Search results for: optimizing%20conditions

Authors: Salma E. Ahmed

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Since the mid 50’s, enormous attention has been paid towards nanocarriers and their applications in drug and gene delivery. Among these vesicles, liposomes and micelles have been heavily investigated due to their many advantages over other types. Liposomes, for instance, are mostly distinguished by their ability to encapsulate hydrophobic, hydrophilic and amphiphilic drugs. Micelles, on the other hand, are self-assembled shells of lipids, amphiphilic or oppositely charged block copolymers that, once exposed to aqueous media, can entrap hydrophobic agents, and possess prolonged circulation in the bloodstream. Both carriers are considered compatible and biodegradable. Nevertheless, they have limited stabilities, chemical versatilities, and drug encapsulation efficiencies. In order to overcome these downsides, strategies for optimizing a novel drug delivery system that has the architecture of liposomes and polymeric characteristics of micelles have been evolved. Polymersomes are vehicles with fluidic cores and hydrophobic shells that are protected and isolated from the aqueous media by the hydrated hydrophilic brushes which give the carrier its distinctive polymeric bilayer shape. Similar to liposomes, this merit enables the carrier to encapsulate a wide range of agents, despite their affinities and solubilities in water. Adding to this, the high molecular weight of the amphiphiles that build the body of the polymersomes increases their colloidal and chemical stabilities and reduces the permeability of the polymeric membranes, which makes the vesicles more protective to the encapsulated drug. These carriers can also be modified in ways that make them responsive when targeted or triggered, by manipulating their composition and attaching moieties and conjugates to the body of the carriers. These appealing characteristics, in addition to the ease of synthesis, gave the polymersomes greater potentials in the area of drug delivery. Thus, their design and characterization, in comparison with liposomes and micelles, are briefly reviewed in this work.

Keywords: controlled release, liposomes, micelles, polymersomes, targeting

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Authors: Parmeet Kaur, Nighat Yaseen Sofi, Shakti Kumar Gupta, Veena Pandey, Rajvaedhan Azad

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Nutritional status and prevailing blood glucose level trends amongst hospitalized patients has been linked to clinical outcome. Therefore, the present study was undertaken to assess hospitalized Diabetic Eye Disease (DED) patients' anthropometric and dietary intake trends. DED patients with type 1 or 2 diabetes > 20 years were enrolled. Actual food intake was determined by weighed food record method. Mifflin St Joer predictive equation multiplied by a combined stress and activity factor of 1.3 was applied to estimate caloric needs. A questionnaire was further administered to obtain reasons of inadequate dietary intake. Results indicated validity of joint analyses of body mass index in combination with waist circumference for clinical risk prediction. Dietary data showed a significant difference (p < 0.0005) between average daily caloric and carbohydrate intake and actual daily caloric and carbohydrate needs. Mean fasting and post-prandial plasma glucose levels were 150.71 ± 72.200 mg/dL and 219.76 ± 97.365 mg/dL, respectively. Improvement in food delivery systems and nutrition educations were indicated for reducing plate waste and to enable better understanding of dietary aspects of diabetes management. A team approach of nurses, physicians and other health care providers is required besides the expertise of dietetics professional. To conclude, findings of the present study will be useful in planning nutritional care process (NCP) for optimizing glucose control as a component of quality medical nutrition therapy (MNT) in hospitalized DED patients.

Keywords: nutritional status, diabetic eye disease, nutrition care process, medical nutrition therapy

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Authors: Shirin Ghatrehsamani

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Higher efficiency and lower environmental impact are the consequence of using advanced technology in farming. They also help to decrease yield variability by diminishing weather variability impact, optimizing nutrient and pest management as well as reducing competition from weeds. A better understanding of the pros and cons of applying technology and finding the main reason for preventing the utilization of the technology has a significant impact on developing technology adoption among farmers and producers in the digital agriculture era. The results from two surveys carried out in 2019 and 2021 were used to investigate whether the crop types had an impact on the willingness to utilize technology on the farms. The main focus of the questionnaire was on utilizing precision agriculture (PA) technologies among farmers in some parts of the united states. Collected data was analyzed to determine the practical application of various technologies. The survey results showed more similarities in the main reason not to use PA between the two crop types, but the present application of using technology in specialty crops is generally five times larger than in row crops. GPS receiver applications were reported similar for both types of crops. Lack of knowledge and high cost of data handling were cited as the main problems. The most significant difference was among using variable rate technology, which was 43% for specialty crops while was reported 0% for row crops. Pest scouting and mapping were commonly used for specialty crops, while they were rarely applied for row crops. Survey respondents found yield mapping, soil sampling map, and irrigation scheduling were more valuable for specialty crops than row crops in management decisions. About 50% of the respondents would like to share the PA data in both types of crops. Almost 50 % of respondents got their PA information from retailers in both categories, and as the second source, using extension agents were more common in specialty crops than row crops.

Keywords: precision agriculture, smart farming, digital agriculture, technology adoption

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Authors: M. Johnson, R. Faggian, V. Sposito

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A participatory and engaged approach is key in connecting agricultural managers to sustainable agricultural systems to support and optimize production in Victoria’s food bowl. A sustainable intensification (SI) approach is well documented globally, but participation rates amongst Victorian farmers is fragmentary, and key outcomes and implementation strategies are poorly understood. Improvement in decision-support management tools and a greater understanding of the productivity gains available upon implementation of SI is necessary. This paper reviews the current understanding and uptake of SI practices amongst farmers in one of Victoria’s premier food producing regions, the Goulburn Broken; and it spatially analyses the potential for this region to adapt to climate change and optimize food production. A Geographical Information Systems (GIS) approach is taken to develop an interactive decision-support tool that can be accessible to on-ground agricultural managers. The tool encompasses multiple criteria analysis (MCA) that identifies factors during the construction phase of the tool, using expert witnesses and regional knowledge, framed within an Analytical Hierarchy Process. Given the complexities of the interrelations between each of the key outcomes, this participatory approach, in which local realities and factors inform the key outcomes and help to strategies for a particular region, results in a robust strategy for sustainably intensifying production in key food producing regions. The creation of an interactive, locally embedded, decision-support management and education tool can help to close the gap between farmer knowledge and production, increase on-farm adoption of sustainable farming strategies and techniques, and optimize farm productivity.

Keywords: agriculture, decision-support management tool, Geographic Information System, GIS, sustainable intensification

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Authors: Shyaka Eugene

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The efficient and safe demolition of structures is a critical challenge in civil engineering and construction. This study focuses on the development of optimal demolition strategies by investigating the crack propagation behavior in beams induced by soundless cracking agents. It is commonly used in controlled demolition and has gained prominence due to its non-explosive and environmentally friendly nature. This research employs a comprehensive experimental and computational approach to analyze the crack initiation, propagation, and eventual failure in beams subjected to soundless cracking agents. Experimental testing involves the application of various cracking agents under controlled conditions to understand their effects on the structural integrity of beams. High-resolution imaging and strain measurements are used to capture the crack propagation process. In parallel, numerical simulations are conducted using advanced finite element analysis (FEA) techniques to model crack propagation in beams, considering various parameters such as cracking agent composition, loading conditions, and beam properties. The FEA models are validated against experimental results, ensuring their accuracy in predicting crack propagation patterns. The findings of this study provide valuable insights into optimizing demolition strategies, allowing engineers and demolition experts to make informed decisions regarding the selection of cracking agents, their application techniques, and structural reinforcement methods. Ultimately, this research contributes to enhancing the safety, efficiency, and sustainability of demolition practices in the construction industry, reducing environmental impact and ensuring the protection of adjacent structures and the surrounding environment.

Keywords: expansion pressure, energy release rate, soundless chemical demolition agent, crack propagation

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Authors: Mailin Misson, Bo Jin, Sheng Dai, Hu Zhang

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Advances in biotechnology have witnessed a growing interest in enzyme applications for the development of green and sustainable bio processes. While known as powerful bio catalysts, enzymes are no longer of economic value when extended to large commercialization. Alternatively, immobilization technology allows enzyme recovery and continuous reuse which subsequently compensates high operating costs. Employment of enzymes on nano structured materials has been recognized as a promising approach to enhance enzyme catalytic performances. High porosity, inter connectivity and self-assembling behaviors endow nano fibers as exciting candidate for enzyme carrier in bio reactor systems. In this study, nano fibers were successfully fabricated via electro spinning system by optimizing the polymer concentration (10-30 %, w/v), applied voltage (10-30 kV) and discharge distance (11-26 cm). Microscopic images have confirmed the quality as homogeneous and good fiber alignment. The nano fibers surface was modified using strong oxidizing agent to facilitate bio molecule binding. Bovine serum albumin and β-galactosidase enzyme were employed as model bio catalysts and immobilized onto the oxidized surfaces through covalent binding. Maximum enzyme adsorption capacity of the modified nano fibers was 3000 mg/g, 3-fold higher than the unmodified counterpart (1000 mg/g). The highest immobilization yield was 80% and reached the saturation point at 2 mg/ml of enzyme concentration. The results indicate a significant increase of activity retention by the enzyme-bound modified nano fibers (80%) as compared to the nascent one (60%), signifying excellent enzyme-nano carrier bio compatibility. The immobilized enzyme was further used for the bio conversion of dairy wastes into value-added products. This study demonstrates great potential of acid-modified electrospun polystyrene nano fibers as enzyme carriers.

Keywords: immobilization, enzyme, nanocarrier, nanofibers

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Authors: Alireza Vahid, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh, Thomas Dorin

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Aluminum is the preferred material for lightweight applications and its alloys are constantly improving. The high strength 7xxx alloys have been extensively used for structural components in aerospace and automobile industries for the past 50 years. In the next decade, a great number of airplanes will be retired, providing an obvious source of valuable used metals and great demand for cost-effective methods to re-use these alloys. The design of proper aerospace alloys is primarily based on optimizing strength and ductility, both of which can be improved by controlling the additional alloying elements as well as heat treatment conditions. In this project, we explore the design of high-performance alloys with 7xxx as a base material. These designed alloys have to be optimized and improved to compare with modern 7xxx-series alloys and to remain competitive for aircraft manufacturing. Aerospace alloys are extremely complex with multiple alloying elements and numerous processing steps making optimization often intensive and costly. In the present study, we used Bayesian optimization algorithm, a well-known adaptive design strategy, to optimize this multi-variable system. An Al alloy was proposed and the relevant heat treatment schedules were optimized, using the tensile yield strength as the output to maximize. The designed alloy has a maximum yield strength and ultimate tensile strength of more than 730 and 760 MPa, respectively, and is thus comparable to the modern high strength 7xxx-series alloys. The microstructure of this alloy is characterized by electron microscopy, indicating that the increased strength of the alloy is due to the presence of a high number density of refined precipitates.

Keywords: aluminum alloys, Bayesian optimization, heat treatment, tensile properties

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Authors: Akram Khelaifia, Salah Guettala, Nesreddine Djafar Henni, Rachid Chebili

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Reinforced concrete shear walls are pivotal in protecting buildings from seismic forces by providing strength and stiffness. This study highlights the importance of strategically placing shear walls and optimizing the shear wall-to-floor area ratio in building design. Nonlinear analyses were conducted on an eight-story building situated in a high seismic zone, exploring various scenarios of shear wall positioning and ratios to floor area. Employing the performance-based seismic design (PBSD) approach, the study aims to meet acceptance criteria such as inter-story drift ratio and damage levels. The results indicate that concentrating shear walls in the middle of the structure during the design phase yields superior performance compared to peripheral distributions. Utilizing shear walls that fully infill the frame and adopting compound shapes (e.g., Box, U, and L) enhances reliability in terms of inter-story drift. Conversely, the absence of complete shear walls within the frame leads to decreased stiffness and degradation of shorter beams. Increasing the shear wall-to-floor area ratio in building design enhances structural rigidity and reliability regarding inter-story drift, facilitating the attainment of desired performance levels. The study suggests that a shear wall ratio of 1.0% is necessary to meet validation criteria for inter-story drift and structural damage, as exceeding this percentage leads to excessive performance levels, proving uneconomical as structural elements operate near the elastic range.

Keywords: nonlinear analyses, pushover analysis, shear wall, plastic hinge, performance level

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: scalable architectures, sustainability, application design, disruptive technology, machine learning and natural language processing, AI, social media platform, cloud computing, advanced networking and storage devices, advanced monitoring and metering infrastructure, climate change

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Authors: Anil Kumar Gupta, Dronadula Venkata Sai Praneeth, Brajesh Dubey, Arundhuti Devi, Suravi Kalita, Khanindra Sharma

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Increase in urbanization and industrialization have led to improve in the standard of living. However, at the same time, the challenges due to improper solid waste management are also increasing. Municipal Solid Waste management is considered as a vital step in the development of urban infrastructure. The present study focuses on developing a solid waste management plan for an urban area in a developing country. The current scenario of solid waste management practices at various urban bodies in India is summarized. Guwahati city in the northeastern part of the country and is also one of the targeted smart cities (under the governments Smart Cities program) was chosen as case study to develop and implement the solid waste management plan. The whole city was divided into various divisions and waste samples were collected according to American Society for Testing and Materials (ASTM) - D5231-92 - 2016 for each division in the city and a composite sample prepared to represent the waste from the entire city. The solid waste characterization in terms of physical and chemical which includes mainly proximate and ultimate analysis were carried out. Existing primary and secondary collection systems were studied and possibilities of enhancing the collection systems were discussed. The composition of solid waste for the overall city was found to be as: organic matters 38%, plastic 27%, paper + cardboard 15%, Textile 9%, inert 7% and others 4%. During the conference presentation, further characterization results in terms of Thermal gravimetric analysis (TGA), pH and water holding capacity will be discussed. The waste management options optimizing activities such as recycling, recovery, reuse and reduce will be presented and discussed.

Keywords: proximate, recycling, thermal gravimetric analysis (TGA), solid waste management

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Authors: M. Stewart, Ameer Al-Khaykan, J. M. Counsell

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Emissions are a consequence of electricity generation. A major option for low carbon generation, local energy systems featuring Combined Heat and Power with solar PV (CHPV) has significant potential to increase energy performance, increase resilience, and offer greater control of local energy prices while complementing the UK’s emissions standards and targets. Recent advances in dynamic modelling and simulation of buildings and clusters of buildings using the IDEAS framework have successfully validated a novel multi-vector (simultaneous control of both heat and electricity) approach to integrating the wide range of primary and secondary plant typical of local energy systems designs including CHP, solar PV, gas boilers, absorption chillers and thermal energy storage, and associated electrical and hot water networks, all operating under a single unified control strategy. Results from this work indicate through simulation that integrated control of thermal storage can have a pivotal role in optimizing system performance well beyond the present expectations. Environmental impact analysis and reporting of all energy systems including CHPV LES presently employ a static annual average carbon emissions intensity for grid supplied electricity. This paper focuses on establishing and validating CHPV environmental performance against conventional emissions values and assessment benchmarks to analyze emissions performance without and with an active thermal store in a notional group of non-domestic buildings. Results of this analysis are presented and discussed in context of performance validation and quantifying the reduced environmental impact of CHPV systems with active energy storage in comparison with conventional LES designs.

Keywords: CHPV, thermal storage, control, dynamic simulation

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Authors: Mateusz Frydrych

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The construction of diaphragm walls as excavation shoring as well as part of deep foundations is widely used in geotechnical engineering. Today's design challenges lie in the optimal dimensioning of the cross-section, which is demanded by technological considerations. Also in force is the issue of optimization and sustainable use of construction materials, including reduction of carbon footprint, which is currently a relevant challenge for the construction industry. The author presents the concept of an approach to achieving increased efficiency of diaphragm wall excavation shoring by using structural compression technology. The author proposes to implement prestressed tendons in a non-linear manner in the reinforcement cage. As a result bending moment is reduced, which translates into a reduction in the amount of steel needed in the section, a reduction in displacements, and a reduction in the scratching of the casing, including the achievement of better tightness. This task is rarely seen and has not yet been described in a scientific way in the literature. The author has developed a dynamic numerical model that allows the dimensioning of the cross-section of a prestressed shear wall, as well as the study of casing displacements and cross-sectional forces in any defined computational situation. Numerical software from the Sofistik - open source development environment - was used for the study, and models were validated in Plaxis software . This is an interesting idea that allows for optimizing the execution of construction works and reducing the required resources by using fewer materials and saving time. The author presents the possibilities of a prestressed diaphragm wall, among others, using. The example of a diaphragm wall working as a cantilever at the height of two underground floors without additional strutting or stability protection by using ground anchors. This makes the execution of the work more criminal for the contractor and, as a result, cheaper for the investor.

Keywords: prestressed diaphragm wall, Plaxis, Sofistik, innovation, FEM, optimisation

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Authors: Ahdab H. Mahdaly, Debajyoti Pati, Sharran Parkinson, Lee S. Duemer

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The importance of providing employed mothers with the right physical environment inside the home is not an easy task, especially when the culture is involved. This study examines the typical Saudi home as a personal, emotional, social and cultural setting, especially on the interactions between the physical design and perceived control of working mothers. However, owing to the scarcity of published literature on Saudi homes, American employed mothers were included in the study to provide a baseline. With the ongoing transformations in women’s role in Saudi Arabia, there is a perception that traditional home designs may not afford the appropriate sense of control inside the home. Saudi Arabia has numerous interacting layers of socio-cultural-religious forces that affect residential design, and understanding the moderating role of the Saudi home is vital to the ongoing national policy transition on women. The study investigated one narrow, albeit critical, influence of home design on ones sense of control – direct visual and physical accessibility between sets of rooms. Ten subjects, five Saudis and five American, examined visual and physical access between 171 room sets, and provided qualitative responses on how each access influences their sense of control. Three main themes emerged, with potential effects on control: 1- Openness, 2- Proximity, and 3- Separation. Data suggest that although the Saudi home is a substantially more complex setting than the American ones, a class of spaces that can be termed as ‘Neutral Rooms’ serving as cultural separators may represent the ideal solution for optimizing sense of control, without ignoring cultural-religious traditions, during the transition of the Saudi women.

Keywords: direct physical accessibility, home environment, sense of control, visual accessibility, working mothers

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Authors: Ramish, Farhan Khalique Awan

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Kinematic redundancy within the manipulators presents extended dexterity and manipulability to the manipulators. Redundant serial robotic manipulators are very popular in industries due to its competencies to keep away from singularities during normal operation and fault tolerance because of failure of one or more joints. Such fault tolerant manipulators are extraordinarily beneficial in applications where human interference for repair and overhaul is both impossible or tough; like in case of robotic arms for space programs, nuclear applications and so on. The design of this sort of fault tolerant serial 3 DoF manipulator is presented in this paper. This work was the extension of the author’s previous work of designing the simple 3R serial manipulator. This work is the realization of the previous design with optimizing the link lengths for incorporating the feature of fault tolerance. Various measures have been followed by the researchers to quantify the fault tolerance of such redundant manipulators. The fault tolerance in this work has been described in terms of the worst-case measure of relative manipulability that is, in fact, a local measure of optimization that works properly for certain configuration of the manipulators. An optimum fault tolerant Jacobian matrix has been determined first based on prescribed null space properties after which the link parameters have been described to meet the given Jacobian matrix. A solid model of the manipulator was then developed to realize the mathematically rigorous design. Further work was executed on determining the dynamic properties of the fault tolerant design and simulations of the movement for various trajectories have been carried out to evaluate the joint torques. The mathematical model of the system was derived via the Euler-Lagrange approach after which the same has been tested using the RoboAnalyzer© software. The results have been quite in agreement. From the CAD model and dynamic simulation data, the manipulator was fabricated in the workshop and Advanced Machining lab of NED University of Engineering and Technology.

Keywords: fault tolerant, Graham matrix, Jacobian, kinematics, Lagrange-Euler

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Authors: Sadman Durlov, Aditya Ganesh-Ram, Hamidreza Hekmatjou, Md Najmus Salehin, Nora Shayesteh Ameri

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In the field of additive manufacturing, tungsten stands out for its exceptional resistance to high temperatures, making it an ideal candidate for use in extreme conditions. However, its inherent brittleness and vulnerability to thermal cracking pose significant challenges to its manufacturability. This study explores the microstructural evolution of tungsten processed through layer-wise rolling in laser powder bed fusion additive manufacturing, utilizing a comprehensive approach that combines advanced simulation techniques with empirical research. We aim to uncover the complex processes of plastic deformation and microstructural transformations, with a particular focus on the dynamics of grain size, boundary evolution, and phase distribution. Our methodology employs a combination of simulation and experimental data, allowing for a detailed comparison that elucidates the key mechanisms influencing microstructural alterations during the rolling process. This approach facilitates a deeper understanding of the material's behavior under additive manufacturing conditions, specifically in terms of deformation and recrystallization. The insights derived from this research not only deepen our theoretical knowledge but also provide actionable strategies for refining manufacturing parameters to improve the tungsten components' mechanical properties and functional performance. By integrating simulation with practical experimentation, this study significantly enhances the field of materials science, offering a robust framework for the development of durable materials suited for challenging operational environments. Our findings pave the way for optimizing additive manufacturing techniques and expanding the use of tungsten across various demanding sectors.

Keywords: additive manufacturing, layer wise rolling, refractory materials, in-situ microstructure modifications

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Authors: E. Feizi Ashtiani, S. Jamshidi, M.H Niksokhan, A. Feizi Ashtiani

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Waste load allocation (WLA) policies may use multi-objective optimization methods to find the most appropriate and sustainable solutions. These usually intend to simultaneously minimize two criteria, total abatement costs (TC) and environmental violations (EV). If other criteria, such as inequity, need for minimization as well, it requires introducing more binary optimizations through different scenarios. In order to reduce the calculation steps, this study presents value index as an innovative decision making approach. Since the value index contains both the environmental violation and treatment costs, it can be maximized simultaneously with the equity index. It implies that the definition of different scenarios for environmental violations is no longer required. Furthermore, the solution is not necessarily the point with minimized total costs or environmental violations. This idea is testified for Haraz River, in north of Iran. Here, the dissolved oxygen (DO) level of river is simulated by Streeter-Phelps equation in MATLAB software. The WLA is determined for fish farms using multi-objective particle swarm optimization (MOPSO) in two scenarios. At first, the trade-off curves of TC-EV and TC-Inequity are plotted separately as the conventional approach. In the second, the Value-Equity curve is derived. The comparative results show that the solutions are in a similar range of inequity with lower total costs. This is due to the freedom of environmental violation attained in value index. As a result, the conventional approach can well be replaced by the value index particularly for problems optimizing these objectives. This reduces the process to achieve the best solutions and may find better classification for scenario definition. It is also concluded that decision makers are better to focus on value index and weighting its contents to find the most sustainable alternatives based on their requirements.

Keywords: waste load allocation (WLA), value index, multi objective particle swarm optimization (MOPSO), Haraz River, equity

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Authors: Jorge A. Cruz-Morales, Joel Vargas, Arlette A. Santiago, Mikhail A. Tlenkopatchev

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In industrial processes such as oil extraction and refining, products are handled or generated in the gas phase, which represents a challenge in terms of treatment and purification. During the past three decades, new scientific findings and technological advances in separation based on the use of membranes have led to simpler and more efficient gas separation processes, optimizing the use of energy and generating less pollution. This work reports the synthesis and ring-opening metathesis polymerization (ROMP) of new structural isomers based on norbornene dicarboximides bearing trifluoromethyl moieties, specifically N-2-trifluoromethylphenyl-exo,endo-norbornene-5,6-dicarboximide (2a) and N-3-trifluoromethylphenyl-exo,endo-norbornene-5,6-dicarboximide (2b), using tricyclohexylphosphine [1,3-bis(2,4,6-trimethylphenyl)-4,5-dihydroimidazol-2-ylidene][benzylidene] ruthenium dichloride (I), bis(tricyclohexylphosphine) benzylidene ruthenium (IV) dichloride (II), and bis(tricyclohexylphosphine) p-fluorophenylvinylidene ruthenium (II) dichloride (III). It was observed that the -CF3 moiety attached at the ortho position of the aromatic ring increases thermal and mechanical properties of the polymer, whereas meta substitution has the opposite effect. A comparative study of gas transportation in membranes, based on these fluorinated polynorbornenes, showed that -CF3 ortho substitution increases permeability of the polymer membrane as a consequence of the increase in both gas solubility and gas diffusion. In contrast, gas permeability coefficients of the meta-substituted polymer membrane are rather similar to those of that which is non-fluorinated; this can be attributed to a lower fractional free volume. The meta-substituted polymer membrane, besides showing the largest permselectivity coefficients of all the isomers studied here, was also found to have one of the largest permselectivity coefficients for separating H2/C3H6 into glassy polynorbornene dicarboximides.

Keywords: gas transport membranes, polynorbornene dicarboximide, ROMP, structural isomers

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Authors: Paul Lemarignier, Olivier Fiquet, Vincent Pateloup

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In line with the strong desire of nuclear energy players to have ever more effective products in terms of safety, research programs on E-ATF (Enhanced-Accident Tolerant Fuels) that are more resilient, particularly to the loss of coolant, have been launched in all countries with nuclear power plants. Among the multitude of solutions being developed internationally, carcinoembryonic antigen (CEA) and its partners are investigating a promising solution, which is the realization of CERMET (CERamic-METal) type fuel pellets made of a matrix of fissile material, uranium dioxide UO2, which has a low thermal conductivity, and a metallic phase with a high thermal conductivity to improve heat evacuation. Work has focused on the development by powder metallurgy of micro-structured CERMETs, characterized by networks of metallic phase embedded in the UO₂ matrix. Other types of macro-structured CERMETs, based on concepts proposed by thermal simulation studies, have been developed with a metallic phase with a specific geometry to optimize heat evacuation. This solution could not be developed using traditional processes, so additive manufacturing, which revolutionizes traditional design principles, is used to produce these innovative prototype concepts. At CEA Cadarache, work is first carried out on a non-radioactive surrogate material, alumina, in order to acquire skills and to develop the equipment, in particular the robocasting machine, an additive manufacturing technique selected for its simplicity and the possibility of optimizing the paste formulations. A manufacturing chain was set up, with the pastes production, the 3D printing of pellets, and the associated thermal post-treatment. The work leading to the first elaborations of macro-structured alumina/molybdenum CERMETs will be presented. This work was carried out with the support of Framatome and EdF.

Keywords: additive manufacturing, alumina, CERMET, molybdenum, nuclear safety

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Authors: Sarah Ullrich, Juliane Rolle, Christian Beste, Nicole Wolff

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Inhibition and cognitive flexibility are essential parts of executive functions in our daily lives, as they enable the avoidance of unwanted responses or selectively switch between mental processes to generate appropriate behavior. There is growing interest in improving inhibition and response selection through brief mindfulness-based meditations. Arguably, open-monitoring meditation (OMM) improves inhibitory and flexibility performance by optimizing cognitive control and information processing. Yet, the underlying neurophysiological processes have been poorly studied. Using the Simon-Go/Nogo paradigm, the present work examined the effect of a single 15-minute smartphone app-based OMM on inhibitory performance and response selection in meditation novices. We used both behavioral and neurophysiological measures (event-related potentials, ERPs) to investigate which subprocesses of response selection and inhibition are altered after OMM. The study was conducted in a randomized crossover design with N = 32 healthy adults. We thereby investigated Go and Nogo trials in the paradigm. The results show that as little as 15 minutes of OMM can improve response selection and inhibition at behavioral and neurophysiological levels. More specifically, OMM reduces the rate of false alarms, especially during Nogo trials regardless of congruency. It appears that OMM optimizes conflict processing and response inhibition compared to no meditation, also reflected in the ERP N2 and P3 time windows. The results may be explained by the meta control model, which argues in terms of a specific processing mode with increased flexibility and inclusive decision-making under OMM. Importantly, however, the effects of OMM were only evident when there was the prior experience with the task. It is likely that OMM provides more cognitive resources, as the amplitudes of these EKPs decreased. OMM novices seem to induce finer adjustments during conflict processing after familiarization with the task.

Keywords: EEG, inhibition, meditation, Simon Nogo

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Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

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Authors: Chukwuemeka Daniel Ezeliora, Chukwuebuka Lawrence Ezeliora

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The research focused on the appraisal of impact strength on mild steel cladding weld metal geometry. Over the years, poor welding has resulted in failures in engineering components, poor material quality, the collapse of welded materials, and failures in material strength. This is as a result of poor selection and combination of welding input process parameters. The application of the Tungsten Inert Gas (TIG) welding method with weld specimen of length 60; width 40, and thickness of 10 was used for the experiment. A butt joint method was prepared for the welding, and tungsten inert gas welding process was used to perform the twenty (20) experimental runs. A response surface methodology was used to model and to analyze the system. For an adequate polynomial approximation, the experimental design was used to collect the data. The key parameters considered in this work are welding current, gas flow rate, welding speed, and voltage. The range of the input process parameters was selected from the literature and the design. The steps followed to achieve the experimental design and results is the use of response surface method (RSM) implemented in central composite design (CCD) to generate the design matrix, to obtain quadratic model, and evaluate the interactions in the factors as well as optimizing the factors and the response. The result expresses that the best impact strength of the mild steel cladding weld metal geometry is 115.419 Joules. However, it was observed that the result of the input factors is; current 180.4 amp, voltage 23.99 volt, welding speed 142.7 mm.s and gas flow rate 10.8 lit/min as the optimum of the input process parameters. The optimal solution gives a guide for optimal impact strength of the weldment when welding with tungsten inert gas (TIG) under study.

Keywords: mild steel, impact strength, response surface, bead geometry, welding

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Yan Wang, Guowei Chen, Gang Wang

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Soil microbial diversity is one of the important parameters to assess the soil fertility and soil health, even stability of the ecosystem. In this paper, we aim to reveal the soil microbial difference in rhizosphere and root zone, even to pick the special biomarkers influenced by the long term tillage practices, which included four treatments of no-tillage, ridge tillage, continuous cropping with corn and crop rotation with corn and soybean. Here, high-throughput sequencing was performed to investigate the difference of bacteria in rhizosphere and root zone. The results showed a very significant difference of species richness between rhizosphere and root zone soil at the same crop rotation system (p < 0.01), and also significant difference of species richness was found between continuous cropping with corn and corn-soybean rotation treatment in the rhizosphere statement, no-tillage and ridge tillage in root zone soils. Implied by further beta diversity analysis, both tillage methods and crop rotation systems influence the soil microbial diversity and community structure in varying degree. The composition and community structure of microbes in rhizosphere and root zone soils were clustered distinctly by the beta diversity (p < 0.05). Linear discriminant analysis coupled with effect size (LEfSe) analysis of total taxa in rhizosphere picked more than 100 bacterial taxa, which were significantly more abundant than that in root zone soils, whereas the number of biomarkers was lower between the continuous cropping with corn and crop rotation treatment, the same pattern was found at no-tillage and ridge tillage treatment. Bacterial communities were greatly influenced by main environmental factors in large scale, which is the result of biological adaptation and acclimation, hence it is beneficial for optimizing agricultural practices.

Keywords: tillage methods, biomarker, biodiversity, rhizosphere

Procedia PDF Downloads 139

Authors: Chao-Ton Su, Li-Fei Chen

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The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: Rui Li, Min Wen, Kim Bang Salling

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For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euros per kilometer per year. In order to reduce such maintenance expenditures, this paper presents a mixed 0-1 linear mathematical model designed to optimize the predictive railway tamping activities for ballast track in the planning horizon of three to four years. The objective function is to minimize the tamping machine actual costs. The approach of the research is using the simple dynamic model for modelling condition-based tamping process and the solution method for finding optimal condition-based tamping schedule. Seven technical and practical aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality recovery on the track quality after tamping operation; (5) Tamping machine operation practices (6) tamping budgets and (7) differentiating the open track from the station sections. A Danish railway track between Odense and Fredericia with 42.6 km of length is applied for a time period of three and four years in the proposed maintenance model. The generated tamping schedule is reasonable and robust. Based on the result from the Danish railway corridor, the total costs can be reduced significantly (50%) than the previous model which is based on optimizing the number of tamping. The different maintenance strategies have been discussed in the paper. The analysis from the results obtained from the model also shows a longer period of predictive tamping planning has more optimal scheduling of maintenance actions than continuous short term preventive maintenance, namely yearly condition-based planning.

Keywords: integer programming, railway tamping, predictive maintenance model, preventive condition-based maintenance

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Authors: Moloud Torkandam

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Any cities must be designed and built in a way that minimizes their need for fossil fuel. Undoubtedly, the necessity of accepting this principle in the previous eras is undeniable with respect to the mode of constructions. Perhaps only due to the great diversity of materials and new technologies in the contemporary era, such a principle in buildings has been forgotten. The question of optimizing energy consumption in buildings has attracted a great deal of attention in many countries and, in this way, they have been able to cut down the consumption of energy up to 30 percent. The energy consumption is remarkably higher than global standards in our country, and the most important reason is the undesirable state of buildings from the standpoint of energy consumption. In addition to providing the means to protect the natural and fuel resources for the future generations, reducing the use of fossil energies may also bring about desirable outcomes such as the decrease in greenhouse gases (whose emissions cause global warming, the melting of polar ice, the rise in sea level and the climatic changes of the planet earth), the decrease in the destructive effects of contamination in residential complexes and especially urban environments and preparation for national self-sufficiency and the country’s independence and preserving national capitals. This research realize that in this modern day and age, living sustainably is a pre-requisite for ensuring a bright future and high quality of life. In acquiring this living standard, we will maintain the functions and ability of our environment to serve and sustain our livelihoods. Electricity is now an integral part of modern life, a basic necessity. In the provision of electricity, we are committed to respecting the environment by reducing the use of fossil fuels through the use of proven technologies that use local renewable and natural resources as its energy source. As far as this research concerned it is completely necessary to work on different type of energy producing such as solar and CPVT system.

Keywords: energy, photovoltaic, termal system, solar energy, CPVT

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Authors: Fanous Mohammadi, Majid H. Tangestani, Mohammad H. Tayebi

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This research aims to evaluate and compare Geographical Information Systems (GIS)-based fuzzy models for producing orogenic gold prospectivity maps in the Saqqez area, NW of Iran. Gold occurrences are hosted in sericite schist and mafic to felsic meta-volcanic rocks in this area and are associated with hydrothermal alterations that extend over ductile to brittle shear zones. The predictor maps, which represent the Pre-(Source/Trigger/Pathway), syn-(deposition/physical/chemical traps) and post-mineralization (preservation/distribution of indicator minerals) subsystems for gold mineralization, were generated using empirical understandings of the specifications of known orogenic gold deposits and gold mineral systems and were then pre-processed and integrated to produce mineral prospectivity maps. Five fuzzy logic operators, including AND, OR, Fuzzy Algebraic Product (FAP), Fuzzy Algebraic Sum (FAS), and GAMMA, were applied to the predictor maps in order to find the most efficient prediction model. Prediction-Area (P-A) plots and field observations were used to assess and evaluate the accuracy of prediction models. Mineral prospectivity maps generated by AND, OR, FAP, and FAS operators were inaccurate and, therefore, unable to pinpoint the exact location of discovered gold occurrences. The GAMMA operator, on the other hand, produced acceptable results and identified potentially economic target sites. The P-A plot revealed that 68 percent of known orogenic gold deposits are found in high and very high potential regions. The GAMMA operator was shown to be useful in predicting and defining cost-effective target sites for orogenic gold deposits, as well as optimizing mineral deposit exploitation.

Keywords: mineral prospectivity mapping, fuzzy logic, GIS, orogenic gold deposit, Saqqez, Iran

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Authors: Martin Georgiev, Milena Nanova, Damyan Damov

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Architects, engineers, and developers need to analyse and implement a wide spectrum of data in different formats, if they want to produce viable residential developments. Usually, this data comes from a number of different sources and is not well structured. The main objective of this research project is to provide parametric tools working with real geodesic data that can generate residential solutions. Various codes, regulations and design constraints are described by variables and prioritized. In this way, we establish a common workflow for architects, geodesists, and other professionals involved in the building and investment process. This collaborative medium ensures that the generated design variants conform to various requirements, contributing to a more streamlined and informed decision-making process. The quantification of distinctive characteristics inherent to typical residential structures allows a systematic evaluation of the generated variants, focusing on factors crucial to designers, such as daylight simulation, circulation analysis, space utilization, view orientation, etc. Integrating real geodesic data offers a holistic view of the built environment, enhancing the accuracy and relevance of the design solutions. The use of generative algorithms and parametric models offers high productivity and flexibility of the design variants. It can be implemented in more conventional CAD and BIM workflow. Experts from different specialties can join their efforts, sharing a common digital workspace. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the building investment during its entire lifecycle.

Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization

Procedia PDF Downloads 26

Authors: Mamoon Mousa Atout

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The industries of construction are in continuous growth not only in Middle East rejoin but almost all over the world. For the last fifteen years, big expansion and increase of different types of projects has been observed. Many infrastructural projects have been developed, high rise buildings, big shopping malls, power sub-stations, roads, bridges, schools, universities and developing many of new cities with full and complete facilities. The growth and enlargement of the mentioned developed projects has been accomplished through many international and local contracting organizations. Senior management of these organizations depend on their qualified and experienced team whom are aware of the implications of project management, construction management, engineering management and resource management during tendering till final completion of the project. This research aims to find out why reasons of principles of construction engineering and management are necessary for contracting firms and their managers. Principles of construction management help contracting organizations to accomplish and deliver projects without delay. This can be maintained by establishing guidelines’ details for updating the adopted system of construction management that they have through qualified and experienced project managers. The research focuses on benefits of other essential skills of projects planning, monitoring and control. Defining roles and responsibilities of contractor project managers during tendering and execution is a part of the investigated factors that will be analyzed. Other skills like optimizing and utilizing the obtainable project resources to deliver the project within time, cost and quality will be also investigated to find out how these factors are affecting the performance of contracting firms, projects managers and projects. The conclusion of the research will help senior management team and the contractors project managers about the benefits of implications and benefits construction management system and its effect upon the performance and knowledge of contract values that they have, and the optimal profit margin of the firm it.

Keywords: construction management, contracting firms, project managers, planning processes, roles and responsibilities

Procedia PDF Downloads 272