletin and tangeretin as the major flavonoids in the extract, followed by hesperetin and naringenin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which showed an IC50 of 0.55μg/ml. Nanoconjugates were fabricated via the solvent evaporation method, which was further impregnated into hydrogels. Additionally, the release characteristics of nanoconjugate-laden hydrogels in a simulated gastrointestinal environment were studied. The PLGA-PMFs nanoconjugates exhibited a particle size between 200-250nm having a smooth and spherical shape as revealed by FE-SEM. The impregnated alginate hydrogels offered a dense network that ensured the holding of PLGA-PMF nanoconjugates, as confirmed by Cryo-SEM images. Rheological studies revealed the shear-thinning behavior of hydrogels and their high resistance to deformation. Gastrointestinal studies showed a negligible 4.0% release of flavonoids in the gastric phase, followed by a sustained release over the next hours in the intestinal environment. Therefore, based on the enormous potential of recovering nutraceuticals from agro-processing wastes, further augmented by nanotechnological interventions for enhancing the bioefficacy of these compounds, lays the foundation for exploring the path towards the development of value-added products, thereby contributing towards the sustainable use of agrowaste.

Keywords: agrowaste, gastrointestinal, hydrogel, nutraceuticals

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Authors: Rajeev Ravindran, Amit K. Jaiswal

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Waste from the food-processing industry is produced in large amount and contains high levels of lignocellulose. Due to continuous accumulation throughout the year in large quantities, it creates a major environmental problem worldwide. The chemical composition of these wastes (up to 75% of its composition is contributed by polysaccharide) makes it inexpensive raw material for the production of value-added products such as biofuel, bio-solvents, nanocrystalline cellulose and enzymes. In order to use lignocellulose as the raw material for the microbial fermentation, the substrate is subjected to enzymatic treatment, which leads to the release of reducing sugars such as glucose and xylose. However, the inherent properties of lignocellulose such as presence of lignin, pectin, acetyl groups and the presence of crystalline cellulose contribute to recalcitrance. This leads to poor sugar yields upon enzymatic hydrolysis of lignocellulose. A pre-treatment method is generally applied before enzymatic treatment of lignocellulose that essentially removes recalcitrant components in biomass through structural breakdown. Present study is carried out to find out the best pre-treatment method for the maximum liberation of reducing sugars from spent coffee waste (SPW). SPW was subjected to a range of physical, chemical and physico-chemical pre-treatment followed by a sequential, combinatorial pre-treatment strategy is also applied on to attain maximum sugar yield by combining two or more pre-treatments. All the pre-treated samples were analysed for total reducing sugar followed by identification and quantification of individual sugar by HPLC coupled with RI detector. Besides, generation of any inhibitory compounds such furfural, hydroxymethyl furfural (HMF) which can hinder microbial growth and enzyme activity is also monitored. Results showed that ultrasound treatment (31.06 mg/L) proved to be the best pre-treatment method based on total reducing content followed by dilute acid hydrolysis (10.03 mg/L) while galactose was found to be the major monosaccharide present in the pre-treated SPW. Finally, the results obtained from the study were used to design a sequential lignocellulose pre-treatment protocol to decrease the formation of enzyme inhibitors and increase sugar yield on enzymatic hydrolysis by employing cellulase-hemicellulase consortium. Sequential, combinatorial treatment was found better in terms of total reducing yield and low content of the inhibitory compounds formation, which could be due to the fact that this mode of pre-treatment combines several mild treatment methods rather than formulating a single one. It eliminates the need for a detoxification step and potential application in the valorisation of lignocellulosic food waste.

Keywords: lignocellulose, enzymatic hydrolysis, pre-treatment, ultrasound

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Authors: M. D. Antoine

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Despite the widespread use of complementary and alternative medicine (CAM) for autistic children, little is known about the communication flow between the different parties involved in autism care (e.g., parents/caregivers, conventional providers, alternative practitioners). This study aimed to describe how communication occurs through the first year following an autism spectrum disorder (ASD) diagnosis to identify challenges and potential barriers to communication within the healthcare system in Ottawa, Canada. From an ecological perspective, we collected qualitative data through 12 semi-structured interviews with six parents/caregivers, three conventional providers (e.g., family doctor, neurodevelopmental pediatrician, psychologist), and three alternative practitioners (e.g., naturopath, occupational therapist, speech and language pathologist) operating in Ottawa. We interpreted the data using thematic analysis. Findings revealed communication challenges between the parents/caregivers and conventional providers while they experience better communication flow with fewer challenges in alternative care settings. However, parents/caregivers are the only links between the health professionals of both streams. From the five contexts examined: organizational, interpersonal, media, cultural, and political-legal, we found four themes (provider knowledge, care integration, flexible care, and time constraints) underlining specific barriers to communication flow between the parties involved in the care of autistic children. The increasing interest in alternative medicine is forcing changes in the healthcare system. Communications occur outside the norms making openings for better communication and information-sharing increasingly essential. Within the identified themes in the current study, the necessity for better communication between all parties involved in the care of autistic children is evident. More ASD and CAM-related training for providers would support effective parent/caregiver-provider communication. The findings of the current study contribute to a better understanding of the role of communication in the care management of autism, which has implications for effective autism care.

Keywords: alternative medicine, autism care management, autism spectrum disorder, conventional medicine, parent-provider communication

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Authors: Nazish Badar

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In early 2009, Pandemic type A (H1N1) Influenza virus emerged globally. Since then, it has continued circulation causing considerable morbidity and mortality. The purpose of this study was to evaluate the evolutionary changes in Influenza A (H1N1) pdm09 viruses from 2009-15 and their relevance with the current vaccine viruses. Methods: Respiratory specimens were collected with influenza-like illness and Severe Acute Respiratory Illness. Samples were processed according to CDC protocol. Sequencing and phylogenetic analysis of Haemagglutinin (HA) and neuraminidase (NA) genes was carried out comparing representative isolates from Pakistan viruses. Results: Between Jan2009 - Feb 2016, 1870 (13.2%) samples were positive for influenza A out of 14086. During the pandemic period (2009–10), Influenza A/ H1N1pdm 09 was the dominant strain with 366 (45%) of total influenza positives. In the post-pandemic period (2011–2016), a total of 1066 (59.6%) cases were positive Influenza A/ H1N1pdm 09 with co-circulation of different Influenza A subtypes. Overall, the Pakistan A(H1N1) pdm09 viruses grouped in two genetic clades. Influenza A(H1N1)pdm09 viruses only ascribed to Clade 7 during the pandemic period whereas viruses belong to clade 7 (2011) and clade 6B (2015) during the post-pandemic years. Amino acid analysis of the HA gene revealed mutations at positions S220T, I338V and P100S specially associated with outbreaks in all the analyzed strains. Sequence analyses of post-pandemic A(H1N1)pdm09 viruses showed additional substitutions at antigenic sites; S179N,K180Q (SA), D185N, D239G (CA), S202A (SB) and at receptor binding sites; A13T, S200P when compared with pandemic period. Substitution at Genetic markers; A273T (69%), S200P/T (15%) and D239G (7.6%) associated with severity and E391K (69%) associated with virulence was identified in viruses isolated during 2015. Analysis of NA gene revealed outbreak markers; V106I (23%) among pandemic and N248D (100%) during post-pandemic Pakistan viruses. Additional N-Glycosylation site; HA S179N (23%), NA I23T(7.6%) and N44S (77%) in place of N386K(77%) were only found in post-pandemic viruses. All isolates showed histidine (H) at position 275 in NA indicating sensitivity to neuraminidase inhibitors. Conclusion: This study shows that the Influenza A(H1N1)pdm09 viruses from Pakistan clustered into two genetic clades, with co-circulation of some variants. Certain key substitutions in the receptor binding site and few changes indicative of virulence were also detected in post-pandemic strains. Therefore, it is imperative to continue monitoring of the viruses for early identification of potential variants of high virulence or emergence of drug-resistant variants.

Keywords: Influenza A (H1N1) pdm09, evolutionary analysis, post pandemic period, Pakistan

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Authors: Valeria M. Bastos, Myrian A. Costa, Matheus Ambrozio, Nelson F. F. Ebecken

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In this paper a very simple and effective user administration view of computing clusters systems is implemented in order of friendly provide the configuration and monitoring of distributed application executions. The user view, the administrator view, and an internal control module create an illusionary management environment for better system usability. The architecture, properties, performance, and the comparison with others software for cluster management are briefly commented.

Keywords: big data, computing clusters, administration view, user view

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Authors: N. C. Shahi, Anupama Singh, E. Kate

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Drying is practiced to enhance the storage life, to minimize losses during storage, and to reduce transportation costs of agricultural products. Drying processes range from open sun drying to industrial drying. In most of the developing countries, use of fossil fuels for drying of agricultural products has not been practically feasible due to unaffordable costs to majority of the farmers. On the other hand, traditional open sun drying practiced on a large scale in the rural areas of the developing countries suffers from high product losses due to inadequate drying, fungal growth, encroachment of insects, birds and rodents, etc. To overcome these problems a middle technology dryer having low cost need to be developed for farmers. In case of mechanical dryers, the heated air is the main driving force for removal of moisture. The air is heated either electrically or by burning wood, coal, natural gas etc. using heaters. But, all these common sources have finite supplies. The lifetime is estimated to range from 15 years for a natural gas to nearly 250 years for coal. So, mankind must turn towards its safe and reliable utilization and may have undesirable side effects. The mechanical drying involves higher cost of drying and open sun drying deteriorates the quality. The solar tunnel dryer is one of promising option for drying various agricultural and agro-industrial products on large scale. The advantage of Solar tunnel dryer is its relatively cheaper cost of construction and operation. Although many solar dryers have been developed, still there is a scope of modification in them. Therefore, an attempt was made to develop Solar tunnel dryer and test its performance using highly perishable commodity i.e. leafy vegetables (spinach). The effect of air velocity, loading density and shade net on performance parameters namely, collector efficiency, drying efficiency, overall efficiency of dryer and specific heat energy consumption were also studied. Thus, the need for an intermediate level technology was realized and an effort was made to develop a small scale Solar Tunnel Dryer . A dryer consisted of base frame, semi cylindrical drying chamber, solar collector and absorber, air distribution system with chimney and auxiliary heating system, and wheels for its mobility were the main functional components. Drying of fenugreek was carried out to analyze the performance of the dryer. The Solar Tunnel Dryer temperature was maintained using the auxiliary heating system. The ambient temperature was in the range of 12-33oC. The relative humidity was found inside and outside the Solar Tunnel Dryer in the range of 21-75% and 35-79%, respectively. The solar radiation was recorded in the range of 350-780W/m2 during the experimental period. Studies revealed that total drying time was in range of 230 to 420 min. The drying time in Solar Tunnel Dryer was considerably reduced by 67% as compared to sun drying. The collector efficiency, drying efficiency, overall efficiency and specific heat consumption were determined and were found to be in the range of 50.06- 38.71%, 15.53-24.72%, 4.25 to 13.34% and 1897.54-3241.36 kJ/kg, respectively.

Keywords: overall efficiency, solar tunnel dryer, specific heat consumption, sun drying

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Authors: Orit Baruth, Anat Cohen

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Online courses have become common in many learning programs and various learning environments, particularly in higher education. Social distancing forced in response to the COVID-19 pandemic has increased the demand for these courses. Yet, despite the frequency of use, online learning is not free of limitations and may not suit all learners. Hence, the growth of online learning alongside with learners' diversity raises the question: is online learning, as it currently offered, meets the needs of each learner? Fortunately, today's technology allows to produce tailored learning platforms, namely, personalization. Personality influences learner's satisfaction and therefore has a significant impact on learning effectiveness. A better understanding of personality can lead to a greater appreciation of learning needs, as well to assists educators ensure that an optimal learning environment is provided. In the context of online learning and personality, the research on learning design according to personality traits is lacking. This study explores the relations between personality traits (using the 'Big-five' model) and students' satisfaction with five techno-pedagogical learning solutions (TPLS): discussion groups, digital books, online assignments, surveys/polls, and media, in order to provide an online learning process to students' satisfaction. Satisfaction level and personality identification of 108 students who participated in a fully online learning course at a large, accredited university were measured. Cluster analysis methods (k-mean) were applied to identify learners’ clusters according to their personality traits. Correlation analysis was performed to examine the relations between the obtained clusters and satisfaction with the offered TPLS. Findings suggest that learners associated with the 'Neurotic' cluster showed low satisfaction with all TPLS compared to learners associated with the 'Non-neurotics' cluster. learners associated with the 'Consciences' cluster were satisfied with all TPLS except discussion groups, and those in the 'Open-Extroverts' cluster were satisfied with assignments and media. All clusters except 'Neurotic' were highly satisfied with the online course in general. According to the findings, dividing learners into four clusters based on personality traits may help define tailor learning paths for them, combining various TPLS to increase their satisfaction. As personality has a set of traits, several TPLS may be offered in each learning path. For the neurotics, however, an extended selection may suit more, or alternatively offering them the TPLS they less dislike. Study findings clearly indicate that personality plays a significant role in a learner's satisfaction level. Consequently, personality traits should be considered when designing personalized learning activities. The current research seeks to bridge the theoretical gap in this specific research area. Establishing the assumption that different personalities need different learning solutions may contribute towards a better design of online courses, leaving no learner behind, whether he\ she likes online learning or not, since different personalities need different learning solutions.

Keywords: online learning, personality traits, personalization, techno-pedagogical learning solutions

Procedia PDF Downloads 97

Authors: Khadija Al-Hosni, Moon Fai Chan, Mohammed Al-Azri

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Background: Several studies suggest that most school-age adolescents are poorly informed on cancer warning signs and risk factors. Providing adolescents with sufficient knowledge would increase their awareness in adulthood and improve seeking behaviors later. Significant: The results will provide a clear vision in assisting key decision-makers in formulating policies on the students' awareness programs towards cancer. So, the likelihood of avoiding cancer in the future will be increased or even promote early diagnosis. Objectives: to evaluate the effectiveness of an education program designed to increase awareness of cancer signs and symptoms risk factors, improve the behavior of seeking help among school students in Oman, and address the barriers to obtaining medical help. Methods: A randomized controlled trial with two groups was conducted in Oman. A total of 1716 students (n=886/control, n= 830/education), aged 15-17 years, at 10th and 11th grade from 12 governmental schools 3 in governorates from 20-February-2022 to 12-May-2022. Basic demographic data were collected, and the Cancer Awareness Measure (CAM) was used as the primary outcome. Data were collected at baseline (T0) and 4 weeks after (T1). The intervention group received an education program about cancer's cause and its signs and symptoms. In contrast, the control group did not receive any education related to this issue during the study period. Non-parametric tests were used to compare the outcomes between groups. Results: At T0, the lamp was the most recognized cancer warning sign in the control (55.0%) and intervention (55.2%) groups. However, there were no significant changes at T1 for all signs in the control group. In contrast, all sign outcomes were improved significantly (p<0.001) in the intervention group, and the highest response was unexplained pain (93.3%). Smoking was the most recognized risk factor in both groups: (82.8% for control; 84.1% for intervention) at T0. However, there was no significant change in T1 for the control group, but there was for the intervention group (p<0.001), the highest identification was smoking cigarettes (96.5%). Too scared was the largest barrier to seeking medical help by students in the control group at T0 (63.0%) and T1 (62.8%). However, there were no significant changes in all barriers in this group. Otherwise, being too embarrassed (60.2%) was the largest barrier to seeking medical help for students in the intervention group at T0 and too scared (58.6%) at T1. Although there were reductions in all barriers, significant differences were found in six of ten only (p<0.001). Conclusion: The intervention was effective in improving students' awareness of cancer symptoms, warning signs (p<0.001), and risk factors (p<0.001 reduced the most addressed barriers to seeking medical help (p<0.001) in comparison to the control group. The Ministry of Education in Oman could integrate awareness of cancer within the curriculum, and more interventions are needed on the sociological part to overcome the barriers that interfere with seeking medical help.

Keywords: adolescents, awareness, cancer, education, intervention, student

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Authors: Prince Mugoya, Collins Oduor Ondiek, Patrick Kanyi Wamuyu

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Refugee Job Board Website is a web-based application that provides a platform for organizations to post jobs specifically for refugees. Organizations upload job opportunities and refugees can view them on the website. The website also allows refugees to input their skills and qualifications. The methodology used to develop this system is a waterfall (traditional) methodology. Software development tools include Brackets which will be used to code the website and PhpMyAdmin to store all the data in a database.

Keywords: information technology, refugee, skills, utilization, economy, jobs

Procedia PDF Downloads 157

Authors: Mingizem Gashaw Seid

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Phytoremediation of chromium metal by vetiver grass was investigated in hydroponic system. The removal efficiency for organic load, nutrient and chromium were evaluated as a function of concentration of waste effluent (40 and 50% dilution with distilled water). Under this conditions 64.49-94.06 % of chromium was removed. This shows vetiver grass has potential for accumulation of chromium metal from tannery waste water stream.

Keywords: chromium, phytoremediation, tannery effluent, vetiver grass

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Mohammad A. Alia, Abdelfatah Aref Tamimi, Omaima N. A. Al-Allaf

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This paper reviews a comparison study on the most common used authentication methods. Some of these methods are actually based on cryptography. In this study, we show the main cryptographic services. Also, this study presents a specific discussion about authentication service, since the authentication service is classified into several categorizes according to their methods. However, this study gives more about the real life example for each of the authentication methods. It talks about the simplest authentication methods as well about the available biometric authentication methods such as voice, iris, fingerprint, and face authentication.

Keywords: information security, cryptography, system access control, authentication, network security

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Authors: Vivek Thorat, Suhasini Desai

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The hybrid electric vehicle is widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and low emissions at competitive costs. Retro fitment of hybrid components into a conventional vehicle for achieving better performance is the best solution so far. But retro fitment includes major modifications into a conventional vehicle with a high cost. This paper focuses on the development of a P3x hybrid prototype with rear wheel drive parallel hybrid electric Light Commercial Vehicle (LCV) with minimum and low-cost modifications. This diesel Hybrid LCV is different from another hybrid with regard to the powertrain. The additional powertrain consists of continuous contact helical gear pair followed by chain and sprocket as a coupler for traction motor. Vehicle powertrain which is designed for the intended high-speed application. This work focuses on targeting of design, development, and packaging of this unique parallel diesel-electric vehicle which is based on multimode hybrid advantages. To demonstrate the practical applicability of this transmission with P3x hybrid configuration, one concept prototype vehicle has been build integrating the transmission. The hybrid system makes it easy to retrofit existing vehicle because the changes required into the vehicle chassis are a minimum. The additional system is designed for mainly five modes of operations which are engine only mode, electric-only mode, hybrid power mode, engine charging battery mode and regenerative braking mode. Its driving performance, fuel economy and emissions are measured and results are analyzed over a given drive cycle. Finally, the output results which are achieved by the first vehicle prototype during experimental testing is carried out on a chassis dynamometer using MIDC driving cycle. The results showed that the prototype hybrid vehicle is about 27% faster than the equivalent conventional vehicle. The fuel economy is increased by 20-25% approximately compared to the conventional powertrain.

Keywords: P3x configuration, LCV, hybrid electric vehicle, ROMAX, transmission

Procedia PDF Downloads 247

Authors: Tingyu Zhang

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The cross-basin ecological compensation mechanism is key to stimulating active participation in ecological protection across the entire basin. This study constructs an evolutionary game model of cross-basin ecological compensation in the Yangtze River Economic Belt (YREB), introducing a central government constraint and incentive mechanism (CGCIM) to explore the conditions for achieving strategies of protection and compensation that meet societal expectations. Furthermore, using a water quality-water quantity model combined with factual data from the YREB in 2020, the amount of ecological compensation is calculated. The results indicate that the stability of the evolutionary game model of the upstream and downstream governments in the YREB is closely related to the CGCIM. When the sum of the central government's reward amount to the upstream government and the penalty amount to both sides simultaneously is greater than 39.948 billion yuan, and the sum of the reward amount to the downstream government and the penalty amount to only the lower reaches is greater than 1.567 billion yuan, or when the sum of the reward amount to the downstream government and the penalty amount to both sides simultaneously is greater than 1.567 billion yuan, and the sum of the reward amount to the upstream government and the penalty amount to only the upstream government is greater than 399.48 billion yuan, the protection and compensation become the only evolutionarily stable strategy for the evolutionary game system composed of the upstream and downstream governments in the YREB. At this point, the total ecological compensation that the downstream government of the YREB should pay to the upstream government is 1.567 billion yuan, with Hunan paying 0.03 billion yuan, Hubei 2.53 billion yuan, Jiangxi 0.18 billion yuan, Anhui 1.68 billion yuan, Zhejiang 0.75 billion yuan, Jiangsu 6.57 billion yuan, and Shanghai 3.93 billion yuan. The research results can provide a reference for promoting the improvement and perfection of the cross-basin ecological compensation system in the YREB.

Keywords: ecological compensation, evolutionary game model, central government constraint and incentive mechanism, Yangtze river economic belt

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Authors: Mahshid Arabi

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In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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Authors: Adela Diepoltova, Klara Konecna, Ondrej Jandourek, Petr Nachtigal

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A loss of control over antibiotic-resistant pathogens has become a global issue due to severe and often untreatable infections. This state is reflected in complicated treatment, health costs, and higher mortality. All these factors emphasize the urgent need for the discovery and development of new anti-infectives. One of the most common pathogens mentioned in the phenomenon of antibiotic resistance are bacteria of the genus Staphylococcus. These bacterial agents have developed several mechanisms against the effect of antibiotics. One of them is biofilm formation. In staphylococci, biofilms are associated with infections such as endocarditis, osteomyelitis, catheter-related bloodstream infections, etc. To author's best knowledge, no validated and standardized methodology evaluating candidate compound activity against staphylococcal biofilms exists. However, a variety of protocols for in vitro drug activity testing has been suggested, yet there are often fundamental differences. Based on our experience, a key methodological step that leads to credible results is to form a robust biofilm with appropriate attributes such as firm adherence to the substrate, a complex arrangement in layers, and the presence of extracellular polysaccharide matrix. At first, for the purpose of drug antibiofilm activity evaluation, the focus was put on various conditions (supplementation of cultivation media by human plasma/fetal bovine serum, shaking mode, the density of initial inoculum) that should lead to reproducible and robust in vitro staphylococcal biofilm formation in microtiter plate model. Three model staphylococcal reference strains were included in the study: Staphylococcus aureus (ATCC 29213), methicillin-resistant Staphylococcus aureus (ATCC 43300), and Staphylococcus epidermidis (ATCC 35983). The total biofilm biomass was quantified using the Christensen method with crystal violet, and results obtained from at least three independent experiments were statistically processed. Attention was also paid to the viability of the biofilm-forming staphylococcal cells and the presence of extracellular polysaccharide matrix. The conditions that led to robust biofilm biomass formation with attributes for biofilms mentioned above were then applied by introducing an alternative method analogous to the commercially available test system, the Calgary Biofilm Device. In this test system, biofilms are formed on pegs that are incorporated into the lid of the microtiter plate. This system provides several advantages (in situ detection and quantification of biofilm microbial cells that have retained their viability after drug exposure). Based on our preliminary studies, it was found that the attention to the peg surface and substrate on which the bacterial biofilms are formed should also be paid to. Therefore, further steps leading to the optimization were introduced. The surface of pegs was coated by human plasma, fetal bovine serum, and L-polylysine. Subsequently, the willingness of bacteria to adhere and form biofilm was monitored. In conclusion, suitable conditions were revealed, leading to the formation of reproducible, robust staphylococcal biofilms in vitro for the microtiter model and the system analogous to the Calgary biofilm device, as well. The robustness and typical slime texture could be detected visually. Likewise, an analysis by confocal laser scanning microscopy revealed a complex three-dimensional arrangement of biofilm forming organisms surrounded by an extracellular polysaccharide matrix.

Keywords: anti-biofilm drug activity screening, in vitro biofilm formation, microtiter plate model, the Calgary biofilm device, staphylococcal infections, substrate modification, surface coating

Procedia PDF Downloads 150

Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

Procedia PDF Downloads 69