Search results for: net present cost (NPC)

Authors: Amira Ben Rabeh, Faouzi Benzarti, Hamid Amiri, Mouna Bouaziz

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Alzheimer is a disease that affects the brain. It causes degeneration of nerve cells (neurons) and in particular cells involved in memory and intellectual functions. Early diagnosis of Alzheimer Diseases (AD) raises ethical questions, since there is, at present, no cure to offer to patients and medicines from therapeutic trials appear to slow the progression of the disease as moderate, accompanying side effects sometimes severe. In this context, analysis of medical images became, for clinical applications, an essential tool because it provides effective assistance both at diagnosis therapeutic follow-up. Computer Assisted Diagnostic systems (CAD) is one of the possible solutions to efficiently manage these images. In our work; we proposed an application to detect Alzheimer’s diseases. For detecting the disease in early stage we used the three sections: frontal to extract the Hippocampus (H), Sagittal to analysis the Corpus Callosum (CC) and axial to work with the variation features of the Cortex(C). Our method of classification is based on Support Vector Machine (SVM). The proposed system yields a 90.66% accuracy in the early diagnosis of the AD.

Keywords: Alzheimer Diseases (AD), Computer Assisted Diagnostic(CAD), hippocampus, Corpus Callosum (CC), cortex, Support Vector Machine (SVM)

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Authors: Chatkaew Tansakul, Saovajit Nanruksa, Surasak Chonchirdsin

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Heavy metals in the environment can be occurred by both natural weathering process and human activity, which may present significant risks to human health and the wider environment. A number of heavy metals, i.e. Arsenic (As) and Manganese (Mn), are found with a relatively high concentration in the northern part of Thailand that was assumptively from natural parent rocks and materials. However, scarce literature is challenging to identify the accurate root cause and best available explanation. This study is, therefore, aim to gather heavy metals data in 5 provinces of the North of Thailand where PTT Exploration and Production (PTTEP) public company limited has operated for more than 20 years. A thousand heavy metal analysis is collected and interpreted in term of Enrichment Factor (EF). The trend and distribution of heavy metals in soil and sediment are analyzed by considering altogether the geochemistry of the regional soil and rock. . In addition, the relationship between land use and heavy metals distribution is investigated. In the first conclusion, heavy metal concentrations of (As) and (Mn) in the studied areas are equal to 7.0 and 588.6 ppm, respectively, which are comparable to those in regional parent materials (1 – 12 and 850 – 1,000 ppm for As and Mn respectively). Moreover, there is an insignificant escalation of the heavy metals in these studied areas over two decades.

Keywords: contaminated soil, enrichment factor, heavy metals, parent materials in North of Thailand

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Authors: Paul Essel, Eric T. Glover, Gustav Gbeddy, Yaw Adjei-Kyereme, Abdallah M. A. Dawood, Evans M. Ameho, Emmanuel A. Aberikae

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Radioactive materials mainly in the form of Sealed Radioactive Sources are being used in various sectors (medicine, agriculture, industry, research, and teaching) for the socio-economic development of Ghana. The use of these beneficial radioactive materials has resulted in an inventory of Disused Sealed Radioactive Sources (DSRS) in storage. Most of the DSRS are legacy/historic sources which cannot be returned to their manufacturer or country of origin. Though small in volume, DSRS can be intensively radioactive and create a significant safety and security liability. They need to be managed in a safe and secure manner in accordance with the fundamental safety objective. The Radioactive Waste Management Center (RWMC) of the Ghana Atomic Energy Commission (GAEC) is currently storing a significant volume of DSRS. The initial activities of the DSRS range from 7.4E+5 Bq to 6.85E+14 Bq. If not managed properly, such DSRS can represent a potential hazard to human health and the environment. Storage is an important interim step, especially for DSRS containing very short-lived radionuclides, which can decay to exemption levels within a few years. Long-term storage, however, is considered an unsustainable option for DSRS with long half-lives hence the need for a disposal facility. The GAEC intends to use the International Atomic Energy Agency’s (IAEA’s) Borehole Disposal System (BDS) to provide a safe, secure, and cost-effective disposal option to dispose of its DSRS in storage. The proposed site for implementation of the BDS is on the GAEC premises at Kwabenya. The site has been characterized to gain a general understanding in terms of its regional setting, its past evolution and likely future natural evolution over the assessment time frame. Due to the long half-lives of some of the radionuclides to be disposed of (Ra-226 with half-life of 1600 years), the engineered barriers of the system must be robust to contain these radionuclides for this long period before they decay to harmless levels. There is the need to assess the safety related functions of the engineered barriers of this disposal system.

Keywords: radionuclides, disposal, radioactive waste, engineered barrier

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Authors: Shepherd Manhokwe, Sheron Shoko, Cuthbert Zvidzai

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In the present study, the interactive effects of temperature and cultured bacteria on the performance of a biological treatment system of yeast processing wastewater were investigated. The main objective of this study was to investigate and optimize the operating parameters that reduce organic load and colour. Experiments were conducted based on a Central Composite Design (CCD) and analysed using Response Surface Methodology (RSM). Three dependent parameters were either directly measured or calculated as response. These parameters were total Chemical Oxygen Demand (COD) removal, colour reduction and total solids. COD removal efficiency of 26 % and decolourization efficiency of 44 % were recorded for the wastewater treatment. The optimized conditions for the biological treatment were found to be at 20 g/l cultured bacteria and 25 °C for COD reduction. For colour reduction optimum conditions were temperature of 30.35°C and bacterial formulation of 20g/l. Biological treatment of baker’s yeast processing effluent is a suitable process for the removal of organic load and colour from wastewater, especially when the operating parameters are optimized.

Keywords: COD reduction, optimisation, response surface methodology, yeast processing wastewater

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Authors: Jana Tchekalarova, Stela Georgieva, Petia Peneva, Petar Todorov

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In the present study, a series of bioconjugates of N-modified hemorphine analogs containing second pharmacophore cinnamic acids (CA) or caffeic acid (KA) were synthesized by a traditional solid-phase Fmoc chemistry method for peptide synthesis. Electrochemical and fluorometric analysis and in vivo anticonvulsant activity in mice were conducted on the compounds. The three CA (H4-CA, H5-CA, and H7-CA) and three KA (H4-KA, H5-KA, and H7-KA)-conjugated hemorphine derivatives showed dose-dependent anticonvulsant activity in the maximal electroshock test (MES) in mice. The KA-conjugated H5-KA derivate was the only compound that suppressed clonic seizures at the lowest dose of 0.5 µg/mouse in the scPTZ test. The activity against the psychomotor seizures in the 6-Hz test was detected only for the H4-CA (0.5 µg) and H4-KA (0.5 µg and 1 µg), respectively. The peptide derivates did not exhibit neurotoxicity in the rotarod test. Our findings suggest that conjugated CA and KA hemorphine peptides can be used as a background for developing hemorphin-related analogs with anticonvulsant activity. Acknowledgments: This study is funded by the European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria, project № BG-RRP-2.004-0002, "BiOrgaMCT".

Keywords: hemorphins, SPSS, caffeic/cinnamic acid, anticonvulsant activity, electrochemistry, fluorimetry

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Authors: Sabrina Boutaleb, Kouider Halim Benrahou, François Schosseler, Abdelouahed Tounsi, El Abbas Adda Bedia

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The use of polyurethane in different areas becomes more frequent. This is due to significant advantages they have including their lightness and resistance. However, their use requires a mastery of their mechanical performance. We will present in this work, a COAPUR 6050 which can be used to develop composite materials. COAPUR 6050 is an associative polyurethane thickener allowing fine rheological adjustment of flat or semi-gloss paints. COAPUR 6050 is characterised by its thickening efficiency at low shear rate. It is a solvent-free liquid product. It promotes good paint pick up, while maintaining a low yield point after shearing, and consequently a good levelling. We will then determine its rheological behaviour experimentally using different annular gaps. The rheological properties of COAPUR 6050 were researched by rotational rheometer (Rheometer-Mars III) using different annular gaps. There is the influence of the size of the annular gap on the behaviour as well as on the rheological parameters of the COAPUR 6050. The rheological properties data of COAPUR 6050 were regressed by nonlinear regression method and their rheological models were established, are characterized by yield pseudoplastic model. In this case, it is essential to make a viscometric correction. The latter was developed and presented in the experimental results.

Keywords: COAPUR 6050, flow’s couette, polyurethane, rheological behaviours

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Authors: Rinaldo Diricchardi

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In this paper, author theoretically and empirically explores the ethnic identity of the descendants of the Indian travelers in Slovenia Sinti, who are in modern time, for the researchers, still a "tabula rasa". He investigates the extent to which Sinti ethnic particular identities (e.g. Sinti chiefs, Sinti’s individual political structure…), the Sinti language (dialect, which is topic and it is not allowed to be spoken in public), culture and habits still in the impact of anachronism, moreover, to what extent the community is still “tabula rasa” (to non–Sinti population). The relationships within the Sinti entity: "in se–intra se" is a mirror of duality of the relation of "extra se". Is it possible that the concepts of social/economical relationships are reflecting the Sinti community, moreover, the possible influence of minority from outside to inside? Is the stratification of their ethnicity and their language ethnicism? In addition, is the result of stratification of discourse still inherited and discounted the Indian caste system? In present article, author uses the word Gypsy with high respect and with a large measure of prudentiality, without negative connotations. At the first Gypsy World Congress in 1971 in London the Sinti did not accept unification with Romani, but Sinti and others Gypsies still keep the name Gypsy/Romanichals, Gypsy/Kale, Gypsy/Manouches, Gypsy/Manoesje, Gypsy/Xoraxano, Gypsy/Machaways and Gypsy/Kalderashe. In addition, all of the European documents taken into account respect and use the name Gypsy.

Keywords: Sinti, Gypsy, identity, stratification, inclusion, exclusion

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Authors: Saeid Motevalli, Siti Fatimah Azzahrah Binti Abd Mutalib, Mohd Sahandri Ghani Hamzah, Hazalizah Hamzah

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The main purpose of the present study was to investigate the relationship between body esteem and self-esteem with sport-confidence among university students. This study was conducted by using the descriptive and correlational study design. Meanwhile, the method involved in this study was the online survey method. The population of the sample are mainly Universiti Pendidikan Sultan Idris (UPSI) students only which 120 participants were selected by cluster sampling method from two faculties named Fakulti Pembangunan Manusia (FPM) and Fakulti Sains Sukan dan Kejurulatihan (FSSKJ). The instrument used in this study was The Body-Esteem Scale (BES) by Franzoi and Shields (1984), Rosenberg Self-Esteem Scale (RSES) by Rosenberg (1965) and the Vealey’s Trait Sport-Confidence Inventory (TSCI) by (Vealey, 1986). The results of the Pearson product-moment correlation coefficient showed that there was a positive and moderate correlation between students’ body-esteem and sport-confidence and a negative and low correlation between students’ self-esteem and sport-confidence. Likewise, based on the entry method used all two predictor variables were significant in explaining sport confidence among UPSI students. In conclusion, it can be said that students’ sport-confidence affected by students’ self-esteem and body-esteem.

Keywords: body esteem, self-esteem, sport-confidence, students

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Authors: Karima Djebaili, Lamine Melkemi

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Elgamal encryption is a fundamental public-key encryption in cryptography, which is based on the difficulty of discrete logarithm problem and the Diffie-Hellman problem. Supposing the Diffie–Hellman problem is computationally infeasible then Elgamal is secure under a chosen plaintext attack, where security indicates it is difficult for the attacker, given the ciphertext, to restore the whole of the plaintext. However, although it is secure against chosen plaintext attack, Elgamal is absolutely malleable i.e. is not secure against an adaptive chosen ciphertext attack, where the attacker can recover the plaintext. We present a extension on Elgamal encryption which result in non-malleability against adaptive chosen plaintext attack using concatenation and a cryptographic hash function, our evidence utilizes the device of plaintext aware. The algorithm proposed can be used in cryptography voting protocol given its level security. Our protocol protects the confidentiality of voters because each voter encrypts their choice before casting their vote, offers public verifiability using a signing algorithm, the final result is correctly computed using homomorphic property, and works even in the presence of an adversary due to the propriety of non-malleability. Moreover, the protocol prevents some parties colluding to fix the vote results.

Keywords: Elgamal encryption, non-malleability, plaintext aware, e-voting

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Authors: David Pham, Yongfeng Zhang

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Graphs are an important structure for data storage and computation. Recent years have seen the success of deep learning on graphs such as Graph Neural Networks (GNN) on various data mining and machine learning tasks. However, most of the deep learning models on graphs cannot easily explain their predictions and are thus often labelled as “black boxes.” For example, Graph Attention Network (GAT) is a frequently used GNN architecture, which adopts an attention mechanism to carefully select the neighborhood nodes for message passing and aggregation. However, it is difficult to explain why certain neighbors are selected while others are not and how the selected neighbors contribute to the final classification result. In this paper, we present a graph learning model called Explainable Graph Attention Network (XGAT), which integrates graph attention modeling and explainability. We use a single model to target both the accuracy and explainability of problem spaces and show that in the context of graph attention modeling, we can design a unified neighborhood selection strategy that selects appropriate neighbor nodes for both better accuracy and enhanced explainability. To justify this, we conduct extensive experiments to better understand the behavior of our model under different conditions and show an increase in both accuracy and explainability.

Keywords: explainable AI, graph attention network, graph neural network, node classification

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Authors: Suman Podder

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As Australian ‘Open Banking’ allows customers to share their financial data with accredited Third-Party Providers (‘TPPs’), it is necessary to evaluate whether the regulators have achieved the balance between protecting customer data privacy and promoting data-related innovation. Recognising the need to increase customers’ influence on their own data, and the benefits of data-related innovation, the Australian Government introduced ‘Consumer Data Right’ (‘CDR’) to the banking sector through Open Banking regulation. Under Open Banking, TPPs can access customers’ banking data that allows the TPPs to tailor their products and services to meet customer needs at a more competitive price. This facilitated access and use of customer data will promote innovation by providing opportunities for new products and business models to emerge and grow. However, the success of Open Banking depends on the willingness of the customers to share their data, so the regulators have augmented the protection of data by introducing new privacy safeguards to instill confidence and trust in the system. The dilemma in policymaking is that, on the one hand, lenient data privacy laws will help the flow of information, but at the risk of individuals’ loss of privacy, on the other hand, stringent laws that adequately protect privacy may dissuade innovation. Using theoretical and doctrinal methods, this paper examines whether the privacy safeguards under Open Banking will add to the compliance burden of the participating financial institutions, resulting in the undesirable effect of stifling other policy objectives such as innovation. The contribution of this research is three-fold. In the emerging field of customer data sharing, this research is one of the few academic studies on the objectives and impact of Open Banking in the Australian context. Additionally, Open Banking is still in the early stages of implementation, so this research traces the evolution of Open Banking through policy debates regarding the desirability of customer data-sharing. Finally, the research focuses not only on the customers’ data privacy and juxtaposes it with another important objective of promoting innovation, but it also highlights the critical issues facing the data-sharing regime. This paper argues that while it is challenging to develop a regulatory framework for protecting data privacy without impeding innovation and jeopardising yet unknown opportunities, data privacy and innovation promote different aspects of customer welfare. This paper concludes that if a regulation is appropriately designed and implemented, the benefits of data-sharing will outweigh the cost of compliance with the CDR.

Keywords: consumer data right, innovation, open banking, privacy safeguards

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Authors: Bandari Shankar, Yohannes Yirga

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In this paper, the problem of heat and mass transfer in unsteady MHD boundary-layer flow of nanofluids over stretching sheet with a non uniform heat source/sink is considered. The unsteadiness in the flow and temperature is caused by the time-dependent stretching velocity and surface temperature. The unsteady boundary layer equations are transformed to a system of non-linear ordinary differential equations and solved numerically using Keller box method. The velocity, temperature, and concentration profiles were obtained and utilized to compute the skin-friction coefficient, local Nusselt number, and local Sherwood number for different values of the governing parameters viz. solid volume fraction parameter, unsteadiness parameter, magnetic field parameter, Schmidt number, space-dependent and temperature-dependent parameters for heat source/sink. A comparison of the numerical results of the present study with previously published data revealed an excellent agreement

Keywords: unsteady, heat and mass transfer, manetohydrodynamics, nanofluid, non-uniform heat source/sink, stretching sheet

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Authors: Imdat Taymaz, Erman Aslan, Kemal Cakir

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The Lattice Boltzmann Method (LBM) is performed to computationally investigate the laminar flow and heat transfer of an incompressible fluid with constant material properties in a 2D channel with a built-in triangular prism. Both momentum and energy transport is modelled by the LBM. A uniform lattice structure with a single time relaxation rule is used. Interpolation methods are applied for obtaining a higher flexibility on the computational grid, where the information is transferred from the lattice structure to the computational grid by Lagrange interpolation. The flow is researched on for different Reynolds number, while Prandtl number is keeping constant as a 0.7. The results show how the presence of a triangular prism effects the flow and heat transfer patterns for the steady-state and unsteady-periodic flow regimes. As an evaluation of the accuracy of the developed LBM code, the results are compared with those obtained by a commercial CFD code. It is observed that the present LBM code produces results that have similar accuracy with the well-established CFD code, as an additionally, LBM needs much smaller CPU time for the prediction of the unsteady phonema.

Keywords: laminar forced convection, lbm, triangular prism

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Authors: G. Venkata Rao, R. Srinivasa Rao, B. Neelima Sri Priya

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The over extraction of groundwater from the coastal aquifers, result in reduction of groundwater resource and lowering of water level. In general, the depletion of groundwater level enhances the landward migration of saltwater wedge. Now a days the ground water extraction increases by year to year because increased population and industrialization. The ground water is the only source of irrigation, domestic and Industrial purposes at Pydibhimavaram industrial area, which is located in the coastal belt of Srikakulam district, India of Latitudes 18.145N 83.627E and Longitudes 18.099N 83.674E. The present study has been attempted to calculate amount of water getting recharged into this aquifer, status of rainfall pattern for the past two decades and the runoff is calculated by using Khosla’s formula with available rainfall and temperature in the study area. A decision support model has been developed on the basis of Monthly Extractions of the water from the ground through bore wells and the Net Recharge of the aquifer. It is concluded that the amount of extractions is exceeding the amount of recharge from May to October in a given year which will in turn damage the water balance in the subsurface layers.

Keywords: aquifer, decision support model, groundwater extraction, run off estimation and rainfall

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Authors: Amit K. Singh, Subhankar Sen

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The bifurcation curve of separation in steady two-dimensional viscous flow past an elliptic cylinder is studied by varying the angle of incidence (α) with different aspect ratio (ratio of minor to major axis). The solutions are based on numerical investigation, using finite element analysis, of the Navier-Stokes equations for incompressible flow. Results are presented for Reynolds number up to 50 and angle of incidence varies from 0° to 90°. Range of aspect ratio (Ar) is from 0.1 to 1 (in steps of 0.1) and flow is considered as unbounded flow. Bifurcation curve represents the locus of Reynolds numbers (Res) at which flow detaches or separates from the surface of the body at a given α and Ar. In earlier studies, effect of Ar on laminar separation curve or bifurcation curve is limited for Ar = 0.1, 0.2, 0.5 and 0.8. Some results are also available at α = 90° and 45°. The present study attempts to provide a systematic data and clear understanding on the effect of Ar at bifurcation curve and its point of maxima. In addition, issues regarding location of separation angle and maximum ratio of coefficient of lift to drag are studied. We found that nature of curve, separation angle and maximum ratio of lift to drag changes considerably with respect to change in Ar.

Keywords: aspect ratio, bifurcation curve, elliptic cylinder, GMRES, stabilized finite-element

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Authors: Luiz Antonio Da Costa Rodrigues, Mara Aparecida De Castilho Lopes, Alexandre Santos Alencar

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Teaching of science must transcend simple transmission of fundamental concepts and allow scientific literacy, as a process for understanding the human being as an integral part of a complex and interdependent whole. In this context, approaching the theme ‘Antarctica’ in deaf education is an important advance for teaching, considering that that continent has direct interactions with the climatic and environmental system of the planet. Therefore, textbooks can be important tools to enable the Deaf Community to access the discussion about the natural environment. A specific script was used to analyze textbooks adopted by schools in the Rio de Janeiro Metropolitan Region. Results show that none of the 14 analyzed books have a specific chapter on the theme, some presents images of the continent without reference to their environmental importance, and the complementary texts present in the analyzed material do not address the theme either. It is concluded that the study on Antarctica and global changes in elementary education is still incipient and the material used by most Brazilian public schools does not contemplate that subject in an accessible way for the deaf person. This fact represents the distance between deaf students and their environment, denoting the need for actions to promote that and other neglected themes in Science teaching.

Keywords: Antarctica, deaf education, science teaching, textbook

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Authors: Lin Gong, Holger Göbel

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In the present study, we have investigated the influence of UV/ozone treatment on pentacene-based organic field effect transistors (OFETs) with a bilayer gate dielectric. The OFETs for this study were fabricated on heavily n-doped Si substrates with a thermally deposited SiO2 dielectric layer (300nm). On the SiO2 dielectric a very thin (≈ 15nm) buffer layer of polystyrene (PS) was first spin-coated and then treated by UV/ozone to modify the surface prior to the deposition of pentacene. We found out that by extending the UV/ozone treatment time the threshold voltage of the OFETs was monotonically shifted towards positive values, whereas the field effect mobility first decreased but eventually reached a stable value after a treatment time of approximately thirty seconds. Since the field effect mobility of the UV/ozone treated bilayer OFETs was found to be higher than the value of a comparable transistor with a single layer dielectric, we propose that the bilayer (SiO2/PS) structure can be used to shift the threshold voltage to a desired value without sacrificing field effect mobility.

Keywords: buffer layer, organic field effect transistors, threshold voltage, UV/ozone treatment

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Authors: Abdeljalil Métioui

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The purpose of this paper is to present the results of research on the conceptual representations of 128 Quebec (Canada) pre-service teachers enrolled in their third year of university in a program to train elementary teachers about heat and temperature. To identify their conceptual representations about heat and temperature, we constructed a multiple-choice questionnaire consisting of five questions. For each question, they had to explain their choice of an answer. At the methodological level, this step is essential to be able to identify the student conceptual representations. It should be noted that the selected questions were based: (1) on the works have done worldwide on primary and secondary students’ misconceptions about heat and temperature; (2) on the notions prescribed in the curriculum related to the physical world and (3) on student’s everyday contexts. As illustrations, the following are the erroneous conceptual representations identified in our analysis of the data collected: (1) The change of state of the matter does not require a constant temperature, (2) The temperature is a measure in degrees to indicate the level of heat of an object or person, (3) The mercury contained in a thermometer expands when it is heated so that the particles which constitute it expand and (4) The sensation of cold (or warm) is related to the difference in temperature. In conclusion, we will see that it is possible to develop situations of conflict, dealing specifically with the limits of the analogy between heat and temperature. These situations must consider the conceptual representations of the pre-service teachers, as well as the relevant scientific understanding of the concept of heat and temperature.

Keywords: conceptual representation, heat, temperature, pre-service teachers

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Authors: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad

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Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.

Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error

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Authors: Amela Ajanovic, Reinhard Haas

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Electric vehicles (EVs) are considered as an important means to cope with current environmental problems in transport. However, their high capital costs and limited driving ranges state major barriers to a broader market penetration. The core objective of this paper is to investigate the future market prospects of various types of EVs from an economic and ecological point of view. Our method of approach is based on the calculation of total cost of ownership of EVs in comparison to conventional cars and a life-cycle approach to assess the environmental benignity. The most crucial parameters in this context are km driven per year, depreciation time of the car and interest rate. The analysis of future prospects it is based on technological learning regarding investment costs of batteries. The major results are the major disadvantages of battery electric vehicles (BEVs) are the high capital costs, mainly due to the battery, and a low driving range in comparison to conventional vehicles. These problems could be reduced with plug-in hybrids (PHEV) and range extenders (REXs). However, these technologies have lower CO₂ emissions in the whole energy supply chain than conventional vehicles, but unlike BEV they are not zero-emission vehicles at the point of use. The number of km driven has a higher impact on total mobility costs than the learning rate. Hence, the use of EVs as taxis and in car-sharing leads to the best economic performance. The most popular EVs are currently full hybrid EVs. They have only slightly higher costs and similar operating ranges as conventional vehicles. But since they are dependent on fossil fuels, they can only be seen as energy efficiency measure. However, they can serve as a bridging technology, as long as BEVs and fuel cell vehicle do not gain high popularity, and together with PHEVs and REX contribute to faster technological learning and reduction in battery costs. Regarding the promotion of EVs, the best results could be reached with a combination of monetary and non-monetary incentives, as in Norway for example. The major conclusion is that to harvest the full environmental benefits of EVs a very important aspect is the introduction of CO₂-based fuel taxes. This should ensure that the electricity for EVs is generated from renewable energy sources; otherwise, total CO₂ emissions are likely higher than those of conventional cars.

Keywords: costs, mobility, policy, sustainability,

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Arseniy M. Kondratyev, Sergey V. Onufriev, Alexander I. Savvatimskiy

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The microsecond electrical pulse heating technique which provides uniform energy input into an investigated specimen is considered. In the present study we investigated ZrC+C carbide specimens in a form of a thin layer (about 5 microns thick) that were produced using a method of magnetron sputtering on insulating substrates. Specimens contained (at. %): Zr–17.88; C–67.69; N–8.13; O–5.98. Current through the specimen, voltage drop across it and radiation at the wavelength of 856 nm were recorded in the experiments. It enabled us to calculate the input energy, specific heat (from 2300 to 4500 K) and resistivity (referred to the initial dimensions of a specimen). To obtain the true temperature a black body specimen was used. Temperature of the beginning and completion of a phase transition (solid–liquid) was measured.Temperature of the onset of melting was 3150 K at the input energy 2.65 kJ/g; temperature of the completion of melting was 3450 K at the input energy 5.2 kJ/g. The specific heat of the solid phase of investigated carbide calculated using our data on temperature and imparted energy, is close to 0.75 J/gК for temperature range 2100–2800 K. Our results are considered together with the equilibrium Zr-C phase diagram.

Keywords: pulse heating, zirconium carbide, high temperatures, melting

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Authors: Sonia Gonzalez Cruz

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Subtitling activities allow for acquiring and developing certain translation skills, and they also have a great impact on the students' motivation. Active subtitling is a relatively recent activity that has generated a lot of interest particularly in the field of second-language acquisition, but it is also present within both the didactics of general translation and language teaching for translators. It is interesting to analyze the level of inclusion of these new resources into the existent curricula and observe to what extent these different teaching methods are being used in the translation classroom. Although subtitling has already become an independent discipline of study and it is considered to be a type of translation on its own, it is necessary to do further research on the different didactic varieties that this type of audiovisual translation offers. Therefore, this project is framed within the field of the didactics of translation, and it focuses on the relationship between the didactics of general translation and active subtitling as a didactic tool. Its main objective is to analyze the inclusion of interlinguistic active subtitling in general translation curricula at different universities. As it has been observed so far, the analyzed curricula do not make any type of reference to the use of this didactic tool in general translation classrooms. However, they do register the inclusion of other audiovisual activities such as dubbing, script translation or video watching, among others. By means of online questionnaires and interviews, the main goal is to confirm the results obtained after the observation of the curricula and find out to what extent subtitling has actually been included into general translation classrooms.

Keywords: subtitling, general translation, didactics, translation competence

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Authors: Andrea Paltrinieri, Alberto Dreassi, Stefano Miani, Alex Sclip

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The financial crises caused a collapse in prices of most asset classes, raising the attention on alternative investments such as Sukuk, a smaller, fast growing but often misunderstood market. We study diversification benefits of Sukuk, their correlation with other asset classes and the effects of their inclusion in investment portfolios of institutional and retail investors, through a comprehensive comparison of their risk/return profiles during and after the financial crisis. We find a beneficial performance adjusted for the specific volatility together with a lower correlation especially during the financial crisis. The distribution of Sukuk returns is positively skewed and leptokurtic, with a risk/return profile similarly to high yield bonds. Overall, our results suggest that Sukuk present diversification opportunities, a significant volatility-adjusted performance and lower correlations especially during the financial crisis. Our findings are relevant for a number of institutional investors. Long term investors, such as life insurers would benefit from Sukuk’s protective features during financial crisis yet keeping return and growth opportunities, whereas banks would gain due to their role of placers, advisors, market makers or underwriters.

Keywords: sukuk, zero beta asset, asset allocation, sukuk market

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Authors: Emiko Suzuki

Abstract:

Although fitness is defined as the body’s ability to respond to the demand of physical activity without undue fatigue in health science, in media oftentimes physical activity is presented as means to an attractive body rather than a fit and healthy one. Of all types of media, Instagram is becoming an increasingly persuasive source of information and advice on health and fitness, where individuals conceptualize what health and fitness mean for them. However, this user-generated and unregulated platform can be problematic, as it can communicate misleading information about health and fitness and possibly leading individuals to psychological problems such as eating disorders. In fact, previous research has shown that some messages that were posted with a tag that related to inspire others to do fitness, in fact, encouraged distancing the self from the internal needs of the body. For this reason, this present study aims to explore how health and fitness are communicated on Instagram by analyzing images and texts. A content analysis of images that were labeled with particular hashtags was performed, followed by a thematic analysis of texts from the same set of images. The result shows an interesting insight about messages about how health and fitness are communicated from companies through media, then digested and further shared among communities on Instagram. The study explores how the use of visual focused way of communicating health and fitness can lead to the dehumanization of human bodies.

Keywords: Instagram, fitness, dehumanization, body image, embodiment

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Authors: Behnaz Zolfaghari

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In civilized societies, linguists seek to find suitable equivalents for scientific terms in the common language of their society. Many researches have conducted surveys about language of science on one hand and media discourse on the other, but the goal of this research is the comparative analysis of science discourse in Persian academic media and public discourse in the general Persian media by applying experimental meta-function as one of the four theoretical tools introduced by Holiday’s Systemic Functional Grammar .The said analysis aims to explore the processes that can convert the language in which scientific facts are published to a language well suited to the interested layman. The results of comparison show that these two discourses use differently six processes of experimental meta-function. Comparing the redundancy of different processes, the researcher tried to re-identify these differences in these two discourses and present a model for the procedures of converting science discourse to popularized discourse. This model can be useful for those journalists and textbook authors who want to restate scientific technical texts in a simple style for inexpert addresser including general people and students.

Keywords: systemic functional grammar, discourse analysis, science language, popularization, media discourse

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Authors: Riccardo Zanni, Maria Galvez-Llompart, Ramon Garcia-Domenech, Jorge Galvez

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Biopesticides, such as naturally occurring chemicals, pheromones, fungi, bacteria and insect predators are often a winning choice in crop protection because of their environmental friendly profile. They are considered to have lower toxicity than traditional pesticides. After almost a century of pesticides use, resistances to traditional insecticides are wide spread, while those to bioinsecticides have raised less attention, and resistance management is frequently neglected. This seems to be a crucial mistake since resistances have already occurred for many marketed biopesticides. With an eye to the future, we present here a selection of new natural occurring chemicals as potential bioinsecticides. The molecules were selected using a consolidated mathematical paradigm called molecular topology. Several QSAR equations were depicted and subsequently applied for the virtual screening of hundred thousands molecules of natural origin, which resulted in the selection of new potential bioinsecticides. The most innovative aspect of this work does not only reside in the importance of the identification of new molecules overcoming biopesticides’ resistances, but on the possibility to promote shared knowledge in the field of green chemistry through this unique in silico discipline named molecular topology.

Keywords: green chemistry, QSAR, molecular topology, biopesticide

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Authors: Hammad Khan, Wookeun Bae

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The objective of this study was to optimize, achieve and control the highly loaded and efficient nitrite production having suitability for autotrophic and heterotrophic denitritation. A lab scale CSTR for partial and full nitritation was operated to treat the livestock manure digester liquor having an ammonium concentration of ~600 mg-NH4+-N/L and biodegradable contents of ~0.35 g-COD/L. The experiments were performed at 30°C, pH: 8.0, DO: 1.5 mg/L and SRT ranging from 7-20 days. After 125 days operation, >95% nitrite buildup having the ammonium loading rate of ~3.2 kg-NH4+-N/m3-day was seen with almost complete ammonium conversion. On increasing the loading rate further (i-e, from 3.2-6.2 kg-NH4+-N/m3-day), stability of the system remained unaffected. On decreasing the pH from 8 to7.5 and further 7.2, removal rate can be easily controlled as 95%, 75%, and even 50%. Results demonstrated that nitritation stability and desired removal rates are controlled by a balance of simultaneous inhibition by FA & FNA, pH affect and DO limitation. These parameters proved to be effective even to produce an appropriate influent for anammox. In addition, a mathematical model, identified through the occurring biological reactions, is proposed to optimize the full and partial nitritation process. The proposed model present relationship between pH, ammonium and produced nitrite for full and partial nitritation under the varying concentrations of DO, and simultaneous inhibition by FA and FNA.

Keywords: stable nitritation, high loading, autrophic denitritation, CSTR

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Authors: Ursula D. C. Resende, Yan G. Santos, Lucas M. de O. Andrade

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The recent and fast development of the internet, wireless, telecommunication technologies and low-power electronic devices has led to an expressive amount of electromagnetic energy available in the environment and the smart applications technology expansion. These applications have been used in the Internet of Things devices, 4G and 5G solutions. The main feature of this technology is the use of the wireless sensor. Although these sensors are low-power loads, their use imposes huge challenges in terms of an efficient and reliable way for power supply in order to avoid the traditional battery. The radio frequency based energy harvesting technology is especially suitable to wireless power sensors by using a rectenna since it can be completely integrated into the distributed hosting sensors structure, reducing its cost, maintenance and environmental impact. The rectenna is an equipment composed of an antenna and a rectifier circuit. The antenna function is to collect as much radio frequency radiation as possible and transfer it to the rectifier, which is a nonlinear circuit, that converts the very low input radio frequency energy into direct current voltage. In this work, a set of rectennas, mounted on a paper substrate, which can be used for the inner coating of buildings and simultaneously harvest electromagnetic energy from the environment, is proposed. Each proposed individual rectenna is composed of a 2.45 GHz patch antenna and a voltage doubler rectifier circuit, built in the same paper substrate. The antenna contains a rectangular radiator element and a microstrip transmission line that was projected and optimized by using the Computer Simulation Software (CST) in order to obtain values of S11 parameter below -10 dB in 2.45 GHz. In order to increase the amount of harvested power, eight individual rectennas, incorporating metamaterial cells, were connected in parallel forming a system, denominated Electromagnetic Wall (EW). In order to evaluate the EW performance, it was positioned at a variable distance from the internet router, and a 27 kΩ resistive load was fed. The results obtained showed that if more than one rectenna is associated in parallel, enough power level can be achieved in order to feed very low consumption sensors. The 0.12 m2 EW proposed in this work was able to harvest 0.6 mW from the environment. It also observed that the use of metamaterial structures provide an expressive growth in the amount of electromagnetic energy harvested, which was increased from 0. 2mW to 0.6 mW.

Keywords: electromagnetic energy harvesting, metamaterial, rectenna, rectifier circuit

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Authors: Nathenal Thomas Lambamo

Abstract:

Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

Procedia PDF Downloads 70