Search results for: edge application framework

Authors: David Robert Irvine

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In the dental restoration sector, there has been a shift to using zirconia. With the ever increasing need to decrease lead times to deliver restorations faster the zirconia is machined in its pre-sintered state instead of grinding the very hard sintered state. As with all machining, there is tool wear and while investigating the tooling used to machine pre-sintered zirconia it became apparent that the wear rate is based more on material build up and abrasion than it is on plastic deformation like conventional metal machining. It also came to light that the tool material can currently not be selected based on wear resistance, as there is no data. Different works have analysed the effect of the individual wear mechanism separately using similar if not the same material. In this work, the testing method used to analyse the wear was a modified from ISO 8688:1989 to use the pre-sintered zirconia and the cutting conditions used in dental to machine it. This understanding was developed through a series of tests based in machining operations, to give the best representation of the multiple wear factors that can occur in machining of pre-sintered zirconia such as 3 body abrasion, material build up, surface welding, plastic deformation, tool vibration and thermal cracking. From the testing, it found that carbide grades with low trans-granular rupture toughness would fail due to abrasion while those with high trans-granular rupture toughness failed due to edge chipping from build up or thermal properties. The results gained can assist the development of these tools and the restorative dental process. This work was completed with the aim of assisting in the selection of tool material for future tools along with a deeper understanding of the properties that assist in abrasive wear resistance and material build up.

Keywords: abrasive wear, cemented carbide, pre-sintered zirconia, tool wear

Procedia PDF Downloads 151

Authors: Mohammad Hossein Bayati Chaleshtari, Hadi Khoramishad

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Minimizing the stress concentration around triangular cutout in infinite perforated plates subjected to a uniform heat flux induces thermal stresses is an important consideration in engineering design. Furthermore, understanding the effective parameters on stress concentration and proper selection of these parameters enables the designer to achieve a reliable design. In the analysis of thermal stress, the effective parameters on stress distribution around cutout include fiber angle, flux angle, bluntness and rotation angle of the cutout for orthotropic materials. This paper was tried to examine effect of these parameters on thermal stress analysis of infinite perforated plates with central triangular cutout. In order to achieve the least amount of thermal stress around a triangular cutout using a novel swarm intelligence optimization technique called dragonfly optimizer that inspired by the life method and hunting behavior of dragonfly in nature. In this study, using the two-dimensional thermoelastic theory and based on the Likhnitskiiʼ complex variable technique, the stress analysis of orthotropic infinite plate with a circular cutout under a uniform heat flux was developed to the plate containing a quasi-triangular cutout in thermal steady state condition. To achieve this goal, a conformal mapping function was used to map an infinite plate containing a quasi- triangular cutout into the outside of a unit circle. The plate is under uniform heat flux at infinity and Neumann boundary conditions and thermal-insulated condition at the edge of the cutout were considered.

Keywords: infinite perforated plate, complex variable method, thermal stress, optimization method

Procedia PDF Downloads 129

Authors: H. E. M. W. G. M. K. Ekanayake, J. Dharmasena

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Natural Landscape fragmentation and habitat loss are emerging issues in Sri Lanka, which is due to rapid urban development and inadequate concern of managing Landscape connectivity. Urban Wetlands are the most vulnerable ecosystem effects from the fragmentation. Therefore, management of landscape connectivity with proper analysis and understanding has become a most important measure for urban wetland habitats. This study aimed to introduce spatial planning strategy to identify and locate landscape developments appropriately in order to restore landscape connectivity. Therefore, the study focuses on understanding the relationship between habitat patch metrics and landscape connectivity with reference to Colombo wetlands. Geographic Information Systems (GIS) was used to measure the wetland patch metrics; Patch area, Total edge, Perimeter-area ratio, Core area index and Inter-patch distances. Further, GIS-enabled least-cost path tool was used to measure the Landscape connectivity and calculate the number of species flow paths per wetland patch. According to the research findings; increasing the patch area, maintaining a mean perimeter-area ratio and core area index also reducing the inter-patch distances could enhance the landscape connectivity. Further, this study introduces three patch typologies; ‘active patches,' ‘open patches’ and ‘closed patches’ that severs to landscape connectivity in different levels. In the end, the study proposes a strategy for Landscape Architects to select most suitable locations to implement ecological based landscape developments with adjacent to the existing urban habitat in order to enhance habitat patch metrics and to restore the landscape connectivity.

Keywords: landscape fragmentation, urban wetlands, landscape connectivity, patch metrics

Procedia PDF Downloads 187

Authors: Yang Bao, Shi Wei Deng, WangQun Lin

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This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

Procedia PDF Downloads 549

Authors: D. M. Lewis, L. Frisby, U. Stead

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Objective: Many patients are receiving invasive treatments in acute care or are dying in hospital without having had comprehensive goals of care conversations. Some of these treatments may not align with the patient’s wishes, may be futile, and may cause unnecessary suffering. While many staff may recognize the benefits of engaging patients and families in Serious Illness Conversations (a goal of care framework developed by Ariadne Labs in Boston), few staff feel confident and/or competent in having these conversations in acute care. Another barrier to having these conversations may be due to a lack of incorporation in the current workflow. An educational exercise, titled the Two Question Challenge, was initiated on four medical units across two Vancouver Coastal Health (VCH) hospitals in attempt to engage the entire interdisciplinary team in asking patients and families questions around goals of care and to improve the documentation of these expressed wishes and preferences. Methods: Four acute care units across two separate hospitals participated in the Two Question Challenge. On each unit, over the course of two eight-hour shifts, all members of the interdisciplinary team were asked to select at least two questions from a selection of nine goals of care questions. They were asked to pose these questions of a patient or family member throughout their shift and then asked to document their conversations in a centralized Advance Care Planning/Goals of Care discussion record in the patient’s chart. A visual representation of conversation outcomes was created to demonstrate to staff and patients the breadth of conversations that took place throughout the challenge. Staff and patients were interviewed about their experiences throughout the challenge. Two palliative approach leads remained present on the units throughout the challenge to support, guide, or role model these conversations. Results: Across four acute care medical units, 47 interdisciplinary staff participated in the Two Question Challenge, including nursing, allied health, and a physician. A total of 88 questions were asked of patients, or their families around goals of care and 50 newly documented goals of care conversations were charted. Two code statuses were changed as a result of the conversations. Patients voiced an appreciation for these conversations and staff were able to successfully incorporate these questions into their daily care. Conclusion: The Two Question Challenge proved to be an effective way of having teams explore the goals of care of patients and families in an acute care setting. Staff felt that they gained confidence and competence. Both staff and patients found these conversations to be meaningful and impactful and felt they were notably different from their usual interactions. Documentation of these conversations in a centralized location that is easily accessible to all care providers increased significantly. Application of the Two Question Challenge in non-medical units or other care settings, such as long-term care facilities or community health units, should be explored in the future.

Keywords: advance care planning, goals of care, interdisciplinary, palliative approach, serious illness conversations

Procedia PDF Downloads 89

Authors: Omar Alsetoohy, Mohamed Ezzat, Mahmoud Abou Kamar

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The success of a restaurant or hotel depends very much on the quality and quantity of its human resources. Thus, establishing a competitive edge through human assets requires careful attention to the practices that best leverage these assets. Usually, hotel or restaurant employees recognize customer defection as an unfavorable or unpleasant occurrence associated with failure. These failures could be in handling, communication, learning, or encouragement. Besides, employees could be afraid of blame from their colleagues and managers, which prevents them from freely discussing these mistakes with them. Such behaviors, in turn, would push employees to withdraw from the workplace. However, we have a good knowledge of the leadership outcomes, but less is known about how and why these effects occur. Accordingly, mindful leaders usually analyze the causes and underlying mechanisms of failures for work improvement. However, despite the excessive literature in the field of leadership and employee behaviors, to date, no research studies had investigated the impact of a failure-tolerant restaurant culture on the employees’ withdrawal behaviors considering the moderating role of psychological empowerment and mindful leadership. Thus, this study seeks to investigate the impact of a failure-tolerant culture on the employees’ withdrawal behaviors in fast-food restaurants in Egypt considering the moderating effects of employee empowerment and mindful leaders. This study may contribute to the existing literature by filling the gap between failure-tolerant cultures and employee withdrawal behaviors in the hospitality literature. The study may also identify the best practices for restaurant operators and managers to deal with employees' failures as an improvement tool for their performance.

Keywords: failure-tolerant culture, employees’ withdrawal behaviors psychological empowerment, mindful leadership, restaurants

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Authors: A. Serap Fırat

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The aim of this study is to display conceptually the relationship and interaction between matter of human resources training and the information age. Fast development from industrial community to an information community has occurred and organizations have been seeking ways to overcome this change. Human resources policy and human capital with enhanced competence will have direct impact on work performance; therefore, this paper deals with the increased importance of human resource management due to the fact that it nurtures human capital. Researching and scanning are used as a method in this study. Both local and foreign literature and expert views are employed -as much as one could be- in the making of the theoretical framework of this study.

Keywords: human resources, information age, education, organization, occupation

Procedia PDF Downloads 355

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Vassiliki Drosou, Theoni Oikonomou

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EU-SOLARIS will form a new legal entity to explore and implement improved rules and procedures for Research Infrastructures (RI) for Concentrated Solar Thermal (CST) and solar chemistry technologies, in order to optimize RI development and R&D coordination. It is expected to be the first of its kind, where industrial needs and private funding will play a significant role. The success of EU-SOLARIS initiative will be the establishment of a new governance body, aided by sustainable financial models. EU-SOLARIS is expected to be an important tool, which will provide the most complete, high quality scientific infrastructure portfolio at international level and to facilitate researchers' access to highly specialised research infrastructure through a single access point. This will be accomplished by linking scientific communities, industry and universities involved in the CST sector. The access to be offered by EU-SOLARIS will guarantee the direct contact of experienced scientists with newcomers and interested students. The set of RIs participating in EU-SOLARIS will offer access to state of the art infrastructures, high-quality services, and will enable users to conduct high quality research. Access to these facilities will contribute to the enhancement of the European research area by: -Opening installations to European and non-European scientists, coming from both academia and industry, thus improving co-operation. -Improving scientific critical mass in domains where knowledge is now widely dispersed. -Generating strong Europe-wide R&D project consortia, increasing the competitiveness of each member alone. EU-SOLARIS will be created in the framework of a European project, co-funded by the 7th Framework Programme of the European Union –whose initiative is to foster, contribute and promote the scientific and technological development of the CST and solar chemistry technologies. Primary objective of EU-SOLARIS is to contribute to the improvement of the state of the art of these technologies with the aim of preserving and reinforcing the European leadership in this field, in which EU-SOLARIS is expected to be a valuable instrument. EU-SOLARIS scope, activities, objectives, current status and vision will be given in the article. Moreover, the rules, processes and criteria regulating the access to the research infrastructures included in EU-SOLARIS will be presented.

Keywords: concentrated solar thermal (CST) technology, renewable energy sources, research infrastructures, solar chemistry

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Authors: Mariia Khramova, Sergio Martinez, Duc Nguyen

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Modern electronic devices, particularly smartphones, are characterised by extremely high environmental footprint and short product lifecycle. Every year manufacturers release new models with even more superior performance, which pushes the customers towards new purchases. As a result, millions of devices are being accumulated in the urban mine. To tackle these challenges the concept of circular economy has been introduced to promote repair, reuse and recycle of electronics. In this case, electronic devices, that previously ended up in landfills or households, are getting the second life, therefore, reducing the demand for new raw materials. Smartphone reuse is gradually gaining wider adoption partly due to the price increase of flagship models, consequently, boosting circular economy implementation. However, along with reuse of communication device, circular economy approach needs to ensure the data of the previous user have not been 'reused' together with a device. This is especially important since modern smartphones are comparable with computers in terms of performance and amount of data stored. These data vary from pictures, videos, call logs to social security numbers, passport and credit card details, from personal information to corporate confidential data. To assess how well the data privacy requirements are followed on smartphones second-hand market, a sample of 100 Android smartphones has been purchased from IT Asset Disposition (ITAD) facilities responsible for data erasure and resell. Although devices should not have stored any user data by the time they leave ITAD, it has been possible to retrieve the data from 19% of the sample. Applied techniques varied from manual device inspection to sophisticated equipment and tools. These findings indicate significant barrier in implementation of circular economy and a limitation of smartphone reuse. Therefore, in order to motivate the users to donate or sell their old devices and make electronic use more sustainable, data privacy on second-hand smartphone market should be significantly improved. Presented research has been carried out in the framework of sustainablySMART project, which is part of Horizon 2020 EU Framework Programme for Research and Innovation.

Keywords: android, circular economy, data privacy, second-hand phones

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Authors: Eugene Rybin

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Reduction of nutrient losses when using mineral fertilizers is a very important and urgent challenge, which is of both economic and environmental significance. This paper shows the production of slow- and controlled release fertilizers through application of inorganic coatings, which make the released nutrients plant-available. The method of production of coated fertilizers with inorganic cover material is an alternative to other methods where polymer coatings are used. The method is based on spraying an aqueous slurry onto the surface of granules with simultaneous drying in drums under certain conditions and subsequent cooling of granules. This method of production of slow- and controlled-release fertilizers is more ecofriendly compared with others because inorganic materials are used to create a membrane. That is why the coating material is definitely biodegradable. There is also shown the effect of these coatings on the properties of fertilizers, as well as on the agrochemical efficiency and nutrient efficiency/ availability to the plants. The agrochemical tests have proved the increase of nutrient efficiency for every nutrient in compound fertilizers (NPK, NPS) for 3 consecutive years by 10-20 % and by 25-28% for urea, as well as an increase in crop yield, by 10-15% in general, and its quality. Moreover, the decrease in caking by almost 70% was proven as well as slowing down the release rate of nutrients from fertilizers. Control of the release rate was achieved by regulation of thickness and contents of coating materials. All of those characteristics were researched according to the standard-used methods. The performed research has developed the fertilizer technology of slow- and controlled release of nutrients through applying of plant-available inorganic coatings. It leads to a better synchronization of nutrient release rate and plants needs, as well as reduces the harmful effects on the environment from the fertilizers applied.

Keywords: controlled release, fertilizers, nutrients, plant-available coatings

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Authors: Huiqiang Yang, Domingo Santana

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This paper proposes a novel configuration which introduces a natural draft dry cooling tower system in a molten salt power tower. A three-dimensional numerical modeling was developed based on the novel configuration. A plan of building 20 new concentrating solar power plants has been announced by Chinese government in September 2016, and among these 20 new plants, most of them are located in regions with long winter and harsh winter climate. The innovative configuration proposed includes an external receiver concrete tower at the center, a natural draft dry cooling tower which is surrounding the external receiver concrete tower and whose shell is fixed on the external receiver concrete tower, and a power block (including a steam generation system, a steam turbine system and hot/cold molten salt tanks, and water treatment systems) is covered by the roof of the natural draft dry cooling tower. Heat exchanger bundles are vertically installed at the furthest edge of the power block. In such a way, all power block equipment operates under suitable environmental conditions through whole year operation. The monthly performance of the novel configuration is simulated as compared to a standard one. The results show that the novel configuration is much more efficient in each separate month in a typical meteorological year. Moreover, all systems inside the power block have less thermal losses at low ambient temperatures, especially in harsh winter climate. It is also worthwhile mentioning that a photovoltaic power plant can be installed on the roof of the cooling tower to reduce the parasites of the molten salt power tower.

Keywords: molten salt power tower, natural draft dry cooling, commercial scale, power block, harsh winter climate

Procedia PDF Downloads 326

Authors: Dušan Bojović, Wei Huang, Zdravko Stojanović, Jovan Ilić

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In an era of ever-growing electricity generation from renewable energy sources, namely wind and solar, a need for reliable energy storage and intensive balancing of the electric power system gains significance. For decades, pump storage hydroelectric power plants have proven to be an important asset regarding the storage of generated electricity. However, with the increasing overall share of wind and solar in electric systems at large, the importance of electric grid stability keeps growing. A large pump storage project, the Bistrica Pump Storage Plant (PSP), is currently under development in Serbia. The Bistrica PSP will be designed as a 600+ MW power plant, which is envisaged as a significant contributor to the Serbian power grid stability as more and more renewable energy sources are implemented over time. PSP Bistrica is seen as a strategically important project on the green agenda path of the Electric Power Industry of Serbia as a necessary pre-condition for the safe implementation of other renewable energy sources. The importance of such a plant would also play an important role in reducing the electricity production from coal, i.e., thermoelectric power plants. During the project’s development, various techniques and technologies are evaluated for the purpose of determining the optimum (the most profitable) solution. Over the course of this paper, these technologies – such as frequency-regulated pump turbines and ternary sets will be presented, with a detailed explanation of their possible application within the Bistrica PSP project and their relative advantages/disadvantages in this particular case.

Keywords: hydraulic turbines, pumped storage, renewable energy, competing technologies

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Authors: Hadjer Didouh, Izzaddine Sameut Bouhaik, Mohammed Hadj Meliani

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This research delves into the intricate dynamics of biofilm adhesion on surfaces, particularly focusing on the widely employed X52 surface in oil and gas industry pipelines. Biofilms, characterized by microorganisms within a self-produced matrix, pose significant challenges due to their detrimental impact on surfaces. Our study integrates advanced molecular techniques and cutting-edge microscopy, such as scanning electron microscopy (SEM), to identify microbial communities and visually assess biofilm adhesion. Simultaneously, we concentrate on the X52 surface, utilizing impedance spectroscopy and potentiodynamic polarization to gather electrochemical responses under various conditions. In conjunction with the broader investigation, we propose a novel approach to mitigate biofilm-induced corrosion challenges. This involves environmentally friendly inhibitors derived from plants, offering a sustainable alternative to conventional chemical treatments. Our inquiry screens and selects inhibitors based on their efficacy in hindering biofilm formation and reducing corrosion rates on the X52 surface. This study contributes valuable insights into the interplay between electrochemical processes and biofilm attachment on the X52 surface. Furthermore, the outcomes of this research have broader implications for the oil and gas industry, where biofilm-related corrosion is a persistent concern. The exploration of eco-friendly inhibitors not only holds promise for corrosion control but also aligns with environmental considerations and sustainability goals. The comprehensive nature of this research aims to enhance our understanding of biofilm dynamics, provide effective strategies for corrosion mitigation, and contribute to sustainable practices in pipeline management within the oil and gas sector.

Keywords: bio-corrosion, biofilm, attachment, X52, metal/bacteria interface

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

Procedia PDF Downloads 57

Authors: Kuate Tueguem William Norbert, Ngoh Dooh Jules Patrice, Kone Sangou Abdou Nourou, Mboussi Serge Bertrand, Chewachang Godwill Mih, Essome Sale Charles, Djuissi Tohoto Doriane, Ambang Zachee

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The objectives of this study were to evaluate the effects of foliar application of 24-epibrassinolide (EBR) on the development of rice helminthosporiosis caused by Bipolaris oryzae and its influence on the improvement of growth parameters and induction of the synthesis of defense substances in the rice plants. The experimental asset up involved a multifactorial split-plot with two varieties (NERICA 3 and local variety KAMKOU) and five treatments (T0: control, T1: EBR, T2: BANKO PLUS (fungicide), T3: NPK (chemical fertilizer), T4: mixture: NPK + BANKO PLUS + EBR) with three repetitions. Agro-morphological and epidemiological parameters, as well as substances for plant resistance, were evaluated over two growing seasons. The application of the EBR induced significant growth of the rice plants for the 2015 and 2016 growing seasons on the two varieties tested compared to the T0 treatment. At 74 days after sowing (DAS), NERICA 3 showed plant heights of 58.9 ± 5.4; 83.1 ± 10.4; 86.01 ± 9.4; 69.4 ± 11.1 and 87.12 ± 7.4 cm at T0; T1; T2; T3, and T4, respectively. Plant height for the variety KAMKOU varied from 87,12 ± 8,1; 88.1 ± 8.1 and 92.02 ± 6.3 cm in T1, T2, and T3 to 74.1 ± 8.6 and 74.21 ± 11.4 cm in T0 and T3. In accordance with the low rate of expansion of helminthosporiosis in experimental plots, EBR (T1) significantly reduced the development of the disease with severities of 0.0; 1.29, and 2.04%, respectively at 78; 92, and 111 DAS on the variety NERICA 3 compared with1; 3.15 and 3.79% in the control T0. The reduction of disease development/severity as a result of the application of EBR is due to the induction of acquired resistance of rice varieties through increased phenol (13.73 eqAG/mg/PMF) and total protein (117.89 eqBSA/mg/PMF) in the T1 treatment against 5.37 eqAG/mg/PMF and 104.97 eqBSA/mg/PMF in T0 for the NERICA 3 variety. Similarly, on the KAMKOU variety, 148.53 eqBSA/mg/PMF were protein and 6.10 eqAG/mg/PMF of phenol in T1. In summary, the results show the significant effect of EBR on plant growth, yield, synthesis of secondary metabolites and defense proteins, and disease resistance. The EBR significantly reduced losses of rice grains by causing an average gain of about 1.55 t/ha compared to the control and 1.00 t/ha compared to the NPK-based treatment for the two varieties studied. Further, the enzymatic activities of PPOs, POXs, and PR2s were higher in leaves from treated EBR-based plants. These results show that 24-epibrassinolide can be used in the control of helminthosporiosis of rice to reduce disease and increase yields.

Keywords: Oryza sativa, 24-epibrassinolide, helminthosporiosis, secondary metabolites, PR proteins, acquired resistance

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Authors: Deepak Singh, Rail Kuliev

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The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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Authors: Mohamed Amhal, Jose Sayritupac

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Photovoltaic (PV) systems have risen as one of the modern renewable energy sources that are used in wide ranges to produce electricity and deliver it to the electrical grid. In parallel, monitoring systems have been deployed as a key element to track the energy production and to forecast the total production for the next days. The reliability of the PV energy production has become a crucial point in the analysis of PV systems. A deeper understanding of each phenomenon that causes a gain or a loss of energy is needed to better design, operate and maintain the PV systems. This work analyzes the current losses distribution in PV systems starting from the available solar energy, going through the DC side and AC side, to the delivery point. Most of the phenomena linked to energy losses and gains are considered and modeled, based on real time monitoring data and datasheets of the PV system components. An analysis of the order of magnitude of each loss is compared to the current literature and commercial software. To date, the analysis of PV systems performance based on a breakdown structure of energy losses and gains is not covered enough in the literature, except in some software where the concept is very common. The cutting-edge of the current analysis is the implementation of software tools for energy losses estimation in PV systems based on several energy losses definitions and estimation technics. The developed tools have been validated and tested on some PV plants in France, which are operating for years. Among the major findings of the current study: First, PV plants in France show very low rates of soiling and aging. Second, the distribution of other losses is comparable to the literature. Third, all losses reported are correlated to operational and environmental conditions. For future work, an extended analysis on further PV plants in France and abroad will be performed.

Keywords: energy gains, energy losses, losses distribution, monitoring, photovoltaic, photovoltaic systems

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Authors: Martial Amou

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This study was carried out to assess the situation of households’ livelihood under a changing climate pattern in the Zio district of Togo, West Africa. The study examined three important aspects: (i) assessment of households’ livelihood situation under a changing climate pattern, (ii) farmers’ perception and understanding of local climate change, (iii) determinants of adaptation strategies undertaken in cropping pattern to climate change. To this end, secondary sources of data, and survey data collected from 235 farmers in four villages in the study area were used. Adapted conceptual framework from Sustainable Livelihood Framework of DFID, two steps Binary Logistic Regression Model and descriptive statistics were used in this study as methodological approaches. Based on Sustainable Livelihood Approach (SLA), various factors revolving around the livelihoods of the rural community were grouped into social, natural, physical, human, and financial capital. Thus, the study came up that households’ livelihood situation represented by the overall livelihood index in the study area (34%) is below the standard average households’ livelihood security index (50%). The natural capital was found as the poorest asset (13%) and this will severely affect the sustainability of livelihood in the long run. The result from descriptive statistics and the first step regression (selection model) indicated that most of the farmers in the study area have clear understanding of climate change even though they do not have any idea about greenhouse gases as the main cause behind the issue. From the second step regression (output model) result, education, farming experience, access to credit, access to extension services, cropland size, membership of a social group, distance to the nearest input market, were found to be the significant determinants of adaptation measures undertaken in cropping pattern by farmers in the study area. Based on the result of this study, recommendations are made to farmers, policy makers, institutions, and development service providers in order to better target interventions which build, promote or facilitate the adoption of adaptation measures with potential to build resilience to climate change and then improve rural livelihood.

Keywords: climate change, rural livelihood, cropping pattern, adaptation, Zio District

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Sarah Irani, Meisam Modarresi

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Lifestyle entrepreneurship allows the business owner to create a business activity that aligns with their values, interests, and motivations. Examining the views and experiences of lifestyle entrepreneurs has an essential impact on the growth of the entrepreneurial economy and the concept of entrepreneurship. The primary purpose of this research is to discover the main and secondary influencing aspects of lifestyle entrepreneurship. This research is qualitative and tries to develop research in this field by presenting a framework from the literature. This study can provide a clear picture of lifestyle entrepreneurship. The results showed that lifestyle entrepreneurship is influenced by four main aspects.

Keywords: entrepreneurship, entrepreneurs, innovation, lifestyle entrepreneurship, small businesses development

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Andres Diaz Garcia, Ana Maria Ceballos Rojas, Duvan Albeiro Millan Montano

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This paper describes the initial technological development stages in the area of liquid fermentation required to reach the quantities of biomass of the biofertilizer microorganism Rhizobium sp. strain B02, for the application of the unitary stages downstream at laboratory scale. In the first stage, the adjustment and standardization of the fermentation process in conventional batch mode were carried out. In the second stage, various fed-batch and continuous fermentation strategies were evaluated in 10L-bioreactor in order to optimize the yields in concentration (Colony Forming Units/ml•h) and biomass (g/l•h), to make feasible the application of unit operations downstream of process. The growth kinetics, the evolution of dissolved oxygen and the pH profile generated in each of the strategies were monitored and used to make sequential adjustments. Once the fermentation was finished, the final concentration and viability of the obtained biomass were determined and performance parameters were calculated with the purpose of select the optimal operating conditions that significantly improved the baseline results. Under the conditions adjusted and standardized in batch mode, concentrations of 6.67E9 CFU/ml were reached after 27 hours of fermentation and a subsequent noticeable decrease was observed associated with a basification of the culture medium. By applying fed-batch and continuous strategies, significant increases in yields were achieved, but with similar concentration levels, which involved the design of several production scenarios based on the availability of equipment usage time and volume of required batch.

Keywords: biofertilizer, liquid fermentation, Rhizobium sp., standardization of processes

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Authors: Prema Basargekar

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Facilitating the subject ‘Entrepreneurship Education’ in higher education, such as management studies, can be exhilarating as well as challenging. It is a multi-disciplinary and ever-evolving subject. Capturing entrepreneurship as a phenomenon in a holistic manner is a daunting task as it requires covering various dimensions such as new ideas generation, entrepreneurial traits, business opportunities scanning, the role of policymakers, value creation, etc., to name a few. Implicit entrepreneurship theory and effectuation are two different theories that focus on engaging the participants to create content by using their own experiences, perceptions, and belief systems. It helps in understanding the phenomenon holistically. The assumption here is that all of us are part of the entrepreneurial ecosystem, and effective learning can come through active engagement and peer learning by all the participants together. The present study is an attempt to use these theories in the class assignment given to the students at the beginning of the course to build the course content and understand entrepreneurship as a phenomenon in a better way through peer learning. The assignment was given to three batches of MBA post-graduate students doing the program in one of the private business schools in India. The subject of ‘Entrepreneurship Management’ is facilitated in the third trimester of the first year. At the beginning of the course, the students were given the assignment to submit a brief write-up/ collage/picture/poem or in any other format about “What entrepreneurship means to you?” They were asked to give their candid opinions about entrepreneurship as a phenomenon as they perceive it. Nearly 156 students doing post-graduate MBA submitted the assignment. These assignments were further used to find answers to two research questions. – 1) Are students able to use divergent and innovative forms to express their opinions, such as poetry, illustrations, videos, etc.? 2) What are various dimensions of entrepreneurship which are emerging to understand the phenomenon in a better way? The study uses the Brawn and Clark framework of reflective thematic analysis for qualitative analysis. The study finds that students responded to this assignment enthusiastically and expressed their thoughts in multiple ways, such as poetry, illustration, personal narrative, videos, etc. The content analysis revealed that there could be seven dimensions to looking at entrepreneurship as a phenomenon. They are 1) entrepreneurial traits, 2) entrepreneurship as a journey, 3) value creation by entrepreneurs in terms of economic and social value, 4) entrepreneurial role models, 5) new business ideas and innovations, 6) personal entrepreneurial experiences and aspirations, and 7) entrepreneurial ecosystem. The study concludes that an implicit approach to facilitate entrepreneurship education helps in understanding it as a live phenomenon. It also encourages students to apply divergent and convergent thinking. It also helps in triggering new business ideas or stimulating the entrepreneurial aspirations of the students. The significance of the study lies in the application of implicit theories in the classroom to make higher education more engaging and effective.

Keywords: co-creation of content, divergent thinking, entrepreneurship education, implicit theory

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Authors: Z. Kassab, A. Aboulkas, A. Barakat, M. El Achaby

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The red algae are available enormously around the world and their exploitation for the production of agar product has become as an important industry in recent years. However, this industrial processing of red algae generated a large quantity of solid fibrous wastes, which constitute a source of a serious environmental problem. For this reason, the exploitation of this solid waste would help to i) produce new value-added materials and ii) to improve waste disposal from environment. In fact, this solid waste can be fully utilized for the production of cellulose microfibers and nanocrystals because it consists of large amount of cellulose component. For this purpose, the red algae waste was chemically treated via alkali, bleaching and acid hydrolysis treatments with controlled conditions, in order to obtain pure cellulose microfibers and cellulose nanocrystals. The raw product and the as-extracted cellulosic materials were successively characterized using serval analysis techniques, including elemental analysis, X-ray diffraction, thermogravimetric analysis, infrared spectroscopy and transmission electron microscopy. As an application, the as extracted cellulose nanocrystals were used as nanofillers for the production of polymer-based composite films with improved thermal and tensile properties. In these composite materials, the adhesion properties and the large number of functional groups that are presented in the CNC’s surface and the macromolecular chains of the polymer matrix are exploited to improve the interfacial interactions between the both phases, improving the final properties. Consequently, the high performances of these composite materials can be expected to have potential in packaging material applications.

Keywords: cellulose nanowhiskers, food packaging, polymer composites, red algae waste

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Authors: Jihane Saad, Thomas Lendormi, Caroline Le Marechal, Anne-marie Pourcher, Céline Druilhe, Jean-louis Lanoiselle

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Agricultural anaerobic digestion consists in the conversion of animal slurry and manure into biogas and digestate. They need, however, to be treated at 70 ºC during 60 min before anaerobic digestion according to the European regulation (EC n°1069/2009 & EU n°142/2011). The impact of such heat treatment on the outcome of bacteria has been poorly studied up to now. Moreover, a recent study¹ has shown that enterococci and clostridia are still detected despite the application of such thermal treatment, questioning the relevance of this approach for the hygienisation of digestate. The aim of this study is to establish the heat inactivation kinetics of two species of enterococci (Enterococcus faecalis and Enterococcus faecium) and two species of clostridia (Clostridioides difficile and Clostridium novyi as a non-toxic model for Clostridium botulinum of group III). A pure culture of each strain was prepared in a specific sterile medium at concentration of 10⁴ – 10⁷ MPN / mL (Most Probable number), depending on the bacterial species. Bacterial suspensions were then filled in sterilized capillary tubes and placed in a water or oil bath at desired temperature for a specific period of time. Each bacterial suspension was enumerated using a MPN approach, and tests were repeated three times for each temperature/time couple. The inactivation kinetics of the four indicator bacteria is described using the Weibull model and the classical Bigelow model of first-order kinetics. The Weibull model takes biological variation, with respect to thermal inactivation, into account and is basically a statistical model of distribution of inactivation times as the classical first-order approach is a special case of the Weibull model. The heat treatment at 70 ºC / 60 min contributes to a reduction greater than 5 log10 for E. faecium and E. faecalis. However, it results only in a reduction of about 0.7 log10 for C. difficile and an increase of 0.5 log10 for C. novyi. Application of treatments at higher temperatures is required to reach a reduction greater or equal to 3 log10 for C. novyi (such as 30 min / 100 ºC, 13 min / 105 ºC, 3 min / 110 ºC, and 1 min / 115 ºC), raising the question of the relevance of the application of heat treatment at 70 ºC / 60 min for these spore-forming bacteria. To conclude, the heat treatment (70 ºC / 60 min) defined by the European regulation is sufficient to inactivate non-sporulating bacteria. Higher temperatures (> 100 ºC) are required as far as spore-forming bacteria concerns to reach a 3 log10 reduction (sporicidal activity).

Keywords: heat treatment, enterococci, clostridia, inactivation kinetics

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Authors: Kaushal Kishore

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Immense amount of imported fuels are used in Fiji for electricity generation, transportation and for carrying out miscellaneous household work. To alleviate its dependency on fossil fuel, paramount importance has been given to instigate the utilization of renewable energy sources for power generation and to reduce the environmental dilapidation. Amongst the many renewable energy sources, wind has been considered as one of the best identified renewable sources that are comprehensively available in Fiji. In this study the wind resource assessment for three locations in Rakiraki, Fiji has been carried out. The wind resource estimation at Rokavukavu, Navolau and at Tuvavatu has been analyzed. The average wind speed at 55 m above ground level (a.g.l) at Rokavukavu, Navolau, and Tuvavatu sites are 5.91 m/s, 8.94 m/s and 8.13 m/s with the turbulence intensity of 14.9%, 17.1%, and 11.7% respectively. The moment fitting method has been used to estimate the Weibull parameter and the power density at each sites. A high resolution wind resource map for the three locations has been developed by using Wind Atlas Analysis and Application Program (WAsP). The results obtained from WAsP exhibited good wind potential at Navolau and Tuvavatu sites. A wind farm has been proposed at Navolau and Tuvavatu site that comprises six Vergnet 275 kW wind turbines at each site. The annual energy production (AEP) for each wind farm is estimated and an economic analysis is performed. The economic analysis for the proposed wind farms at Navolau and Tuvavatu sites showed a payback period of 5 and 6 years respectively.

Keywords: annual energy production, Rakiraki Fiji, turbulence intensity, Weibull parameter, wind speed, Wind Atlas Analysis and Application Program

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Authors: Sandhra M. Pillai

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This article examines the relevance, difficulties, and potential applications of DNA analysis in the criminal justice system. A potent tool for connecting suspects to crime sites, clearing the innocent of wrongdoing, and resolving cold cases, DNA analysis has transformed forensic investigations. The scientific foundations of DNA analysis, including DNA extraction, sequencing, and statistical analysis, are covered in the article. To guarantee accurate and trustworthy findings, it also discusses the significance of quality assurance procedures, chain of custody, and DNA sample storage. DNA analysis has significantly advanced science, but it also brings up substantial moral and legal issues. To safeguard individual rights and uphold public confidence, privacy concerns, possible discrimination, and abuse of DNA information must be properly addressed. The paper also emphasises the effects of the criminal justice system on people and communities while highlighting the necessity of equity, openness, and fair access to DNA testing. The essay describes the obstacles and future directions for DNA analysis. It looks at cutting-edge technology like next-generation sequencing, which promises to make DNA analysis quicker and more affordable. To secure the appropriate and informed use of DNA evidence, it also emphasises the significance of multidisciplinary collaboration among scientists, law enforcement organisations, legal experts, and policymakers. In conclusion, DNA analysis has enormous potential for improving the course of criminal justice. We can exploit the potential of DNA technology while respecting the ideals of justice, fairness, and individual rights by navigating the ethical, legal, and societal issues and encouraging discussion and collaboration.

Keywords: DNA analysis, DNA evidence, reliability, validity, legal frame, admissibility, ethical considerations, impact, future direction, challenges

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Authors: M. Zayoud, S. Oueida, S. Ionescu, P. AbiChar

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Background: Wireless sensor network is encompassed of diversified tools of information technology, which is widely applied in a range of domains, including military surveillance, weather forecasting, and earthquake forecasting. Strengthened grounds are always developed for wireless sensor networks, which usually emerges security issues during professional application. Thus, essential technological tools are necessary to be assessed for secure aggregation of data. Moreover, such practices have to be incorporated in the healthcare practices that shall be serving in the best of the mutual interest Objective: Aggregation of encrypted data has been assessed through homomorphic stream cipher to assure its effectiveness along with providing the optimum solutions to the field of healthcare. Methods: An experimental design has been incorporated, which utilized newly developed cipher along with CPU-constrained devices. Modular additions have also been employed to evaluate the nature of aggregated data. The processes of homomorphic stream cipher have been highlighted through different sensors and modular additions. Results: Homomorphic stream cipher has been recognized as simple and secure process, which has allowed efficient aggregation of encrypted data. In addition, the application has led its way to the improvisation of the healthcare practices. Statistical values can be easily computed through the aggregation on the basis of selected cipher. Sensed data in accordance with variance, mean, and standard deviation has also been computed through the selected tool. Conclusion: It can be concluded that homomorphic stream cipher can be an ideal tool for appropriate aggregation of data. Alongside, it shall also provide the best solutions to the healthcare sector.

Keywords: aggregation, cipher, homomorphic stream, encryption

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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