Search results for: electrochemical hydrogen storage

Authors: Margita Čanigová, Jana Račková, Miroslav Kročko, Viera Ducková, Vladimíra Kňazovická

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The aim of the study was to test the milk samples in terms of enterococci presence and their counts. Tested samples were as follows: raw cow milk, raw cow milk stored at 10°C for 16 hours and milk pasteurised at 72°C for 15 seconds. The typical colonies were isolated randomly and identified by classical biochemical test - EN-COCCUS test (Lachema, CR) and by PCR. Isolated strains were tested in terms of antibiotic resistance by well diffusion method. Examined antibiotics were: vancomycin (30 μg/disc), gentamicin (120 μg/disc), erythromycin (15 μg/disc), teicoplanine (30 μg/disc), ampicillin (10 μg/disc) and tetracycline (30 μg/disc). Average value of enterococci counts in raw milk cistern samples (n=30) was 8.25 ± 1.37 ×103 CFU/cm3. Storage tank milk samples (n=30) showed an increase (P > 0.05) and average value was 9.16 ± 1.49 × 103 CFU/cm3. Occurrence of enterococci in pasteurized milk (n=30) was sporadic and their counts were mostly below 10 CFU/cm3. Overall, 96 enterococci strains were isolated. In samples of raw cow milk and stored raw cow milk, Enterococcus faecalis was a dominant species (58.1% and 71.7%, respectively), followed by E. faecium (16.3% and 0%, respectively). Enterococcus mundtii, E. casseliflavus, E. durans and E. gallinarum were isolated, too. Resistances to ampicillin, erythromycin, gentamicin, tetracycline and vancomycin were found in 7.29%, 3.13%, 4.00%, 13.54% and 10.42% of isolated enterococci strains, respectively. Resistance to teicoplanine was not found in any isolated strain. All Vancomycin-Resistant Enterococci (VRE) belonged to E. faecalis. Obtained results confirmed that raw milk is a potential risk of enterococci resistant to antibiotics transmission into the food chain.

Keywords: antibiotic resistance, enterococci, milk, biosystems engineering

Procedia PDF Downloads 381

Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

Procedia PDF Downloads 138

Authors: Shubhangi Salokhe

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Agriculture encompasses crop and livestock production, forestry, and fisheries for food and non-food products. Farmers combine land, water, commercial inputs, labor, and their management skills into practices and systems that produce food and fibre. Harvesting of agricultural produce is either followed by the processing of fresh produce or storage for later consumption. All these activities result in a vast generation of waste in terms of crop residue or food waste. So, a large amount of agricultural waste is produced every year. Waste arising from food and agricultural sectors has the potential for vast applications. So, agricultural waste management is an essential component of sustainable agriculture. The major portion of the waste comes from the residues of crops on farms, food processing, livestock, aquaculture, and agro-industry waste. Therefore, management of these agricultural wastes is an important task, and it requires robust strategic planning. It can contribute to three pillars of sustainable agriculture development. It protects the environment (environmental pillar), enhances the livelihoods of farmers (economic pillar), and can contribute to increasing the sustainability of the agricultural sector (social pillar). This paper addresses the essential technological aspects, possible solutions, and sound policy concerns to accomplish long-term way out of agriculture waste management and to minimize the negative impact of waste on the environment. The author has developed a sustainable agriculture waste management model for improving the sustainability of agriculture.

Keywords: agriculture, development, management, waste

Procedia PDF Downloads 50

Authors: Evelyne Nguegwouo, Raoul Fonkem Sonfack Tsakem, Abel Wade, Gabriel Nama Medoua, Kamgaing Theophile

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Fresh and smoked fish are widely consumed in Cameroon. The traditional nature of smoking, the lack of hygiene in production, the poor preservation of stocks and the long storage time for certain types of fish considerably favor the contamination of products by molds, which secrete toxic molecules called mycotoxins. Today there are more than 400 types of mycotoxins, Aflatoxins being the most formidable. These toxins are considered carcinogenic in humans. It is in this perspective that we proposed to evaluate the total Aflatoxins in the fish marketed and consumed by the populations of the city of Yaoundé in Cameroon. On the one hand, it was a question of conducting a survey of fish consumers and sellers in points of sale, sampling fish of three species [Marquereau (Scomber scombrus), Cod (Gadus morhua) and Bifaka (Ethmalosa fimbriata)], randomly in some markets of the city to evaluate the total Aflatoxins contents (B1, B2, G1, G2) by the quantitative ELISA method and finally to estimate the level of exposure of the populations. It emerges from this study that of the 30 samples analyzed, 96.1% contained total Aflatoxins and two samples had total Aflatoxins levels above the standard, which is 20 ppb. These first results show that the risk is present in Cameroon and in order to improve the quality of marketed fish in terms of mycotoxins, a more thorough control must be done from the production chain to the consumer.

Keywords: aflatoxins, evaluation, exposure, mycotoxins, fish

Procedia PDF Downloads 79

Authors: Nishaben Desai Dholakiya, Anirban Roy, Ranjan Dey

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Understanding ocean thermodynamics has become increasingly critical as Earth's oceans serve as the primary planetary heat regulator, absorbing approximately 93% of excess heat energy from anthropogenic greenhouse gas emissions. This investigation presents a comprehensive analysis of Arabian Sea surface seawater thermodynamics, focusing specifically on heat capacity (Cp) and thermal expansion coefficient (α) - parameters fundamental to global heat distribution patterns. Through high-precision experimental measurements of ultrasonic velocity and density across varying temperature (293.15-318.15K) and salinity (0.5-35 ppt) conditions, it characterize critical thermophysical parameters including specific heat capacity, thermal expansion, and isobaric and isothermal compressibility coefficients in natural seawater systems. The study employs advanced machine learning frameworks - Random Forest, Gradient Booster, Stacked Ensemble Machine Learning (SEML), and AdaBoost - with SEML achieving exceptional accuracy (R² > 0.99) in heat capacity predictions. the findings reveal significant temperature-dependent molecular restructuring: enhanced thermal energy disrupts hydrogen-bonded networks and ion-water interactions, manifesting as decreased heat capacity with increasing temperature (negative ∂Cp/∂T). This mechanism creates a positive feedback loop where reduced heat absorption capacity potentially accelerates oceanic warming cycles. These quantitative insights into seawater thermodynamics provide crucial parametric inputs for climate models and evidence-based environmental policy formulation, particularly addressing the critical knowledge gap in thermal expansion behavior of seawater under varying temperature-salinity conditions.

Keywords: climate change, arabian sea, thermodynamics, machine learning

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Authors: Dennis L. Owuor, Okuthe P. Kogeda, Johnson I. Agbinya

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Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.

Keywords: indoor localization, digital forensics, fingerprinting, tracking and cloud

Procedia PDF Downloads 337

Authors: Poonam Singh, Surendra Prasad, William Aalbersberg

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Iron the most essential trace element in human nutrition. Its deficiency has serious health consequences and is a major public health threat worldwide. The common deficiencies in Fiji population reported are of Fe, Ca and Zn. It has also been reported that 40% of women in Fiji are iron deficient. Therefore, we have been studying the bioavailability of iron in commonly consumed Fiji foods. To study the bioavailability it is essential to assess the iron contents in raw foods. This paper reports the iron contents and its bioavailability in commonly consumed foods by multicultural population of Fiji. The food samples (rice, breads, wheat flour and breakfast cereals) were analyzed by atomic absorption spectrophotometer for total iron and its bioavailability. The white rice had the lowest total iron 0.10±0.03 mg/100g but had high bioavailability of 160.60±0.03%. The brown rice had 0.20±0.03 mg/100g total iron content but 85.00±0.03% bioavailable. The white and brown breads showed the highest iron bioavailability as 428.30±0.11 and 269.35 ±0.02%, respectively. The Weetabix and the rolled oats had the iron contents 2.89±0.27 and 1.24.±0.03 mg/100g with bioavailability of 14.19±0.04 and 12.10±0.03%, respectively. The most commonly consumed normal wheat flour had 0.65±0.00 mg/100g iron while the whole meal and the Roti flours had 2.35±0.20 and 0.62±0.17 mg/100g iron showing bioavailability of 55.38±0.05, 16.67±0.08 and 12.90±0.00%, respectively. The low bioavailability of iron in certain foods may be due to the presence of phytates/oxalates, processing/storage conditions, cooking method or interaction with other minerals present in the food samples.

Keywords: iron, bioavailability, Fiji foods, in vitro technique, human nutrition

Procedia PDF Downloads 529

Authors: Anamarel Medina-Hernandez, Teresa Ponce-Noyola, Ileana Vera-Reyes, Ana C. Ramos-Valdivia

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Somatic embryos reproduce original seed characteristics and could be implemented in biotechnological studies. Jatropha curcas L. is an important plant for biodiesel production, but also is used in traditional medicine. Seeds from J. curcas are toxic because contain diterpenoids called phorbol esters, but in Mexico exist a non-toxic variety. Therefore, somatic embryos suspension cultures from non-toxic J. curcas variety were induced. In order to investigate the characteristics of somatic embryos, a differential proteomic analysis was made between pre-globular and globular stages by 2-D gel electrophoresis. 108 spots were differentially expressed (p<0.02), and 20 spots from globular somatic embryos were sequenced by MALDI-TOF-TOF mass spectrometry. A comparative analysis of terpenoids production between the two stages was made by RP-18 TLC plates. The sequenced proteins were related to energy production (68%), protein destination and storage (9%), secondary metabolism (9%), signal transduction (5%), cell structure (5%) and aminoacid metabolism (4%). Regarding terpenoid production, in pre-globular and globular somatic embryos were identified sterols and triterpenes of pharmacological interest (alpha-amyrin and betulinic acid) but also it was found compounds that were unique to each stage. The results of this work are the basis to characterize at different levels the J. curcas somatic embryos so that this system can be used efficiently in biotechnological processes.

Keywords: Jatropha curcas, proteomics, somatic embryo, terpenoids

Procedia PDF Downloads 256

Authors: S. F. Halim, H. F. Naguib, S. N. Lawandy, R. S. Hegazy, M. N. Baheg

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The main drawbacks of the traditional carbon fabric reinforced epoxy resin (CFRP) are low strain failure, delamination between composites layers, and low impact resistance due to the brittleness of epoxy resin. The aim of this study is to enhance the fracture properties of the CFRP composites laminates via the variation of composite's designs. A series of composites were fabricated in which bidirectional (00/900) carbon fabric (CF) layers were laid inside the resin matrix with orientation codes as F1 [(00, 900)/ (00, 900)], F2 [(900, 00)/ (00, 900)] and F3 [(00,900)/ (900, 00). The mechanical and dynamic properties of the composites were estimated. In addition, the morphology of samples surface was examined by scanning electron microscope (SEM) after impact fracture. The results revealed that the CFRP properties could be tailored fitting specific applications by controlling the fabric orientation inside the CFRP composite design. F2 orientation [(900, 00)/ (00.900)] showed the highest tensile and flexural strength values. On the other hand, the impact strength values of composites were in the order F1 > F2 > F3. The storage modulus, loss modulus, and glass transition temperature Tg values obtained from the dynamic mechanical analysis (DMA) examination was in the order F1 > F2 > F3. The variation in the properties of the composite was clearly explained by the SEM micrographs as the failure of F3 orientation properties was referred to as the complete breakage of the CF layers upon fracture.

Keywords: carbon fiber, CFRP, composites, epoxy resins, flexural strength

Procedia PDF Downloads 128

Authors: Nivon P. Alejandra, Valencia P. L. Rodrigo, Vivanco V. Martin, Morita A. Adelina

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Technological innovation is fundamental to reach and maintain the levels of competitiveness of agricultural producers, the detection of actors, their activities, resources and capacities of an innovation system is needed for the development of technological packages that adapt to each type of crops, local circumstances and characteristics of the producer. The growing development of the viticulture and wine sector in Mexico prospects an increase in its national market participation for 2020, this is the reason to consider it a fertile field for the technological packages adoption that promote Precision Agriculture (PA) in a harmonic and sustainable development. A viability inspection of technological packages adoption by viticulture and wine sector is made following the methodology proposed by SAGARPA in 2015 and the World Bank in 2008: the history, actors, strengths and opportunities are analyzed in this particular agroindustrial sector, also its technological innovation system is inspected in order to improve technological capacities and innovation networks taking into account local and regional resources. PA and technological packages adoption can help improving the conditions and quality of the grape for winemaking: increasing the wine's storage potential and its nutraceutical nature. The assertive diagnosis in vineyard opportunity areas will help the management of the crop by applying natural treatments at the right time in the right place.

Keywords: technological packages, precision farming, sustainable development, innovation

Procedia PDF Downloads 199

Authors: Mosupi Ratshaa

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Despite years of diligent study, sedimentation is still undoubtedly the most severe technical problem faced by the dam industry. The problem of sedimentation build-up and its removal should be the focus as an approach to remedy this. The world's reservoirs lose about 1% of their storage capacity yearly to sedimentation, what this means is that 1% of water that could be stored is lost the world-over. The increase in population means that the need for water also increases and, therefore, the loss due to sedimentation is of great concern especially to the conservation of water. When it comes to reservoir sedimentation, the thought of water conservation comes with soil conservation since this increasing sediment that takes the volume meant for water is being lost from dry land. For this reason, reservoir sediment control is focused on reducing sediment entering the reservoir and reducing sediment within the reservoir. There are many problems with sediment control such as the difficulty to predict settling patterns, inability to greatly reduce the sediment volume entering the river flow which increases the reservoirs trap efficiency just to mention a few. Notably reservoirs are habitats for flora and fauna, the process of removing sediment from these reservoirs damages this ecosystem so there is an ethical point to be considered in this section. This paper looks at the methods used to control the sedimentation of reservoirs and their effects to the ecosystem in the aim of reducing water losses due to sedimentation. Various control measures which reduce sediment entering the reservoir such as Sabo dams or Check dams along with measures which emphasize the reduction in built-up settled sediment such as flushing will be reviewed all with the prospect of conservation.

Keywords: sedimentation, conservation, ecosystem, flushing

Procedia PDF Downloads 336

Authors: Moulay Driss Mellaoui, Khadija Zaki, Khalid Abbiche, Abdallah Imjjad, Rachid Boutiddar, Abdelouahid Sbai, Aaziz Jmiai, Souad El Issami, Al Mokhtar Lamsabhi, Hanane Zejli

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This study presents a comprehensive analysis of six isoxazolidine and isoxazoline derivatives, leveraging a multifaceted approach that combines Density Functional Theory (DFT), AdmetSAR analysis, and molecular docking simulations to explore their electronic, pharmacokinetic, and anticancer properties. Through DFT analysis, using the B3LYP-D3BJ functional and the 6-311++G(d,p) basis set, we optimized molecular geometries, analyzed vibrational frequencies, and mapped Molecular Electrostatic Potentials (MEP), identifying key sites for electrophilic attacks and hydrogen bonding. Frontier Molecular Orbital (FMO) analysis and Density of States (DOS) plots revealed varying stability levels among the compounds, with 1b, 2b, and 3b showing slightly higher stability. Chemical potential assessments indicated differences in binding affinities, suggesting stronger potential interactions for compounds 1b and 2b. AdmetSAR analysis predicted favorable human intestinal absorption (HIA) rates for all compounds, highlighting compound 3b superior oral effectiveness. Molecular docking and molecular dynamics simulations were conducted on isoxazolidine and 4-isoxazoline derivatives targeting the EGFR receptor (PDB: 1JU6). Molecular docking simulations confirmed the high affinity of these compounds towards the target protein 1JU6, particularly compound 3b, among the isoxazolidine derivatives, compound 3b exhibited the most favorable binding energy, with a g score of -8.50 kcal/mol. Molecular dynamics simulations over 100 nanoseconds demonstrated the stability and potential of compound 3b as a superior candidate for anticancer applications, further supported by structural analyses including RMSD, RMSF, Rg, and SASA values. This study underscores the promising role of compound 3b in anticancer treatments, providing a solid foundation for future drug development and optimization efforts.

Keywords: isoxazolines, DFT, molecular docking, molecular dynamic, ADMET, drugs.

Procedia PDF Downloads 47

Authors: A. T. Asutosh, J. Woo, M. Kouhirostami, M. Sam, A. Khantawang, C. Cuales, W. Ryor, C. Kibert

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Climate change and global warming vortex have grown to alarming proportions. Therefore, the need for a shift in the conceptualization of energy production is paramount. Energy practices have been created in the current situation. Fossil fuels continue their prominence, at the expense of renewable sources. Despite this abundance, a large percentage of the world population still has no access to electricity but there have been encouraging signs in global movement from nonrenewable to renewable energy but means to reverse climate change have been elusive. Worldwide, organizations have put tremendous effort into innovation. Conferences and exhibitions act as a platform that allows a broad exchange of information regarding trends in the renewable energy field. The Solar Power International (SPI) conference and exhibition is a gathering of concerned activists, and probably the largest convention of its kind. This study investigates current development in the renewable energy field, analyzing means by which industry is being applied to the issue. In reviewing the 2019 SPI conference, it was found innovations in recycling and assessing the environmental impacts of the solar products that need critical attention. There is a huge movement in the electrical storage but there exists a large gap in the development of security systems. This research will focus on solar energy, but impacts will be relevant to the entire renewable energy market.

Keywords: climate change, renewable energy, solar, trends, research, solar power international, SPI

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Authors: Rajat Raj, Rohini S. Hallikar

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The ever-increasing integration of renewable energy sources in the power grid necessitates the development of efficient and reliable microgrid systems. Photovoltaic (PV) systems coupled with energy storage technologies, such as batteries, offer promising solutions for sustainable and resilient power generation. This paper proposes an adaptive power control topology for a PV-battery microgrid system, aiming to optimize the utilization of available solar energy and enhance the overall system performance. In order to provide a smooth transition between the OFF-GRID and ON-GRID modes of operation with proportionate power sharing, a self-adaptive control method for a microgrid is proposed. Three different modes of operation are discussed in this paper, i.e., GRID connected, the transition between Grid-connected and Islanded State, and changing the irradiance of PVs and doing the transitioning. The simulation results show total harmonic distortion to be 0.08, 1.43 and 2.17 for distribution generation-1 and 4.22,3.92 and 2.10 for distribution generation-2 in the three modes, respectively which helps to maintain good power quality. The simulation results demonstrate the superiority of the adaptive power control topology in terms of maximizing renewable energy utilization, improving system stability and ensuring a seamless transition between grid-connected and islanded modes.

Keywords: islanded modes, microgrids, photo voltaic, total harmonic distortion

Procedia PDF Downloads 171

Authors: Vitalii Yu. Kapitan, Aleksandr V. Perzhu, Konstantin V. Nefedev

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The necessity of studying magnetic multilayer structures is explained by the prospects of their practical application as a technological base for creating new storages medium. Magnetic multilayer films have many unique features that contribute to increasing the density of information recording and the speed of storage devices. Multilayer structures are structures of alternating magnetic and nonmagnetic layers. In frame of the classical Heisenberg model, lattice spin systems with direct short- and long-range exchange interactions were investigated by Monte Carlo methods. The thermodynamic characteristics of multilayer structures, such as the temperature behavior of magnetization, energy, and heat capacity, were investigated. The processes of magnetization reversal of multilayer structures in external magnetic fields were investigated. The developed software is based on the new, promising programming language Rust. Rust is a new experimental programming language developed by Mozilla. The language is positioned as an alternative to C and C++. For the Monte Carlo simulation, the Metropolis algorithm and its parallel implementation using MPI and the Wang-Landau algorithm were used. We are planning to study of magnetic multilayer films with asymmetric Dzyaloshinskii–Moriya (DM) interaction, interfacing effects and skyrmions textures. This work was supported by the state task of the Ministry of Education and Science of the Russia # 3.7383.2017/8.9

Keywords: The Monte Carlo methods, Heisenberg model, multilayer structures, magnetic skyrmion

Procedia PDF Downloads 166

Authors: Farzad Doostishoar, Abbas Pardakhty, Abdolreza Hassanzadeh, Sudeh salarpour, Elham Sharif

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Background: Sericin is a protein extracted from silk and has antioxidant, antimicrobial, antineoplastic, wound healing and moisturizing properties. Different cosmetic formulation of sericin is available in different countries such as Japan and the other south-eastern Asian countries. We formulated and evaluated the sunscreen properties of topical formulations of sericin by an in vitro method. Method: Niosomes composed of sorbitan palmitate (Span 40), polysorbate 40 (Tween 40) and cholesterol (300 µmol, 3.5:3.5:3 molar ratio) were prepared by film hydration technique. Sericin was dissolved in normal saline and the lipid hydration was carried out at 60°C and the niosomes were incorporated in a Carbomer gel base. A W/O cream was also prepared and the release of sericin was evaluated by using Franz diffusion cell. Particle size analysis, sericin encapsulation efficiency measurement, morphological studies and stability evaluation were done in niosomal formulations. SPF was calculated by using Transpore tape in vitro method for both formulations. Results: Niosomes had high stability during 6 months storage at 4-8°C. The mean volume diameter of niosomes was less than 7 µm which is ideal for sustained release of drugs in topical formulations. The SPF of niosomal gel was 25 and higher than sericin cream with a diffusion based release pattern of active material. Conclusion: Sericin can be successfully entrapped in niosomes with sustained release pattern and relatively high SPF.

Keywords: sericin, niosomes, sun protection factor, cream, gel

Procedia PDF Downloads 500

Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

Procedia PDF Downloads 259

Authors: Gaurav Prabhudesai, Gaetan Brill

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The sun's energy source comes from a hydrogen-to-helium thermonuclear reaction, generating a temperature of about 5760 K on its outer layer. On account of this high temperature, energy is radiated by the sun, a part of which reaches the earth. This sunlight, even after losing part of its energy en-route to scattering and absorption, provides a time and space averaged solar flux of 174.7 W/m^2 striking the earth’s surface. According to one study, the solar energy striking earth’s surface in one and a half hour is more than the energy consumption that was recorded in the year 2001 from all sources combined. Thus, technology for extraction of solar energy holds much promise for solving energy crisis. Of the many technologies developed in this regard, Concentrating Solar Power (CSP) plants with central solar tower and receiver system are very impressive because of their capability to provide a renewable energy that can be stored in the form of heat. One design of central receiver towers is an open cavity where sunlight is concentrated into by using mirrors (also called heliostats). This concentrated solar flux produces high temperature inside the cavity which can be utilized in an energy conversion process. The amount of energy captured is reduced by losses occurring at the cavity through all three modes viz., radiation to the atmosphere, conduction to the adjoining structure and convection. This study investigates the natural convection losses to the environment from the receiver. Computational fluid dynamics were used to simulate the fluid flow and heat transfer of the receiver; since no analytical solution can be obtained and no empirical correlations exist for the given geometry. The results provide guide lines for predicting natural convection losses for hexagonal and circular shaped open cavities. Additionally, correlations are given for various inclination angles and aspect ratios. These results provide methods to minimize natural convection through careful design of receiver geometry and modification of the inclination angle, and aspect ratio of the cavity.

Keywords: concentrated solar power (CSP), central receivers, natural convection, CFD, open cavities

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Authors: Shahin A. Abdel-Naby, Asad T. Hassan

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Electron-ion recombination data are needed for plasma modeling. The recombination processes include radiative recombination (RR), dielectronic recombination (DR), and trielectronic recombination (TR). When a free electron is captured by an ion with simultaneous excitation of its core, a doubly-exited intermediate state may be formed. The doubly excited state relaxes either by electron emission (autoionization) or by radiative decay (photon emission). DR process takes place when the relaxation occurs to a bound state by photon emission. Reliable laboratory astrophysics data (theory and experiment) for DR rate coefficients are needed to determine the charge state distribution in photoionized sources such as X-ray binaries and active galactic nuclei. DR rate coefficients for NIII and OIV ions are calculated using state-of-the-art multi-configuration Breit-Pauli atomic structure AUTOSTRUCTURE collisional package within the generalized collisional-radiative framework. Level-resolved calculations for RR and DR rate coefficients from the ground and metastable initial states are produced in an intermediate coupling scheme associated with Δn = 0 (2→2) and Δn = 1 (2 →3) core-excitations. DR cross sections for these ions are convoluted with the experimental electron-cooler temperatures to produce DR rate coefficients. Good agreements are found between these rate coefficients and the experimental measurements performed at the CRYRING heavy-ion storage ring for both ions.

Keywords: atomic data, atomic process, electron-ion collision, plasmas

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Authors: Lucija Pustahija, Christine Bandl, Wolfgang Kern, Christian Mitterer

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Concerning today´s ecological demands, producing reliable materials from sustainable resources is a continuously developing topic. Such an example is the production of carbon materials via pyrolysis of natural gases or biomass. The amazing properties of pyrolytic carbon are utilized in various fields, where in particular the application in building industry is a promising way towards the utilization of pyrolytic carbon and composites based on pyrolytic carbon. For many applications, surface modification of carbon is an important step in tailoring its properties. Therefore, in this paper, an investigation of different oxidation methods was performed to prepare the carbon surface before functionalizing it with organosilanes, which act as coupling agents for epoxy and polyurethane resins. Made in such a way, a building material based on carbon composites could be used as a lightweight, durable material that can be applied where water or air filtration / purification is needed. In this work, both wet and dry oxidation were investigated. Wet oxidation was first performed in solutions of nitric acid (at 120 °C and 150 °C) followed by oxidation in hydrogen peroxide (80 °C) for 3 and 6 h. Moreover, a hydrothermal method (under oxygen gas) in autoclaves was investigated. Dry oxidation was performed under plasma and corona discharges, using different power values to elaborate optimum conditions. Selected samples were then (in preliminary experiments) subjected to a silanization of the surface with amino and glycidoxy organosilanes. The functionalized surfaces were examined by X-ray photon spectroscopy and Fourier transform infrared spectroscopy spectroscopy, and by scanning electron microscopy. The results of wet and dry oxidation methods indicated that the creation of functionalities was influenced by temperature, the concentration of the reagents (and gases) and the duration of the treatment. Sequential oxidation in aq. HNO₃ and H₂O₂ results in a higher content of oxygen functionalities at lower concentrations of oxidizing agents, when compared to oxidizing the carbon with concentrated nitric acid. Plasma oxidation results in non-permanent functionalization on the carbon surface, by which it´s necessary to find adequate parameters of oxidation treatments that could enable longer stability of functionalities. Results of the functionalization of the carbon surfaces with organosilanes will be presented as well.

Keywords: building materials, dry oxidation, organosilanes, pyrolytic carbon, resins, surface functionalization, wet oxidation

Procedia PDF Downloads 100

Authors: S. Hallal, Z. Chami, A. Hadji-Lehtihet, S. Sokhal-Boudella, A. Berhoune, L. Yargui

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Gaucher disease is the most common lysosomal storage in our population, it is due to a deficiency of β –glucosidase acid. The enzyme deficiency causes a pathological accumulation of undegraded substrate in lysosomes. This metabolic overload is responsible for a multisystemic disease with hepatosplenomegaly, anemia, thrombocytopenia, and bone involvement. Neurological involvement is rare. The laboratory diagnosis of Gaucher disease consists of phenotypic diagnosis by determining the enzymatic activity of β - glucosidase by fluorimetric method, a study by genotypic diagnosis in the GBA gene, limiting the search recurrent mutations (N370S, L444P, 84 GG); PCR followed by an enzymatic digestion. Abnormal profiles were verified by sequencing. Monitoring of treated patients is provided by the determination of chitotriosidase. Our experience spaning a period of 6 years (2007-2014) has enabled us to diagnose 78 patients out of a total of 328 requests from the various departments of pediatrics, internal medicine, neurology. Genotypic diagnosis focused on the entire family of 9 children treated at pediatric CHU Mustapha, which help define the clinical form; or 5 of them had type III disease, carrying the L444P mutation in the homozygous state. Three others were composite (N370/L444P) (N370S/other unintended mutation in our study), and only in one family no recurrent mutation has been found. This molecular study permits screening of heterozygous essential for genetic counseling.

Keywords: Gaucher disease, mutations, N370S, L444P

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Authors: Charuvan Kasemsap

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This research was studied in Bangnampriao District, Chachernsao Province, Thailand. The primary data relating to flooding, drought, and saline intrusion problem on agriculture were collected by surveying, focus group, and in-depth interview with agricultural officers, technical officers of irrigation department, and local government leader of Bangnampriao District. The likelihood and consequence of risk were determined the risk index by risk assessment matrix. In addition, the risk index and the total coping capacity scores were investigated the vulnerability index by vulnerability matrix. It was found that the high-risk drought and saline intrusion was dramatically along Bang Pakong River owing to the end destination of Chao Phraya Irrigation system of Central Thailand. This leads yearly the damage of rice paddy, mango tree, orchard, and fish pond. Therefore, some agriculture avoids rice growing during January to May, and also pumps fresh water from a canal into individual storage pond. However, Bangnampriao District will be strongly affected by the impacts of climate change. Monthly precipitations are expected to decrease in number; dry seasons are expected to be more in number and longer in duration. Thus, the risk and vulnerability of agriculture are also increasing. Adaptation strategies need to be put in place in order to enhance the resilience of the agriculture.

Keywords: agriculture, bangnampriao, climate change, risk assessment

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Authors: Jafar Ahmadi, Alireza Pour-Aboughadareh

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Wheat is the first and the most important grain of the world and its bakery property is due to glutenin and gliadin qualities. Wheat seed proteins were divided into four groups according to solubility. Two groups are albumin and globulin dissolving in water and salt solutions possessing metabolic activities. Two other groups are inactive and non-dissolvable and contain glutelins or glutenins and prolamins or gliadins. Gliadins are major components of the storage proteins in wheat endosperm. Gliadin proteins are separated into three groups based on electrophoretic mobility: α/β-gliadin, γ-gliadin, and ω-gliadin. It seems that little information is available about gliadin genes in Iranian wild relatives of wheat. Thus, the aim of this study was the evaluation of the wheat wild relatives collected from different origins of Zagros Mountains in Iran, involving coding gliadin genes using specific primers. For this, forty accessions of Triticum boeoticum and Triticum urartu were selected. For each accession, genomic DNA was extracted and PCRs were performed in total volumes of 15 μl. The amplification products were separated on 1.5% agarose gels. In results, for Gli-2A locus, three allelic variants were detected by Gli-2As primer pairs. The sizes of PCR products for these alleles were 210, 490 and 700 bp. Only five (13%) and two accessions (5%) produced 700 and 490 bp fragments when their DNA was amplified with the Gli.As.2 primer pairs. However, 37 of the 40 accessions (93%) carried 210 bp allele, and three accessions (8%) did not yield any product for this marker. Therefore, these germplasm could be used as rich gene pool to broaden the genetic base of bread wheat.

Keywords: diploied wheat, gliadin, Triticum boeoticum, Triticum urartu

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Authors: Niklas Panten, Eberhard Abele

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

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

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Authors: Madara Nikolajenko, Jevgenija Kondratjeva

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Stress is a response of the body to physical or psychological environmental stressors. Cortisol level in blood serum is determined as the main indicator of stress, but the blood collection, the animal preparation and other activities can cause unpleasant conditions and induce increase of these hormones. Therefore, less invasive methods are searched to determine stress hormone levels, for example, by measuring the cortisol level saliva. The aim of the study is to find out the changes of stress hormones in blood and saliva in home and experimental dogs in simulated short-term stress conditions. The study included clinically healthy experimental beagle dogs (n=6) and clinically healthy home American Staffordshire terriers (n=6). The animals were let into a fenced area to adapt. Loud drum sounds (in cooperation with 'Andžeja Grauda drum school') were used as a stressor. Blood serum samples were taken for sodium, potassium, glucose and cortisol level determination and saliva samples for cortisol determination only. Control parameters were taken immediately before the start of the stressor, and next samples were taken immediately after the stress. The last measurements were taken two hours after the stress. Electrolyte levels in blood serum were determined using direction selective electrode method (ILab Aries analyzer) and cortisol in blood serum and saliva using electrochemical luminescence method (Roche Diagnostics). Blood glucose level was measured with glucometer (ACCU-CHECK Active test strips). Cortisol level in the blood increased immediately after the stress in all home dogs (P < 0,05), but only in 33% (P < 0,05) of the experimental dogs. After two hours the measurement decreased in 83% (P < 0,05) of home dogs (in 50% returning to the control point) and in 83% (P < 0,05) of the experimental dogs. Cortisol in saliva immediately after the stress increased in 50% (P > 0,05) of home dogs and in 33% (P > 0,05) of the experimental dogs. After two hours in 83% (P > 0,05) of the home animals, the measurements decreased, only in 17% of the experimental dogs it decreased as well, while in 49% measurement was undetectable due to the lack of material. Blood sodium, potassium, and glucose measurements did not show any significant changes. The combination of short-term stress indicators, when, after the stressor, all indicators should immediately increase and decrease after two hours, confirmed in none of the animals. Therefore the authors can conclude that each animal responds to a stressful situation with different physiological mechanisms and hormonal activity. Cortisol level in saliva and blood is released with the different speed and is not an objective indicator of acute stress.

Keywords: animal behaivor, cortisol, short-term stress, stress indicators

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Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

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Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

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Authors: Rachna Jain, Sushila Madan, Bindu Garg

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Cloud computing is the key powerhouse in numerous organizations due to shifting of their data to the cloud environment. In recent years it has been observed that cloud-based-services are being used on large scale for content storage, distribution and processing. Various issues have been observed in cloud computing environment that need to be addressed. Security and privacy are found topmost concern area. In this paper, a novel security model is proposed to secure data by utilizing CDN services like image to icon conversion. CDN Service is a content delivery service which converts an image to icon, word to pdf & Latex to pdf etc. Presented model is used to convert an image into icon by keeping image secret. Here security of image is imparted so that image should be encrypted and decrypted by data owners only. It is also discussed in the paper that how server performs multiplication and selection on encrypted data without decryption. The data can be image file, word file, audio or video file. Moreover, the proposed model is capable enough to multiply images, encrypt them and send to a server application for conversion. Eventually, the prime objective is to encrypt an image and convert the encrypted image to image Icon by utilizing homomorphic encryption.

Keywords: cloud computing, user data security, homomorphic encryption, image multiplication, CDN service

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Rashid S. Mohammad, Shicheng Zhang, Sun Lu, Syed Jamal-Ud-Din, Xinzhe Zhao

Abstract:

A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO₂ injection process in unconventional tight reservoir. Cyclic CO₂ injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO₂ injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO₂ injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO₂ injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO₂ in the aquifer is one of the safest and permanent trapping techniques when considering CO₂ storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO₂ enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO₂ injection process while considering the effects of asphaltene deposition and solubility of CO₂ in the brine in order to prevent asphaltene precipitation, minimize CO₂ emission, optimize cyclic CO₂ injection, and maximize oil production.

Keywords: tight reservoirs, cyclic O₂ injection, asphaltene, solubility, reservoir simulation

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Authors: PR

Abstract:

Renewable energy is a sustainable substitute to fossil fuels, which are depleting and attributing to global warming as well as greenhouse gas emissions. Renewable energy innovations including solar, wind, and geothermal have grown significantly and play a critical role in meeting energy demands recently. Consequently, Artificial Intelligence (AI) could further enhance the benefits of renewable energy systems. The combination of renewable technologies and AI could facilitate the development of smart grids that can better manage energy distribution and storage. AI thus has the potential to optimize the efficiency and reliability of renewable energy systems, reduce costs, and improve their overall performance. The conventional methods of using smart micro-grids are to connect these micro-grids in series or parallel or a combination of series and parallel. Each of these methods has its advantages and disadvantages. In this study, the proposal of using the method of connecting microgrids in a spiral manner is investigated. One of the important reasons for choosing this type of structure is the two-way reinforcement and exchange of each inner layer with the outer and upstream layer. With this model, we have the ability to increase energy from a small amount to a significant amount based on exponential functions. The geometry used to close the smart microgrids is based on nature.This study provides an overview of the applications of algorithms and models of AI as well as its advantages and challenges in renewable energy systems.

Keywords: artificial intelligence, renewable energy sources, spiral model, optimize

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