Search results for: gradient generation

Authors: Delaram Hosseinioun

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In their collections, Shirin Neshat, Mitra Tabrizian, Gohar Dashti and Newsha Tavakolian adopt a hybrid form of narrative to confront the restrictions imposed on women in hegemonic public and private spaces. Focusing on motives such as social marginalisation, crisis of belonging, as well as lack of agency for women, the artists depict the regression of women’s rights in their respective generations. Based on the ideas of Michael Bakhtin, namely his concept of polyphony or the plurality of contradictory voices, the views of Judith Butler on giving an account to oneself and Henri Leverbre’s theories on social space, this study illustrates the artists’ concept of identity in crisis through time and space. The research explores how the artists took their art as a novel dimension to depict and confront the hardships imposed on Iranian women. Henri Lefebvre makes a distinction between complex social structures through which individuals situate, perceive and represent themselves. By adding Bakhtin’s polyphonic view to Lefebvre’s concepts of perceived and lived spaces, the study explores the sense of social fragmentation in the works of Dashti and Tavakolian. One argument is that as the representatives of the contemporary generation of female artists who spend their lives in Iran and faced a higher degree of restrictions, their hyperbolic and theatrical styles stand as a symbolic act of confrontation against restrictive socio-cultural norms imposed on women. Further, the research explores the possibility of reclaiming one's voice and sense of agency through art, corresponding with the Bakhtinian sense of polyphony and Butler’s concept of giving an account to oneself. Works of Neshat and Tabrizian as the representatives of the previous generation who faced exile and diaspora, encompass a higher degree of misplacement, violence and decay of women’s presence. In Their works, the women’s body encompasses Lefebvre’s dismantled temporal and special setting. Notably, the ongoing social conviction and gender-based dogma imposed on women frame some of the concurrent motives among the selected collections of the four artists. By applying an interdisciplinary lens and integrating the conducted interviews with the artists, the study illustrates how the artists seek a transcultural account for themselves and women in their generations. Further, the selected collections manifest the urgency for an authentic and liberal voice and setting for women, resonating with the concurrent Women, Life, Freedom movement in Iran.

Keywords: persian modern female photographers, transcultural studies, shirin neshat, mitra tabrizian, gohar dashti, newsha tavakolian, butler, bakhtin, lefebvre

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Authors: Ines Oliveira, Ana Reis

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Magnetic Pulse Welding (MPW) is a cold solid-state welding process, accomplished by the electromagnetically driven, high-speed and low-angle impact between two metallic surfaces. It has the same working principle of Explosive Welding (EXW), i.e. is based on the collision of two parts at high impact speed, in this case, propelled by electromagnetic force. Under proper conditions, i.e., flyer velocity and collision point angle, a permanent metallurgical bond can be achieved between widely dissimilar metals. MPW has been considered a promising alternative to the conventional welding processes and advantageous when compared to other impact processes. Nevertheless, MPW current applications are mostly academic. Despite the existing knowledge, the lack of consensus regarding several aspects of the process calls for further investigation. As a result, the mechanical resistance, morphology and structure of the weld interface in MPW of Al/Cu dissimilar pair were investigated. The effect of process parameters, namely gap, standoff distance and energy, were studied. It was shown that welding only takes place if the process parameters are within an optimal range. Additionally, the formation of intermetallic phases cannot be completely avoided in the weld of Al/Cu dissimilar pair by MPW. Depending on the process parameters, the intermetallic compounds can appear as continuous layer or small pockets. The thickness and the composition of the intermetallic layer depend on the processing parameters. Different intermetallic phases can be identified, meaning that different temperature-time regimes can occur during the process. It is also found that lower pulse energies are preferred. The relationship between energy increase and melting is possibly related to multiple sources of heating. Higher values of pulse energy are associated with higher induced currents in the part, meaning that more Joule heating will be generated. In addition, more energy means higher flyer velocity, the air existing in the gap between the parts to be welded is expelled, and this aerodynamic drag (fluid friction) is proportional to the square of the velocity, further contributing to the generation of heat. As the kinetic energy also increases with the square of velocity, the dissipation of this energy through plastic work and jet generation will also contribute to an increase in temperature. To reduce intermetallic phases, porosity, and melt pockets, pulse energy should be minimized. The bond formation is affected not only by the gap, standoff distance, and energy but also by the mandrel’s surface conditions. No correlation was clearly identified between surface roughness/scratch orientation and joint strength. Nevertheless, the aspect of the interface (thickness of the intermetallic layer, porosity, presence of macro/microcracks) is clearly affected by the surface topology. Welding was not established on oil contaminated surfaces, meaning that the jet action is not enough to completely clean the surface.

Keywords: bonding mechanisms, impact welding, intermetallic compounds, magnetic pulse welding, wave formation

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Authors: Yahia. Kourd, N. Guersi D. Lefebvre

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In this paper we propose to study the faults diagnosis in squirrel-cage induction motor using MLP neural networks. We use neural healthy and faulty models of the behavior in order to detect and isolate some faults in machine. In the first part of this work, we have created a neural model for the healthy state using Matlab and a motor located in LGEB by acquirins data inputs and outputs of this engine. Then we detected the faults in the machine by residual generation. These residuals are not sufficient to isolate the existing faults. For this reason, we proposed additive neural networks to represent the faulty behaviors. From the analysis of these residuals and the choice of a threshold we propose a method capable of performing the detection and diagnosis of some faults in asynchronous machines with squirrel cage rotor.

Keywords: faults diagnosis, neural networks, multi-models, squirrel-cage induction motor

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Authors: Yu-Jen Shih, Yao-Hui Hunag

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Electrocoagulation (EC) using metallic nickel foam as anode and cathode for the removal of boron from solution was studied. The electrolytic parameters included pH, current density, and initial boron concentration for optimizing the EC process. Experimental results showed that removal efficiency was increased by elevating pH from 4.0 to 8.0, and then decreased at higher pH. The electrolytic efficacy was not affected by current density. In respect of energy consumption, 1.25 mA/cm2 of current density was acceptable for an effective EC of boron, while increasing boric acid from 10 to 100 ppm-B did not impair removal efficiency too much. Cyclic voltammetry indicated that the oxide film, Ni(OH)2 and NiOOH, at specific overpotentials would result in less weight loss of anode than that predicted by the Faraday’s law. The optimal conditions under which 99.2% of boron was removed and less than 1 ppm-B remained in the electrolyte would be pH 8, four pairs of electrodes, and 1.25 mA/cm2 in 120 min as treating wastewaters containing 10 ppm-B. XRD and SEM characterization suggested that the granular crystallites of hydroxide precipitates was composed of theophrastite.

Keywords: borohydrides, hydrogen generation, NiOOH, electrocoagulation, cyclic voltammetry, boron removal

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Authors: Hyun Ji Hyun, Hyo Sun Suh, Min Kook Kim, Yong Chan Kwon, Byung-Mu Lee

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Scope: This study is focused on the effect of myristic acid on LPS-induced inflammation in RAW 264.7 macrophage cells. Methods and results: For the experiment, RAW 264.7 mouse macrophage cell line was used. Results showed that treatment with myristic acid can attenuate LPS-induced inflammation. Moreover, myristic acid significantly suppressed expression of inflammatory mediators and down-regulating UVB-induced intracellular ROS generation. Furthermore, myristic acid reduced the expression of NF-κB by inhibiting degradation of IκB-α and ERK, JNK, and p38 pathways by inhibiting phosphorylation in RAW 264.7 macrophage cells. Conclusion: Overall, these data suggest that the myristic acid could reduce LPS-induced inflammation. Acknowledgment: This research was supported by the Ministry of Trade, Industry & Energy(MOTIE), Korea Institute for Advancement of Technology(KIAT) through the Encouragement Program for The Industries of Economic Cooperation Region

Keywords: anti-inflammation, myristic acid, ROS, ultraviolet light

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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: Sourita Ghosh, Falguni Pati, Suhanya Duraiswamy

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Spheroid, a simple three-dimensional cellular aggregate, allows us to simulate the in-vivo complexity of cellular signaling and interactions in greater detail than traditional 2D cell culture. It can be used as an in-vitro model for drug toxicity testing, tumor modeling and many other such applications specifically for cancer. Our work is focused on the development of an affordable, user-friendly, robust, reproducible, high throughput microfluidic device for water in oil droplet production, which can, in turn, be used for spheroids manufacturing. Here, we have investigated the droplet breakup between two non-Newtonian fluids, viz. silicone oil and decellularized liver matrix, which acts as our extra cellular matrix (ECM) for spheroids formation. We performed some biochemical assays to characterize the liver ECM, as well as rheological studies on our two fluids and observed a critical dependence of capillary number (Ca) on droplet breakup and homogeneous drop formation

Keywords: chip less, droplets, extracellular matrix, liver spheroid

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Authors: Steven Sam, Ximena Schmidt, Hugh Dickinson, Jens Jensen

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The goal of this study is to explore the potential of data science and citizen science approaches to develop an interactive, digital, open infrastructure that pulls together African indigenous agriculture and food systems data from multiple sources, making it accessible and reusable for policy, research and practice in modern food production efforts. The World Bank has recognised that African Indigenous Knowledge (AIK) is innovative and unique among local and subsistent smallholder farmers, and it is central to sustainable food production and enhancing biodiversity and natural resources in many poor, rural societies. AIK refers to tacit knowledge held in different languages, cultures and skills passed down from generation to generation by word of mouth. AIK is a key driver of food production, preservation, and consumption for more than 80% of citizens in Africa, and can therefore assist modern efforts of reducing food insecurity and hunger. However, the documentation and dissemination of AIK remain a big challenge confronting librarians and other information professionals in Africa, and there is a risk of losing AIK owing to urban migration, modernisation, land grabbing, and the emergence of relatively small-scale commercial farming businesses. There is also a clear disconnect between the AIK and scientific knowledge and modern efforts for sustainable food production. The study combines data science and citizen science approaches through active community participation to generate and share AIK for facilitating learning and promoting knowledge that is relevant for policy intervention and sustainable food production through a curated digital platform based on FAIR principles. The study adopts key informant interviews along with participatory photo and video elicitation approach, where farmers are given digital devices (mobile phones) to record and document their every practice involving agriculture, food production, processing, and consumption by traditional means. Data collected are analysed using the UK Science and Technology Facilities Council’s proven methodology of citizen science (Zooniverse) and data science. Outcomes are presented in participatory stakeholder workshops, where the researchers outline plans for creating the platform and developing the knowledge sharing standard framework and copyrights agreement. Overall, the study shows that learning from AIK, by investigating what local communities know and have, can improve understanding of food production and consumption, in particular in times of stress or shocks affecting the food systems and communities. Thus, the platform can be useful for local populations, research, and policy-makers, and it could lead to transformative innovation in the food system, creating a fundamental shift in the way the North supports sustainable, modern food production efforts in Africa.

Keywords: Africa indigenous agriculture knowledge, citizen science, data science, sustainable food production, traditional food system

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Authors: Gabriela Rivadeneyra-Romero, Claudia del C. Gutierrez Torres, Sergio A. Martinez-Delgadillo, Victor X. Mendoza-Escamilla, Alejandro Alonzo-Garcia

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Ultrasonic degradation is currently being used in sonochemical reactors to degrade pollutant compounds from aqueous media, as emerging contaminants (e.g. pharmaceuticals, drugs and personal care products.) because they can produce possible ecological impacts on the environment. For this reason, it is important to develop appropriate water and wastewater treatments able to reduce pollution and increase reuse. Pollutants such as textile dyes, aromatic and phenolic compounds, cholorobenzene, bisphenol-A and carboxylic acid and other organic pollutants, can be removed from wastewaters by sonochemical oxidation. The effect on the removal of pollutants depends on the type of the ultrasonic frequency used; however, not much studies have been done related to the behavior of the fluid into the sonoreactors operated at different ultrasonic frequencies. Based on the above, it is necessary to study the hydrodynamic behavior of the liquid generated by the ultrasonic irradiation to design efficient sonoreactors to reduce treatment times and costs. In this work, it was studied the hydrodynamic behavior of the fluid in sonochemical reactors at different frequencies (250 kHz, 500 kHz and 1000 kHz). The performances of the sonoreactors at those frequencies were simulated using computational fluid dynamics (CFD). Due to there is great sound speed gradient between piezoelectric and fluid, k-e models were used. Piezoelectric was defined as a vibration surface, to evaluate the different frequencies effect on the fluid into sonochemical reactor. Structured hexahedral cells were used to mesh the computational liquid domain, and fine triangular cells were used to mesh the piezoelectric transducers. Unsteady state conditions were used in the solver. Estimation of the dissipation rate, flow field velocities, Reynolds stress and turbulent quantities were evaluated by CFD and 2D-PIV measurements. Test results show that there is no necessary correlation between an increase of the ultrasonic frequency and the pollutant degradation, moreover, the reactor geometry and power density are important factors that should be considered in the sonochemical reactor design.

Keywords: CFD, reactor, ultrasound, wastewater

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Authors: Bahram Fathi, Seyedhossein Sajadifar, Naser Khiabani

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Data envelopment analysis (DEA) has recently gained popularity in energy efficiency analysis. A common feature of the previously proposed DEA models for measuring energy efficiency performance is that they treat energy consumption as an input within a production framework without considering undesirable outputs. However, energy use results in the generation of undesirable outputs as byproducts of producing desirable outputs. Within a joint production framework of both desirable and undesirable outputs, this paper presents several DEA-type linear programming models for measuring energy efficiency performance. In addition to considering undesirable outputs, our models treat different energy sources as different inputs so that changes in energy mix could be accounted for in evaluating energy efficiency. The proposed models are applied to measure the energy efficiency performances of 12 OPEC countries and the results obtained are presented.

Keywords: energy efficiency, undesirable outputs, data envelopment analysis

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Authors: N. F. F. Ebecken, G. C. Pereira

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Ecological systems are exposed and are influenced by various natural and anthropogenic disturbances. They produce various effects and states seeking response symmetry to a state of global phase coherence or stability and balance of their food webs. This research project addresses the development of a computational methodology for modeling plankton food webs. The use of algorithms to establish connections, the generation of representative fuzzy multigraphs and application of technical analysis of complex networks provide a set of tools for defining, analyzing and evaluating community structure of coastal aquatic ecosystems, beyond the estimate of possible external impacts to the networks. Thus, this study aims to develop computational systems and data models to assess how these ecological networks are structurally and functionally organized, to analyze the types and degree of compartmentalization and synchronization between oscillatory and interconnected elements network and the influence of disturbances on the overall pattern of rhythmicity of the system.

Keywords: ecological networks, plankton food webs, fuzzy multigraphs, dynamic of networks

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Authors: Ayodele E. Ikudayisi, Yomi M. D. Adedeji, Olumuyiwa B. Adegun

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The level of adoption of green building (GB) schemes in Nigeria is low. The prevailing focus on economic development has overshadowed sustainability concerns. Despite these, few project cases exist in Nigeria in which sustainability goals have been achieved. This study aims to draw lessons from these in order to understand the project attributes, certification status, and the delivery process. Through an exploratory case study approach, fifteen project cases across five cities in Nigeria were examined. These represent the first-generation of green buildings in Nigeria, a verifiable reference for future initiatives in Sub-Saharan Africa. From the result, three categories of green buildings were identified, namely certified projects, demonstration projects, and potential projects with varying delivery attributes. Then, it is concluded by setting research and practice agenda towards aligning Nigeria’s building industry with the global trends in sustainable building delivery.

Keywords: LEED, green building, Nigeria, project attributes

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Authors: N. Tochukwu, M. Mukhopadhyay, A. Mohamed

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It is no new that Nigeria faces a continual power shortage problem due to its vast population power demand and heavy reliance on nonrenewable forms of energy such as thermal power or fossil fuel. Many researchers have recommended using geothermal energy as an alternative; however, Past studies focus on the geophysical & geochemical investigation of this energy in the sedimentary and basement complex; only a few studies incorporated the remote sensing methods. Therefore, in this study, the preliminary examination of geothermal resources in the Middle Benue was carried out using satellite imagery in ArcMap. Landsat 8 scene (TIR, NIR, Red spectral bands) was used to estimate the Land Surface Temperature (LST). The Maximum Likelihood Classification (MLC) technique was used to classify sites with very low, low, moderate, and high LST. The intermediate and high classification happens to be possible geothermal zones, and they occupy 49% of the study area (38077km2). Riverline were superimposed on the LST layer, and the identification tool was used to locate high temperate sites. Streams that overlap on the selected sites were regarded as geothermal springs as. Surprisingly, the LST results show lower temperatures (<36°C) at the famous thermal springs (Awe & Wukari) than some unknown rivers/streams found in Kwande (38°C), Ussa, (38°C), Gwer East (37°C), Yola Cross & Ogoja (36°C). Studies have revealed that temperature increases with depth. However, this result shows excellent geothermal resources potential as it is expected to exceed the minimum geothermal gradient of 25.47 with an increase in depth. Therefore, further investigation is required to estimate the depth of the causative body, geothermal gradients, and the sustainability of the reservoirs by geophysical and field exploration. This method has proven to be cost-effective in locating geothermal resources in the study area. Consequently, the same procedure is recommended to be applied in other regions of the Precambrian basement complex and the sedimentary basins in Nigeria to save a preliminary field survey cost.

Keywords: ArcMap, geothermal resources, Landsat 8, LST, thermal springs, MLC

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Authors: Ankita Gaur, Mouli Karmakar, Shyam

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In this study, a silicon solar cell has been modeled and analyzed to enhance its electrical performance by improving the optical properties using an antireflecting coating (ARC). The dynamic optical reflectance, transmittance along with the net transmissivity absorptivity product of each layer are assessed as per the diurnal variation of the angle of incidence using MATLAB 2019. The model is tested with various Anti-Reflective coatings and the performance has also been compared with uncoated cells. ARC improves the optical transmittance of the photon. Higher transmittance of ⁓96.57% with lowest reflectance of ⁓ 1.74% at 12.00 hours was obtained with MgF₂ coated silicon cells. The electrical efficiency of the configured solar cell was evaluated for a composite climate of New Delhi, India, for all weather conditions. The annual electricity generation for Anti-reflective coated and uncoated crystalline silicon PV Module was observed to be 103.14 KWh and 99.51 KWh, respectively.

Keywords: antireflecting coating, electrical efficiency, reflectance, solar cell, transmittance

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Shahriyar Keshtgar, Mahmoud Reza Heyhat, Sasan Bagheri, Ebrahim Gholami, Seyed Naser Raiisosadat

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The eastern Iranian range is a Z-shaped sigmoidal outcrop appearing with a NS-trending general strike on the satellite images, has already been known as the Sistan suture zone, recently identified as the product of an orogenic event introduced either by the Paleogene or Sistan orogen names. The flysch sedimentary basin of eastern Iran was filled by a huge volume of fine-grained Eocene turbiditic sediments, smaller amounts of pelagic deposits and Cretaceous ophiolitic slices, which are entirely remnants of older accretionary prisms appeared in a fold-thrust belt developed onto a subduction zone under the Lut/Afghan block, portions of the Cimmerian superterrane. In these ranges, there are Triassic sedimentary and carbonate sequences (equivalent to Nayband and Shotori Formations) along with scattered outcrops of Permian limestones (equivalent to Jamal limestone) and greenschist-facies metamorphic rocks, probably belonging to the basement of the Lut block, which have tectonic contacts with younger rocks. Moreover, the younger Eocene detrital-volcanic rocks were also thrusted onto the Cretaceous or younger turbiditic deposits. The first generation folds (parallel folds) and thrusts with slaty cleavage appeared parallel to the NE edge of the Lut block. Structural analysis shows that the most vergence of thrusts is toward the southeast so that the Permo-Triassic units in Lut have been thrusted on the younger rocks, including older (probably Jurassic) granites. Additional structural studies show that the regional transport direction in this deformation event is from northwest to the southeast where, from the outside to the inside of the orogen in the Sechengi area. Younger thrusts of the second deformation event were either directly formed as a result of the second deformation event, or they were older thrusts that reactivated and folded so that often, two sets or more slickenlines can be recognized on the thrust planes. The recent thrusts have been redistributed in directions nearly perpendicular to the edge of the Lut block and parallel to the axial surfaces of the northwest second generation large-scale folds (radial folds). Some of these younger thrusts follow the out-of-the-syncline thrust system. The both axial planes of these folds and associated penetrative shear cleavage extended towards northwest appeared with both northeast and southwest dips parallel to the younger thrusts. The large-scale buckling with the layer-parallel stress field has created this deformation event. Such consecutive deformation events perpendicular to each other cannot be basically explained by the simple linear orogen models presented for eastern Iran so far and are more consistent with the oroclinal buckling model.

Keywords: thrust, tectonic vergence, orocline buckling, sechangi, eastern iranian ranges

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Authors: Anésio de Leles Ferreira Filho, Wesley Rodrigues de Oliveira, Jéssica Santoro Gonçalves, Jorge Andrés Cormane Angarita

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The increase in electric power demand in face of environmental issues has intensified the participation of renewable energy sources such as photovoltaics, in the energy matrix of various countries. Due to their operational characteristics, they can generate time-varying harmonic and inter-harmonic distortions. For this reason, the application of methods of measurement based on traditional Fourier analysis, as proposed by IEC 61000-4-7, can provide inaccurate results. Considering the aspects mentioned herein, came the idea of the development of this work which aims to present the results of a comparative evaluation between a methodology arising from the combination of the Prony method with the Kalman filter and another method based on the IEC 61000-4-30 and IEC 61000-4-7 standards. Employed in this study were synthetic signals and data acquired through measurements in a 50kWp photovoltaic installation.

Keywords: harmonics, inter-harmonics, iec61000-4-7, parametric estimators, photovoltaic generation

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Authors: Imane Khalil, Quinn Pratt

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In a nuclear reactor, an array of fuel rods containing stacked uranium dioxide pellets clad with zircalloy is the heat source for a thermodynamic cycle of energy conversion from heat to electricity. After fuel is used in a nuclear reactor, the assemblies are stored underwater in a spent nuclear fuel pool at the nuclear power plant while heat generation and radioactive decay rates decrease before it is placed in packages for dry storage or transportation. A computational model of a Boiling Water Reactor spent fuel assembly is modeled using FLUENT, the computational fluid dynamics package. Heat transfer simulations were performed on the two-dimensional 9x9 spent fuel assembly to predict the maximum cladding temperature for different input to the FLUENT model. Uncertainty quantification is used to predict the heat transfer and the maximum temperature profile inside the assembly.

Keywords: spent nuclear fuel, conduction, heat transfer, uncertainty quantification

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Authors: D. Pugazhenthi, B. Sree Vidya

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Cloud computing is one of the emerging technologies that enables end users to use the services of cloud on ‘pay per usage’ strategy. This technology grows in a fast pace and so is its security threat. One among the various services provided by cloud is storage. In this service, security plays a vital factor for both authenticating legitimate users and protection of information. This paper brings in efficient ways of authenticating users as well as securing information on the cloud. Initial phase proposed in this paper deals with an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. Unique identification and slow intrusive formulates an advanced reliability on user-behaviour based biometrics than conventional means of password authentication. By biometric systems, the accounts are accessed only by a legitimate user and not by a nonentity. The biometric templates employed here do not include single trait but multiple, viz., iris and finger prints. The coordinating stage of the authentication system functions on Ensemble Support Vector Machine (SVM) and optimization by assembling weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained by the Artificial Fish Swarm Algorithm (AFSA). Thus it helps in generating a user-specific secure cryptographic key of the multimodal biometric template by fusion process. Data security problem is averted and enhanced security architecture is proposed using encryption and decryption system with double key cryptography based on Fuzzy Neural Network (FNN) for data storing and retrieval in cloud computing . The proposing scheme aims to protect the records from hackers by arresting the breaking of cipher text to original text. This improves the authentication performance that the proposed double cryptographic key scheme is capable of providing better user authentication and better security which distinguish between the genuine and fake users. Thus, there are three important modules in this proposed work such as 1) Feature extraction, 2) Multimodal biometric template generation and 3) Cryptographic key generation. The extraction of the feature and texture properties from the respective fingerprint and iris images has been done initially. Finally, with the help of fuzzy neural network and symmetric cryptography algorithm, the technique of double key encryption technique has been developed. As the proposed approach is based on neural networks, it has the advantage of not being decrypted by the hacker even though the data were hacked already. The results prove that authentication process is optimal and stored information is secured.

Keywords: artificial fish swarm algorithm (AFSA), biometric authentication, decryption, encryption, fingerprint, fusion, fuzzy neural network (FNN), iris, multi-modal, support vector machine classification

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Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

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The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

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Authors: Kwok Tak Kit

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Under the Paris Agreement 2015, the countries committed to address and combat the climate change and its negative impacts and agree to the target of reducing the global greenhouse gas (GHG) emission substantially by limiting the global temperature to 20C above the pre-industrial level in this century. A internationally Submit named “ 26th United Nations Climate Conference” (COP26) was held in Glasgow in 2021 with all committed countries agreed to the finalize the outstanding element in Paris Agreement and Glasgow Climate Pact to keep 1.50C. In this paper, we will focus on the basic approach of waste strategy, recycling policy, circular economy strategy, net-zero strategy and sustainability strategy and the importance of the elements which affect the carbon emission, waste generation and energy conservation will be further reviewed with recommendation for future study.

Keywords: net-zero carbon, climate change, carbon emission, energy consumption

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Authors: Boris G. German, Edward Jiménez, Sebastián Espinoza, Andrés G. Chico, Ricardo A. Narváez

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The unique flora and fauna of The Galapagos Islands has leveraged a tourism-driven growth in the islands. Nonetheless, such development is energy-intensive and requires thousands of gallons of diesel each year for thermoelectric electricity generation. The needed transport of fossil fuels from the continent has generated oil spillages and affectations to the fragile ecosystem of the islands. The Zero Fossil Fuels initiative for The Galapagos proposed by the Ecuadorian government as an alternative to reduce the use of fossil fuels in the islands, considers the replacement of diesel in thermoelectric generators, by Jatropha curcas vegetable oil. However, the Jatropha oil supply cannot entirely cover yet the demand for electricity generation in Galapagos. Within this context, the present work aims to provide an optimization model that can be used as a selection criterion for approving new Jatropha Curcas collection points in rural areas of Manabi-Ecuador. For this purpose, existing Jatropha collection points in Manabi were grouped under three regions: north (7 collection points), center (4 collection points) and south (9 collection points). Field work was carried out in every region in order to characterize the collection points, to establish local Jatropha supply and to determine transportation costs. Data collection was complemented using GIS software and an objective function was defined in order to determine the profit associated to Jatropha oil production. The market price of both Jatropha oil and residual cake, were considered for the total revenue; whereas Jatropha price, transportation and oil extraction costs were considered for the total cost. The tonnes of Jatropha fruit and seed, transported from collection points to the extraction plant, were considered as variables. The maximum and minimum amount of the collected Jatropha from each region constrained the optimization problem. The supply chain was optimized using linear programming in order to maximize the profits. Finally, a sensitivity analysis was performed in order to find a profit-based criterion for the acceptance of future collection points in Manabi. The maximum profit reached a value of $ 4,616.93 per year, which represented a total Jatropha collection of 62.3 tonnes Jatropha per year. The northern region of Manabi had the biggest collection share (69%), followed by the southern region (17%). The criteria for accepting new Jatropha collection points in the rural areas of Manabi can be defined by the current maximum profit of the zone and by the variation in the profit when collection points are removed one at a time. The definition of new feasible collection points plays a key role in the supply chain associated to Jatropha oil production. Therefore, a mathematical model that assists decision makers in establishing new collection points while assuring profitability, contributes to guarantee a continued Jatropha oil supply for Galapagos and a sustained economic growth in the rural areas of Ecuador.

Keywords: collection points, Jatropha curcas, linear programming, supply chain

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Authors: Brenda Cecilia Ledesma, Andrea Beltramone

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This work deals with the bio-waste valorization approach for catalyst development, the use of products derived from biomass as raw material and the obtaining of biofuels. In this research, activated carbons were synthesized from the orange peel using different synthesis conditions. With the activated carbons obtained with the best structure and texture, PtIr bimetallic catalysts were prepared. Carbon activation was carried out through a chemical process with phosphoric acid as an activating agent, varying the acid concentration, the ratio substrate/activating agent and time of contact between them. The best support was obtained using a carbonization time of 1 h, the temperature of carbonization of 470oC, the phosphoric acid concentration of 50 wt.% and a BET area of 1429 m2/g. Subsequently, the metallic nanoparticles were deposited in the activated carbon to use the solid as a catalytic material for the hydrogenation of HMF to 2,5-DMF. The catalyst presented an excellent performance for biofuels generation.

Keywords: orange peel, bio-waste valorization, platinum, iridium, 5-hydroxymethylfurfural

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Authors: P. V. Leksin, A. A. Kamashev, N. N. Garifyanov, I. A. Garifullin, Ya. V. Fominov, J. Schumann, Y. Krupskaya, V. Kataev, O. G. Schmidt, B. Büchner

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We report on experimental evidence for the occurrence of the long range triplet correlations (LRTC) of the superconducting (SC) condensate in the spin-valve heterostructures CoOx/Fe1/Cu/Fe2/Pb. The LRTC generation in this layer sequence is accompanied by a Tc suppression near the orthogonal mutual orientation of the Fe1 and Fe2 layers’ magnetization. This Tc drop reaches its maximum of 60mK at the Fe2 layer thickness dFe2 = 0.6 nm and falls down when dFe2 is increased. The modification of the Fe/Pb interface by using a thin Cu intermediate layer between Fe and Pb layers reduces the SC transition width without preventing the interaction between Pb and Fe2 layers. The dependence of the SSVE magnitude on Fe1 layer thickness dFe1 reveals maximum of the effect when dFe1 and dFe2 are equal and the dFe2 value is minimal. Using the optimal Fe layers thicknesses and the intermediate Cu layer between Pb and Fe2 layer we realized almost full switching from normal to superconducting state due to SSVE.

Keywords: superconductivity, ferromagnetism, heterostructures, proximity effect

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Authors: Krishnan Manickavasagam, Manikandan Shanmugam

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Clean and abundant renewable energy sources (RES) such as solar energy is seen as the best solution to replace conventional energy source. Unpredictable power generation is a major issue in the penetration of solar energy, as power generated is governed by the irradiance received. Controlling the power generated from solar PV (SPV) panels to battery and load is a challenging task. In this paper, power flow control from SPV to load and energy storage device (ESD) is controlled by a fuzzy decision support system (FDSS) on the availability of solar irradiation. The results show that FDSS implemented with the energy management system (EMS) is capable of managing power within the area, and if excess power is available, then shared with the neighboring area.

Keywords: renewable energy sources, fuzzy decision support system, solar photovoltaic, energy storage device, energy management system

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Authors: Joanna Drzeżdżon

Abstract:

Polyvinyl alcohol and its derivatives such as 2-chloro-2-propen-1-ol have found application in many industries. They are mainly used for the production of adhesives, thickeners and stabilizers of emulsion paints, and surgical threads. Moreover, polyvinyl alcohol derivatives are indispensable reagents in the synthesis of hemiacetals. Polyolefins derived from polyvinyl alcohol are obtained by using catalysts belonging to complex compounds of transition metal ions. The aim of the studies is to the synthesis of a new complex, i.e. dipicolinate oxovanadium(IV) complex with 4,4’-dimethoxy-2,2’-bipyridyl, and to determine its catalytic activities. Moreover, the another aim of the studies was to set conditions for 2-chloro-2-propen-1-ol oligomerization. The catalytic system has been based on the dipicolinate complex of oxovanadium(IV) with 4,4’-dimethoxy-2,2’-bipyridyl and MMAO-12. The results of the studies showed that how a new oxovanadium(IV) complex compound effects on the 2-chloro-2-propen-1-ol oligomerization. Moreover, the results revealed that new catalytic material is a highly active catalyst for the investigated oligomerization.

Keywords: 2-chloro-2-propen-1-ol, oligomerization, dipicolinate, vanadium, methylaluminoxane

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Authors: Kausar Harun, Ahmad Azmin Mohamad

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Zinc oxide (ZnO) has been extensively used in optoelectronic devices, with recent interest as photoanode material in dye-sensitize solar cell. Numerous methods employed to experimentally synthesized ZnO, while some are theoretically-modeled. Both approaches provide information on ZnO properties, but theoretical calculation proved to be more accurate and timely effective. Thus, integration between these two methods is essential to intimately resemble the properties of synthesized ZnO. In this study, experimentally-grown ZnO nanoparticles were prepared by sol-gel storage method with zinc acetate dihydrate and methanol as precursor and solvent. A 1 M sodium hydroxide (NaOH) solution was used as stabilizer. The optimum time to produce ZnO nanoparticles were recorded as 12 hours. Phase and structural analysis showed that single phase ZnO produced with wurtzite hexagonal structure. Further work on quantitative analysis was done via Rietveld-refinement method to obtain structural and crystallite parameter such as lattice dimensions, space group, and atomic coordination. The lattice dimensions were a=b=3.2498Å and c=5.2068Å which were later used as main input in first-principles calculations. By applying density-functional theory (DFT) embedded in CASTEP computer code, the structure of synthesized ZnO was built and optimized using several exchange-correlation functionals. The generalized-gradient approximation functional with Perdew-Burke-Ernzerhof and Hubbard U corrections (GGA-PBE+U) showed the structure with lowest energy and lattice deviations. In this study, emphasize also given to the modification of valence electron energy level to overcome the underestimation in DFT calculation. Both Zn and O valance energy were fixed at Ud=8.3 eV and Up=7.3 eV, respectively. Hence, the following electronic and optical properties of synthesized ZnO were calculated based on GGA-PBE+U functional within ultrasoft-pseudopotential method. In conclusion, the incorporation of Rietveld analysis into first-principles calculation was valid as the resulting properties were comparable with those reported in literature. The time taken to evaluate certain properties via physical testing was then eliminated as the simulation could be done through computational method.

Keywords: density functional theory, first-principles, Rietveld-refinement, ZnO nanoparticles

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Authors: Robert Setekera, Ramses van der Toorn

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We present an extensive analysis of the temperature dependence of the local avalanche model used in most of the modern compact models for bipolar transistors. This local avalanche model uses the Chynoweth's empirical law for ionization coefficient to define the generation of the avalanche current in terms of the local electric field. We carry out the model analysis using DC-measurements taken on both Si and advanced SiGe bipolar transistors. For the advanced industrial SiGe-HBTs, we consider both high-speed and high-power devices (both NPN and PNP transistors). The limitations of the local avalanche model in modeling the temperature dependence of the avalanche current mostly in the weak avalanche region are demonstrated. In addition, the model avalanche parameters are analyzed to see if they are in agreement with semiconductor device physics.

Keywords: avalanche multiplication, avalanche current, bipolar transistors, compact modeling, electric field, impact ionization, local avalanche

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Authors: Eiji Nakamachi, Ryota Sakiyama, Koji Yamamoto, Yusuke Morita, Hidetoshi Sakamoto

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The regeneration of injured central nerve network caused by the cerebrovascular accidents is difficult, because of poor regeneration capability of central nerve system composed of the brain and the spinal cord. Recently, new regeneration methods such as transplant of nerve cells and supply of nerve nutritional factor were proposed and examined. However, there still remain many problems with the canceration of engrafted cells and so on and it is strongly required to establish an efficacious treating method of a central nerve system. Blackman proposed the electromagnetic stimulation method to enhance the axonal nerve extension. In this study, we try to design and fabricate a new three-dimensional (3D) bio-reactor, which can load a uniform AC magnetic field stimulation on PC12 cells in the extracellular environment for enhancement of an axonal nerve extension and 3D nerve network generation. Simultaneously, we measure the morphology of PC12 cell bodies, axons, and dendrites by the multiphoton excitation fluorescence microscope (MPM) and evaluate the effectiveness of the uniform AC magnetic stimulation to enhance the axonal nerve extension. Firstly, we designed and fabricated the uniform AC magnetic field stimulation bio-reactor. For the AC magnetic stimulation system, we used the laminated silicon steel sheets for a yoke structure of 3D chamber, which had a high magnetic permeability. Next, we adopted the pole piece structure and installed similar specification coils on both sides of the yoke. We searched an optimum pole piece structure using the magnetic field finite element (FE) analyses and the response surface methodology. We confirmed that the optimum 3D chamber structure showed a uniform magnetic flux density in the PC12 cell culture area by using FE analysis. Then, we fabricated the uniform AC magnetic field stimulation bio-reactor by adopting analytically determined specifications, such as the size of chamber and electromagnetic conditions. We confirmed that measurement results of magnetic field in the chamber showed a good agreement with FE results. Secondly, we fabricated a dish, which set inside the uniform AC magnetic field stimulation of bio-reactor. PC12 cells were disseminated with collagen gel and could be 3D cultured in the dish. The collagen gel were poured in the dish. The collagen gel, which had a disk shape of 6 mm diameter and 3mm height, was set on the membrane filter, which was located at 4 mm height from the bottom of dish. The disk was full filled with the culture medium inside the dish. Finally, we evaluated the effectiveness of the uniform AC magnetic field stimulation to enhance the nurve axonal extension. We confirmed that a 6.8 increase in the average axonal extension length of PC12 under the uniform AC magnetic field stimulation at 7 days culture in our bio-reactor, and a 24.7 increase in the maximum axonal extension length. Further, we confirmed that a 60 increase in the number of dendrites of PC12 under the uniform AC magnetic field stimulation. Finally, we confirm the availability of our uniform AC magnetic stimulation bio-reactor for the nerve axonal extension and the nerve network generation.

Keywords: nerve regeneration, axonal extension , PC12 cell, magnetic field, three-dimensional bio-reactor

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

Procedia PDF Downloads 329