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Authors: Bahman Ghorashi

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The immense awareness of the global climate change has compelled traditional fossil fuel companies to develop strategies to reduce their carbon footprint and simultaneously consider the production of various sources of clean energy in order to mitigate the environmental impact of their operations. Similarly, supply chain issues, the scarcity of certain raw materials, energy costs as well as market needs, and changing consumer expectations have forced the traditional chemical industry to reexamine their time-honored modes of operation. This study examines how such transformative change might occur through the applications of agile principles as well as industry 4.0 technologies. Clearly, such a transformation is complex, costly, and requires a total commitment on the part of the top leadership and the entire management structure. Factors that need to be considered include organizational speed of change, a restructuring that would lend itself toward collaboration and the selling of solutions to customers’ problems, rather than just products, integrating ‘along’ as well as ‘across’ value chains, mastering change and uncertainty as well as a recognition of the importance of concept-to-cash time, i.e., the velocity of introducing new products to market, and the leveraging of people and information. At the same time, parallel to implementing such major shifts in the ethos, and the fabric of the organization, the change leaders should remain mindful of the companies’ DNA while incorporating the necessary DNA defying shifts. Furthermore, such strategic maneuvers should inevitably incorporate the managing of the upstream and downstream operations, harnessing future opportunities, preparing and training the workforce, implementing faster decision making and quick adaptation to change, managing accelerated response times, as well as forming autonomous and cross-functional teams. Moreover, the leaders should establish the balance between high-value solutions versus high-margin products, fully implement digitization of operations and, when appropriate, incorporate the latest relevant technologies, such as: AI, IIoT, ML, and immersive technologies. This study presents a summary of the agile principles and the relevant technologies and draws lessons from some of the best practices that are already implemented within the chemical industry in order to establish a roadmap to agility. Finally, the critical role of educational institutions in preparing the future workforce for Industry 4.0 is addressed.

Keywords: agile principles, immersive technologies, industry 4.0, workforce preparation

Procedia PDF Downloads 71

Authors: J. B. Athavale, Sean Clarke

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Introduction According to ancient Indian scriptures, a person’s consciousness includes the physical body, the vital energy sheath (Pranshakti), the mental body (which includes one’s feelings and emotions), the intellectual body (which refers to one’s decision-making ability), and the Soul (which is the God Principle that resides in every person). Apart from the physical body, all the other aspects are subtle in nature. In today’s world, much attention is given to one’s physical appearance and intellectual prowess. While there have been improvements in the attention given to mental health, its complete nature is not understood, and in many cultures, mental ill health is considered taboo and looked down upon. Regarding the spiritual well-being of a person, our spiritual research has shown that people’s understanding and efforts are mostly lacking and superficial as they do not conform to Universal Spiritual Principles. Also, true well-being occurs only when all the bodies are healthy. Methodology The spiritual research team at the University has found that the spiritual aspect of a person’s life affects all the physical, psychological, and intellectual bodies of a person resulting in ill health. Cleansing these bodies at a spiritual level is essential to regain well-being. Using Aura and Energy Scanners and advanced sixth sense, we studied what causes spiritual impurity in various bodies and how to cleanse them. We measured the spiritual vibrations of a person and how they get affected due to various daily activities. For example, we studied the difference in a person’s aura before and after applying chemical-based makeup vs. natural makeup. Key Findings From the various spiritual research experiments we conducted, we found that: • All our actions and our thoughts affect our various bodies and have the potential to change the aura for the better or worse. • When there is an increase in negative vibrations around a person, negative energies from the subtle dimension are more likely to affect a person. • As the person’s spiritual level increases, the positivity in their aura also increases, and it is much easier to cleanse the various bodies spiritually. • Spiritual practice is like a general spiritual tonic that increases the positivity in one’s aura. The benefits of this are that it leads to mental stability and intellectual clarity. • Spiritual healing remedies augment any spiritual practice to obtain a faster healing effect. Conclusion Taking care of oneself spiritually has a positive halo effect on all one’s bodies. Spiritual cleansing is required regularly if one wants to attain a state of well-being. Spiritual practice and spiritual healing lead to spiritual growth, stability of mind, and less stress and reactions. Spiritually purer people affect the environment positively, and there is less unrest and more harmony between man and nature.

Keywords: body, spirituality, cleansing, consciousness

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Authors: X. Li, Y. Liu, H. Wong, B. Pardoen, A. Fabbri, F. McGregor, E. Liu

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The target of this paper is to investigate how saturated poroelastic soils subject to freezing temperatures behave and how different boundary conditions can intervene and affect the thermo-hydro-mechanical (THM) responses, based on a particular but classical configuration of a finite homogeneous soil layer studied by Terzaghi. The essential relations on the constitutive behavior of a freezing soil are firstly recalled: ice crystal - liquid water thermodynamic equilibrium, hydromechanical constitutive equations, momentum balance, water mass balance, and the thermal diffusion equation, in general, non-linear case where material parameters are state-dependent. The system of equations is firstly linearized, assuming all material parameters to be constants, particularly the permeability of liquid water, which should depend on the ice content. Two analytical solutions solved by the classic Laplace transform are then developed, accounting for two different sets of boundary conditions. Afterward, the general non-linear equations with state-dependent parameters are solved using a commercial code COMSOL based on finite elements method to obtain numerical results. The validity of this numerical modeling is partially verified using the analytical solution in the limiting case of state-independent parameters. Comparison between the results given by the linearized analytical solutions and the non-linear numerical model reveals that the above-mentioned linear computation will always underestimate the liquid pore pressure and displacement, whatever the hydraulic boundary conditions are. In the nonlinear model, the faster growth of ice crystals, accompanying the subsequent reduction of permeability of freezing soil layer, makes a longer duration for the depressurization of water liquid and slower settlement in the case where the ground surface is swiftly covered by a thin layer of ice, as well as a bigger global liquid pressure and swelling in the case of the impermeable ground surface. Nonetheless, the analytical solutions based on linearized equations give a correct order-of-magnitude estimate, especially at moderate temperature variations, and remain a useful tool for preliminary design checks.

Keywords: chemical potential, cryosuction, Laplace transform, multiphysics coupling, phase transformation, thermodynamic equilibrium

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Authors: Vitalijus Leibenka

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After 2014 the world of Russia’s actions in annexing Crimea has seen a hybrid war that has helped Russia achieve its goals. The world and NATO nations have pointed out that hybrid action can help achieve not only military but also economic and political goals. One of the weapons of action in hybrid warfare is information warfare tools, the use of which helps to carry out actions in the context of hybrid warfare as a whole. In addition, information war tools can be used alone, over time and for long-term purposes. Although forms of information war, such as propaganda and disinformation, have been used in the past, in old conflicts and wars, new forms of information war have emerged as a result of technological development, making the dissemination of information faster and more efficient. The world understands that information is becoming a weapon, but not everyone understands that both information war and information warfare differ in their essence and full content. In addition, the damage and impact of the use of information war, which may have worse consequences than a brief military conflict, is underestimated. Lithuania is also facing various interpretations of the information war. Some believe that the information attack is an information war and the understanding of the information war is limited to a false message in the press. Others, however, deepen and explain the essence of the information war. Society has formed in such a way that not all people are able to assess the threats of information war, to separate information war from information attack. Recently, the Lithuanian government has been taking measures in the context of the information war, making decisions that allow the development of the activities of the state and state institutions in order to create defense mechanisms in the information war. However, this is happening rather slowly and incompletely. Every military conflict, related to Lithuania in one way or another, forces Lithuanian politicians to take up the theme of information warfare again. As a result, a national cyber security center is being set up, and Russian channels spreading lies are banned. However, there is no consistent development and continuous improvement of action against information threats. Although a sufficiently influential part of society (not a political part) helps to stop the spread of obscure information by creating social projects such as “Demaskuok” and “Laikykis ten su Andriumi tapinu”, it goes without saying that it will not become a key tool in the fight against information threats. Therefore, in order to achieve clean dissemination of information in Lithuania, full-fledged and substantial political decisions are necessary, the adoption of which would change the public perception of the information war, its damage, impact and actions that would allow to combat the spread. Political decisions should cover the educational, military, economic and political areas, which are one of the main and most important in the state, which would allow to fundamentally change the situation against the background of information war.

Keywords: information war, information warfare, hybrid war, hybrid warfare, NATO, Lithuania, Russia

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Maria Sofia Palagonia, Doriano Brogioli, Fabio La Mantia

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In the last decade, lithium has become an important raw material in various sectors, in particular for rechargeable batteries. Its production is expected to grow more and more in the future, especially for mobile energy storage and electromobility. Until now it is mostly produced by the evaporation of water from salt lakes, which led to a huge water consumption, a large amount of waste produced and a strong environmental impact. A new, clean and faster electrochemical technique to recover lithium has been recently proposed: electrochemical ion pumping. It consists in capturing lithium ions from a feed solution by intercalation in a lithium-selective material, followed by releasing them into a recovery solution; both steps are driven by the passage of a current. In this work, a new configuration of the electrochemical cell is presented, used to study and optimize the process of the intercalation of lithium ions through the hydrodynamic condition. Lithium Manganese Oxide (LiMn₂O₄) was used as a cathode to intercalate lithium ions selectively during the reduction, while Nickel Hexacyano Ferrate (NiHCF), used as an anode, releases positive ion. The effect of hydrodynamics on the process has been studied by conducting the experiments at various fluxes of the electrolyte through the electrodes, in terms of charge circulated through the cell, captured lithium per unit mass of material and overvoltage. The result shows that flowing the electrolyte inside the cell improves the lithium capture, in particular at low lithium concentration. Indeed, in Atacama feed solution, at 40 mM of lithium, the amount of lithium captured does not increase considerably with the flux of the electrolyte. Instead, when the concentration of the lithium ions is 5 mM, the amount of captured lithium in a single capture cycle increases by increasing the flux, thus leading to the conclusion that the slowest step in the process is the transport of the lithium ion in the liquid phase. Furthermore, an influence of the concentration of other cations in solution on the process performance was observed. In particular, the capturing of the lithium using a different concentration of NaCl together with 5 mM of LiCl was performed, and the results show that the presence of NaCl limits the amount of the captured lithium. Further studies can be performed in order to understand why the full capacity of the material is not reached at the highest flow rate. This is probably due to the porous structure of the material since the liquid phase is likely not affected by the convection flow inside the pores. This work proves that electrochemical ion pumping, with a suitable hydrodynamic design, enables the recovery of lithium from feed solutions at the lower concentration than the sources that are currently exploited, down to 1 mM.

Keywords: desalination battery, electrochemical ion pumping, hydrodynamic, lithium

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Authors: Suraj D. Khadka, Priyantha W. Jayawickrama

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In search of a sustainable construction material, geopolymer has been investigated for past decades to evaluate its advantage over conventional products. Synthesis of geopolymer requires a source of aluminosilicate mixed with sodium hydroxide and sodium silicate at different proportions to maintain a Si/Al molar ratio of 1-3 and Na/Al molar ratio of unity. A comprehensive geopolymer study was performed with Metakaolin and Class C Fly ash as primary aluminosilicate sources. Synthesized geopolymer was analyzed for time-dependent viscosity, setting period and strength at varying initial moisture content, curing temperature and humidity. Different concentration of Ca(OH)₂ and CaSO₄.2H₂O were added to vary the amount of calcium contained in synthesized geopolymer. Influence of calcium content in unconfined compressive strength behavior of geopolymer were analyzed. Finally, Scanning Electron Microscopy-Energy Dispersive Spectroscopy (SEM-EDS) was performed to investigate the hardened product. It was observed that fly ash based geopolymer had shortened setting time and faster increase in viscosity as compared to geopolymer synthesized from metakaolin. This was primarily attributed to higher calcium content resulting in formation of calcium silicate hydrates (CSH). SEM-EDS was performed to verify the presence of CSH phases. Spectral analysis of geopolymer prepared by addition of Ca(OH)₂ and CaSO₄.2H₂O indicated higher CSH phases at higher concentration. It was observed that lower concentration of added calcium favored strength gain in geopolymer. However, at higher calcium concentration, decrease in strength was observed. Strength variation was also observed with humidity at initial curing condition. At 100% humidity, geopolymer with added calcium presented higher strength compared to samples cured at ambient humidity condition (40%). Reduction in strength in these samples at lower humidity was primarily attributed to reduction in moisture content in specimen due to the formation of CSH phases and loss of moisture through evaporation. For low calcium content geopolymers, with increase in temperature, gain in strength was observed with maximum strength observed at 200 ˚C. However, samples with higher calcium content demonstrated severe cracking resulting in low strength at elevated temperatures.

Keywords: calcium silicate hydrates, geopolymer, humidity, Scanning Electron Microscopy-Energy Dispersive Spectroscopy, unconfined compressive strength

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Authors: Magali Mari, Misha Muller

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The present study’s objectives were to determine how diverse implicit stereotypes affect the processing of written information and linguistic inferential processes, such as presupposition accommodation. When reading a text, one constructs a representation of the described situation, which is then updated, according to new outputs and based on stereotypes inscribed within society. If the new output contradicts stereotypical expectations, the representation must be corrected, resulting in longer reading times. A similar process occurs in cases of linguistic inferential processes like presupposition accommodation. Presupposition accommodation is traditionally regarded as fast, automatic processing of background information (e.g., ‘Mary stopped eating meat’ is quickly processed as Mary used to eat meat). However, very few accounts have investigated if this process is likely to be influenced by domains of social cognition, such as implicit stereotypes. To study the effects of implicit stereotypes on presupposition accommodation, adults were recorded while they read sentences in French, combining two methods, an eye-tracking task and a classic self-paced reading task (where participants read sentence segments at their own pace by pressing a computer key). In one condition, presuppositions were activated with the French definite articles ‘le/la/les,’ whereas in the other condition, the French indefinite articles ‘un/une/des’ was used, triggering no presupposition. Using a definite article presupposes that the object has already been uttered and is thus part of background information, whereas using an indefinite article is understood as the introduction of new information. Two types of stereotypes were under examination in order to enlarge the scope of stereotypes traditionally analyzed. Study 1 investigated gender stereotypes linked to professional occupations to replicate previous findings. Study 2 focused on nationality-related stereotypes (e.g. ‘the French are seducers’ versus ‘the Japanese are seducers’) to determine if the effects of implicit stereotypes on reading are generalizable to other types of implicit stereotypes. The results show that reading is influenced by the two types of implicit stereotypes; in the two studies, the reading pace slowed down when a counter-stereotype was presented. However, presupposition accommodation did not affect participants’ processing of information. Altogether these results show that (a) implicit stereotypes affect the processing of written information, regardless of the type of stereotypes presented, and (b) that implicit stereotypes prevail over the superficial linguistic treatment of presuppositions, which suggests faster processing for treating social information compared to linguistic information.

Keywords: eye-tracking, implicit stereotypes, reading, social cognition

Procedia PDF Downloads 172

Authors: Jian Yu

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Carbo dioxide (CO2) from fossil fuel combustion is a prime green-house gas emission. It can be mitigated by microalgae through conventional photosynthesis. The algal oil is a feedstock of biodiesel, a carbon neutral liquid fuel for transportation. The conventional CO2 fixation, however, is quite slow and affected by the intermittent solar irradiation. It is also a technical challenge to reform the bio-oil into a drop-in liquid fuel that can be directly used in the modern combustion engines with expected performance. Here, an artificial photosynthesis system is presented to produce a biopolyester and liquid fuels from CO2, water, and solar power. In this green process, solar energy is captured using photovoltaic modules and converted into hydrogen as a stable energy source via water electrolysis. The solar hydrogen is then used to fix CO2 by Cupriavidus necator, a hydrogen-oxidizing bacterium. Under the autotrophic conditions, CO2 was reduced to glyceraldehyde-3-phosphate (G3P) that is further utilized for cell growth and biosynthesis of polyhydroxybutyrate (PHB). The maximum cell growth rate reached 10.1 g L-1 day-1, about 25 times faster than that of a typical bio-oil-producing microalga (Neochloris Oleoabundans) under stable indoor conditions. With nitrogen nutrient limitation, a large portion of the reduced carbon is stored in PHB (C4H6O2)n, accounting for 50-60% of dry cell mass. PHB is a biodegradable thermoplastic that can find a variety of environmentally friendly applications. It is also a platform material from which small chemicals can be derived. At a high temperature (240 - 290 oC), the biopolyester is degraded into crotonic acid (C4H6O2). On a solid phosphoric acid catalyst, PHB is deoxygenated via decarboxylation into a hydrocarbon oil (C6-C18) at 240 oC or so. Aromatics and alkenes are the major compounds, depending on the reaction conditions. A gasoline-grade liquid fuel (77 wt% oil) and a biodiesel-grade fuel (23 wt% oil) were obtained from the hydrocarbon oil via distillation. The formation routes of hydrocarbon oil from crotonic acid, the major PHB degradation intermediate, are revealed and discussed. This work shows a novel green process from which biodegradable plastics and high-grade liquid fuels can be directly produced from carbon dioxide, water and solar power. The productivity of the green polyester (5.3 g L-1 d-1) is much higher than that of microalgal oil (0.13 g L-1 d-1). Other technical merits of the new green process may include continuous operation under intermittent solar irradiation and convenient scale up in outdoor.

Keywords: bioplastics, carbon dioxide fixation, drop-in liquid fuels, green process

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Authors: Michael Hast

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Within their first year, infants can differentiate between objects based on their weight. By at least 5 years children hold consistent weight-related misconceptions about the physical world, such as that heavy things fall faster than lighter ones because of their weight. Such misconceptions are seen as a challenge for science education since they are often highly resistant to change through instruction. Understanding the time point of emergence of such ideas could, therefore, be crucial for early science pedagogy. The paper thus discusses two studies that jointly address the issue by examining young children’s search behaviour in hidden displacement tasks under consideration of relative object weight. In both studies, they were tested with a heavy or a light ball, and they either had information about one of the balls only or both. In Study 1, 88 toddlers aged 2 to 3½ years watched a ball being dropped into a curved tube and were then allowed to search for the ball in three locations – one straight beneath the tube entrance, one where the curved tube lead to, and one that corresponded to neither of the previous outcomes. Success and failure at the task were not impacted by weight of the balls alone in any particular way. However, from around 3 years onwards, relative lightness, gained through having tactile experience of both balls beforehand, enhanced search success. Conversely, relative heaviness increased search errors such that children increasingly searched in the location immediately beneath the tube entry – known as the gravity bias. In Study 2, 60 toddlers aged 2, 2½ and 3 years watched a ball roll down a ramp and behind a screen with four doors, with a barrier placed along the ramp after one of four doors. Toddlers were allowed to open the doors to find the ball. While search accuracy generally increased with age, relative weight did not play a role in 2-year-olds’ search behaviour. Relative lightness improved 2½-year-olds’ searches. At 3 years, both relative lightness and relative heaviness had a significant impact, with the former improving search accuracy and the latter reducing it. Taken together, both studies suggest that between 2 and 3 years of age, relative object weight is increasingly taken into consideration in navigating naïve physical concepts. In particular, it appears to contribute to the early emergence of misconceptions relating to object weight. This insight from developmental psychology research may have consequences for early science education and related pedagogy towards early conceptual change.

Keywords: conceptual development, early science education, intuitive physics, misconceptions, object weight

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Authors: Jineetkumar Gawad, Chandrakant Bonde

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Tuberculosis (TB) is a major worldwide concern whose control has been exacerbated by HIV, the rise of multidrug-resistance (MDR-TB) and extensively drug resistance (XDR-TB) strains of Mycobacterium tuberculosis. The interest for newer and faster acting antitubercular drugs are more remarkable than any time. To search potent compounds is need and challenge for researchers. Here, we tried to design lead for inhibition of Decaprenyl phosphoryl-β-D-ribose 2′-epimerase (DprE1) enzyme. Arabinose is an essential constituent of mycobacterial cell wall. DprE1 is a flavoenzyme that converts decaprenylphosphoryl-D-ribose into decaprenylphosphoryl-2-keto-ribose, which is intermediate in biosynthetic pathway of arabinose. Latter, DprE2 converts keto-ribose into decaprenylphosphoryl-D-arabinose. We had a selection of 23 compounds from azaindole series for computational study, and they were drawn using marvisketch. Ligands were prepared using Maestro molecular modeling interface, Schrodinger, v10.5. Common pharmacophore hypotheses were developed by applying dataset thresholds to yield active and inactive set of compounds. There were 326 hypotheses were developed. On the basis of survival score, ADRRR (Survival Score: 5.453) was selected. Selected pharmacophore hypotheses were subjected to virtual screening results into 1000 hits. Hits were prepared and docked with protein 4KW5 (oxydoreductase inhibitor) was downloaded in .pdb format from RCSB Protein Data Bank. Protein was prepared using protein preparation wizard. Protein was preprocessed, the workspace was analyzed using force field OPLS 2005. Glide grid was generated by picking single atom in molecule. Prepared ligands were docked with prepared protein 4KW5 using Glide docking. After docking, on the basis of glide score top-five compounds were selected, (5223, 5812, 0661, 0662, and 2945) and the glide docking score (-8.928, -8.534, -8.412, -8.411, -8.351) respectively. There were interactions of ligand and protein, specifically HIS 132, LYS 418, TRY 230, ASN 385. Pi-pi stacking was observed in few compounds with basic Imidazo [4,5-b] pyridine ring. We had basic azaindole ring in parent compounds, but after glide docking, we received compounds with Imidazo [4,5-b] pyridine as a basic ring. That might be the new lead in the process of drug discovery.

Keywords: DprE1 inhibitors, in silico drug designing, imidazo [4, 5-b] pyridine, lead, tuberculosis

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Authors: Abir O. El Sadik

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Introduction: Wound healing involves the interaction of multiple biological processes among different types of cells, intercellular matrix and specific signaling factors producing enhancement of cell proliferation of the epidermis over dermal granulation tissue. Several studies investigated multiple strategies to promote wound healing and to minimize infection and fluid losses. However, burn crisis, and its related morbidity and mortality are still elevated. The aim of the present study was to examine the effects of mesenchymal stem cells (MSCs) in accelerating wound healing and to compare the most efficient route of administration of MSCs, either intradermal or systemic injection, with focusing on the mechanisms producing epidermal and dermal cell regeneration. Material and methods: Forty-two adult male Sprague Dawley albino rats were divided into three equal groups (fourteen rats in each group): control group (group I); full thickness surgical skin wound model, Group II: Wound treated with systemic injection of MSCs and Group III: Wound treated with intradermal injection of MSCs. The healing ulcer was examined on day 2, 6, 10 and 15 for gross morphological evaluation and on day 10 and 15 for fluorescent, histological and immunohistochemical studies. Results: The wounds of the control group did not reach complete closure up to the end of the experiment. In MSCs treated groups, better and faster healing of wounds were detected more than the control group. Moreover, the intradermal route of administration of stem cells increased the rate of healing of the wounds more than the systemic injection. In addition, the wounds were found completely healed by the end of the fifteenth day of the experiment in all rats of the group injected intradermally. Microscopically, the wound areas of group III were hardly distinguished from the adjacent normal skin with complete regeneration of all skin layers; epidermis, dermis, hypodermis and underlying muscle layer. Fully regenerated hair follicles and sebaceous glands in the dermis of the healed areas surrounded by different arrangement of collagen fibers with a significant increase in their area percent were recorded in this group more than in other groups. Conclusion: MSCs accelerate the healing process of wound closure. The route of administration of MSCs has a great influence on wound healing as intradermal injection of MSCs was more effective in enhancement of wound healing than systemic injection.

Keywords: intradermal, mesenchymal stem cells, morphology, skin wound, systemic injection

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Authors: Muhammad Khairi bin Sulaiman

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The utilization of Building Information Modelling (BIM) in the construction industry has provided an opportunity for designers in the Architecture, Engineering and Construction (AEC) industry to proceed from the conventional method of using manual drafting to a way that creates alternative designs quickly, produces more accurate, reliable and consistent outputs. By using BIM Software, designers can create digital content that manipulates the use of data using the parametric model of BIM. With BIM software, more alternative designs can be created quickly and design problems can be explored further to produce a better design faster than conventional design methods. Generally, BIM is used as a documentation mechanism and has not been fully explored and utilised its capabilities as a design tool. Relative to the current issue, Modular Coordination (MC) design as a sustainable design practice is encouraged since MC design will reduce material wastage through standard dimensioning, pre-fabrication, repetitive, modular construction and components. However, MC design involves a complex process of rules and dimensions. Therefore, a tool is needed to make this process easier. Since the parameters in BIM can easily be manipulated to follow MC rules and dimensioning, thus, the integration of BIM software with MC design is proposed for architects during the design stage. With this tool, there will be an improvement in acceptance and practice in the application of MC design effectively. Consequently, this study will analyse and explore the function and customization of BIM objects and the capability of BIM software to expedite the application of MC design during the design stage for architects. With this application, architects will be able to create building models and locate objects within reference modular grids that adhere to MC rules and dimensions. The parametric modeling capabilities of BIM will also act as a visual tool that will further enhance the automation of the 3-Dimensional space planning modeling process. (Method) The study will first analyze and explore the parametric modeling capabilities of rule-based BIM objects, which eventually customize a reference grid within the rules and dimensioning of MC. Eventually, the approach will further enhance the architect's overall design process and enable architects to automate complex modeling, which was nearly impossible before. A prototype using a residential quarter will be modeled. A set of reference grids guided by specific MC rules and dimensions will be used to develop a variety of space planning and configuration. With the use of the design, the tool will expedite the design process and encourage the use of MC Design in the construction industry.

Keywords: building information modeling, modular coordination, space planning, customization, BIM application, MC space planning

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Authors: Samira Baghbanbari, A. B. P. Lever, Payam S. Shabestari, Donald Weaver

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Existing signal transmission models, although undoubtedly useful, have proven insufficient to explain the full complexity of information transfer within the central nervous system. The development of transformative models will necessitate a more comprehensive understanding of neuronal lipid membrane electrophysiology. Pursuant to this goal, the role of highly organized interfacial phospholipid-water layers emerges as a promising case study. A series of phospholipids in neural-glial gap junction interfaces as well as cholesterol molecules have been computationally modelled using high-performance density functional theory (DFT) calculations. Subsequent 'charge decomposition analysis' calculations have revealed a net transfer of charge from phospholipid orbitals through the organized interfacial water layer before ultimately finding its way to cholesterol acceptor molecules. The specific pathway of charge transfer from phospholipid via water layers towards cholesterol has been mapped in detail. Cholesterol is an essential membrane component that is overrepresented in neuronal membranes as compared to other mammalian cells; given this relative abundance, its apparent role as an electronic acceptor may prove to be a relevant factor in further signal transmission studies of the central nervous system. The timescales over which this electronic charge transfer occurs have also been evaluated by utilizing a system design that systematically increases the number of water molecules separating lipids and cholesterol. Memory loss through hydrogen-bonded networks in water can occur at femtosecond timescales, whereas existing action potential-based models are limited to micro or nanosecond scales. As such, the development of future models that attempt to explain faster timescale signal transmission in the central nervous system may benefit from our work, which provides additional information regarding fast timescale energy transfer mechanisms occurring through interfacial water. The study possesses a dataset that includes six distinct phospholipids and a collection of cholesterol. Ten optimized geometric characteristics (features) were employed to conduct binary classification through an artificial neural network (ANN), differentiating cholesterol from the various phospholipids. This stems from our understanding that all lipids within the first group function as electronic charge donors, while cholesterol serves as an electronic charge acceptor.

Keywords: charge transfer, signal transmission, phospholipids, water layers, ANN

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Authors: M. R. Vijayakumar, K. Priyanka, Ramoji Kosuru, Lakshmi, Sanjay Singh

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Trans resveratrol (RES) is a non-flavonoid poly-phenolic compound proved for its therapeutic and preventive effect against various types of cancer. However, the practical application of RES in cancer treatment is limited because of its higher dose (up to 7.5 g/day in humans), low biological half life, rapid metabolism and faster elimination in mammals. PEGylated core-shell type lipid polymer hybrid nanoparticles are the novel drug delivery systems for long circulation and improved anti cancer effect of its therapeutic payloads. Therefore, the main objective of this study is to extend the biological half life (long circulation) and improve the therapeutic efficacy of RES through core shell type of nanoparticles. D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS), a novel surfactant is applied for the preparation of PEGylated lipid polymer hybrid nanoparticles. The prepared nanoparticles were evaluated by various state of the art techniques such as dynamic light scattering (DLS) technique for particle size and zeta potential, TEM for shape, differential scanning calorimetry (DSC) for interaction analysis and XRD for crystalline changes of drug. Entrapment efficiency and invitro drug release were determined by ultracentrifugation method and dialysis bag method, respectively. Cancer cell viability studies were performed by MTT assay, respectively. Pharmacokinetic studies after i.v administration were performed in sprague dawley rats. The prepared NPs were found to be spherical in shape with smooth surfaces. Particle size and zeta potential of prepared NPs were found to be in the range of 179.2±7.45 to 266.8±9.61 nm and -0.63 to -48.35 mV, respectively. DSC revealed absence of potential interaction. XRD study revealed presence of amorphous form in nanoparticles. Entrapment efficiency was found to be 83.7 % and drug release was found to be in controlled manner. MTT assay showed low MEC and pharmacokinetic studies showed higher AUC of nanoformulaition than its pristine drug. All these studies revealed that the RES loaded PEG modified core-shell type lipid polymer hybrid nanoparticles can be an alternative tool for chemopreventive and therapeutic application of RES in cancer.

Keywords: trans resveratrol, cancer nanotechnology, long circulating nanoparticles, bioavailability enhancement, core shell nanoparticles, lipid polymer hybrid nanoparticles

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Authors: Mostafa Shahriari, Theophile Chaumont-Frelet, David Pardo

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Resistivity measurements are used to characterize the Earth’s subsurface. They are categorized into two different groups: (a) those acquired on the Earth’s surface, for instance, controlled source electromagnetic (CSEM) and Magnetotellurics (MT), and (b) those recorded with borehole logging instruments such as Logging-While-Drilling (LWD) devices. LWD instruments are mostly used for geo-steering purposes, i.e., to adjust dip and azimuthal angles of a well trajectory to drill along a particular geological target. Modern LWD tools measure all nine components of the magnetic field corresponding to three orthogonal transmitter and receiver orientations. In order to map the Earth’s subsurface and perform geo-steering, we invert measurements using a gradient-based method that utilizes the derivatives of the recorded measurements with respect to the inversion variables. For resistivity measurements, these inversion variables are usually the constant resistivity value of each layer and the bed boundary positions. It is well-known how to compute derivatives with respect to the constant resistivity value of each layer using semi-analytic or numerical methods. However, similar formulas for computing the derivatives with respect to bed boundary positions are unavailable. The main contribution of this work is to provide an adjoint-based formulation for computing derivatives with respect to the bed boundary positions. The key idea to obtain the aforementioned adjoint state formulations for the derivatives is to separate the tangential and normal components of the field and treat them differently. This formulation allows us to compute the derivatives faster and more accurately than with traditional finite differences approximations. In the presentation, we shall first derive a formula for computing the derivatives with respect to the bed boundary positions for the potential equation. Then, we shall extend our formulation to 3D Maxwell’s equations. Finally, by considering a 1D domain and reducing the dimensionality of the problem, which is a common practice in the inversion of resistivity measurements, we shall derive a formulation to compute the derivatives of the measurements with respect to the bed boundary positions using a 1.5D variational formulation. Then, we shall illustrate the accuracy and convergence properties of our formulations by comparing numerical results with the analytical derivatives for the potential equation. For the 1.5D Maxwell’s system, we shall compare our numerical results based on the proposed adjoint-based formulation vs those obtained with a traditional finite difference approach. Numerical results shall show that our proposed adjoint-based technique produces enhanced accuracy solutions while its cost is negligible, as opposed to the finite difference approach that requires the solution of one additional problem per derivative.

Keywords: inverse problem, bed boundary positions, electromagnetism, potential equation

Procedia PDF Downloads 157

Authors: E. Menga, S. Hernandez

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Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.

Keywords: frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber

Procedia PDF Downloads 244

Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

Procedia PDF Downloads 154

Authors: Olumuyiwa Ayoola Kokapi, Olugbenga Solomon Bello

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Dyes are organic compounds with complex aromatic molecular structure that resulted in fast colour on a substance. Dye effluent found in wastewater generated from the dyeing industries is one of the greatest contributors to water pollution. Groundnut hull (GH) is an agricultural material that constitutes waste in the environment. Environmental contamination by hazardous organic chemicals is an urgent problem, which is partially solved through adsorption technologies. The choice of groundnut hull was promised on the understanding that some materials of agricultural origin have shown potentials to act as Adsorbate for hazardous organic chemicals. The aim of this research is to evaluate the potential of groundnut hull to adsorb Crystal violet dye through kinetic, isotherm and thermodynamic studies. The prepared groundnut hulls was characterized using Brunauer, Emmett and Teller (BET), Fourier transform infrared (FTIR) and scanning electron microscopy (SEM). Operational parameters such as contact time, initial dye concentration, pH, and effect of temperature were studied. Equilibrium time for the adsorption process was attained in 80 minutes. Adsorption isotherms used to test the adsorption data were Langmuir and Freundlich isotherms model. Thermodynamic parameters such as ∆G°, ∆H°, and ∆S° of the adsorption processes were determined. The results showed that the uptake of dye by groundnut hulls occurred at a faster rate, corresponding to an increase in adsorption capacity at equilibrium time of 80 min from 0.78 to 4.45 mg/g and 0.77 to 4.45mg/g with an increase in the initial dye concentration from 10 to 50 mg/L for pH 3.0 and 8.0 respectively. High regression values obtained for pseudo-second-order kinetic model, sum of square error (SSE%) values along with strong agreement between experimental and calculated values of qe proved that pseudo second-order kinetic model fitted more than pseudo first-order kinetic model. The result of Langmuir and Freundlich model showed that the adsorption data fit the Langmuir model more than the Freundlich model. Thermodynamic study demonstrated the feasibility, spontaneous and endothermic nature of the adsorption process due to negative values of free energy change (∆G) at all temperatures and positive value of enthalpy change (∆H) respectively. The positive values of ∆S showed that there was increased disorderliness and randomness at the solid/solution interface of crystal violet dye and groundnut hulls. The present investigation showed that, groundnut hulls (GH) is a good low-cost alternative adsorbent for the removal of Crystal Violet (CV) dye from aqueous solution.

Keywords: adsorption, crystal violet dye, groundnut halls, kinetics

Procedia PDF Downloads 345

Authors: Ju-Hong Lee, Ching-Wei Liao

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An adaptive array beamformer is designed for automatically preserving the desired signals while cancelling interference and noise. Providing robustness against model mismatches and tracking possible environment changes calls for robust adaptive beamforming techniques. The design criterion yields the well-known generalized sidelobe canceller (GSC) beamformer. In practice, the knowledge of the desired steering vector can be imprecise, which often occurs due to estimation errors in the DOA of the desired signal or imperfect array calibration. In these situations, the SOI is considered as interference, and the performance of the GSC beamformer is known to degrade. This undesired behavior results in a reduction of the array output signal-to-interference plus-noise-ratio (SINR). Therefore, it is worth developing robust techniques to deal with the problem due to local scattering environments. As to the implementation of adaptive beamforming, the required computational complexity is enormous when the array beamformer is equipped with massive antenna array sensors. To alleviate this difficulty, a generalized sidelobe canceller (GSC) with partially adaptivity for less adaptive degrees of freedom and faster adaptive response has been proposed in the literature. Unfortunately, it has been shown that the conventional GSC-based adaptive beamformers are usually very sensitive to the mismatch problems due to local scattering situations. In this paper, we present an effective GSC-based beamformer against the mismatch problems mentioned above. The proposed GSC-based array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. We utilize the predefined steering vector and a presumed angle tolerance range to carry out the required estimation for obtaining an appropriate steering vector. A matrix associated with the direction vector of signal sources is first created. Then projection matrices related to the matrix are generated and are utilized to iteratively estimate the actual direction vector of the desired signal. As a result, the quiescent weight vector and the required signal blocking matrix required for performing adaptive beamforming can be easily found. By utilizing the proposed GSC-based beamformer, we find that the performance degradation due to the considered local scattering environments can be effectively mitigated. To further enhance the beamforming performance, a signal subspace projection matrix is also introduced into the proposed GSC-based beamformer. Several computer simulation examples show that the proposed GSC-based beamformer outperforms the existing robust techniques.

Keywords: adaptive antenna beamforming, local scattering, signal blocking, steering mismatch

Procedia PDF Downloads 84

Authors: S. Vivek, Sharad Sharan, R. Arvind, D. V. Praveen, J. Vigneshwar, S. Ajith, V. R. Sanal Kumar

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In this paper numerical studies have been carried out to examine the starting transient flow features of high-performance solid propellant rocket motors with different port geometries but with same propellant loading density. Numerical computations have been carried out using a 3D SST k-ω turbulence model. This code solves standard k-omega turbulence equations with shear flow corrections using a coupled second order implicit unsteady formulation. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations are employed. We have observed from the numerical results that in solid rocket motors with highly loaded propellants having divergent port geometry the hot igniter gases can create pre-ignition thrust oscillations due to flow unsteadiness and recirculation. Under these conditions the convective flux to the surface of the propellant will be enhanced, which will create reattachment point far downstream of the transition region and it will create a situation for secondary ignition and formation of multiple-flame fronts. As a result the effective time required for the complete burning surface area to be ignited comes down drastically giving rise to a high pressurization rate (dp/dt) in the second phase of starting transient. This in effect could lead to starting thrust oscillations and eventually a hard start of the solid rocket motor. We have also observed that the igniter temperature fluctuations will be diminished rapidly and will reach the steady state value faster in the case of solid propellant rocket motors with convergent port than the divergent port irrespective of the igniter total pressure. We have concluded that the thrust oscillations and unexpected thrust spike often observed in solid rockets with non-uniform ports are presumably contributed due to the joint effects of the geometry dependent driving forces, transient burning and the chamber gas dynamics forces. We also concluded that the prudent selection of the port geometry, without altering the propellant loading density, for damping the total temperature fluctuations within the motor is a meaningful objective for the suppression and control of instability and/or pressure/thrust oscillations often observed in solid propellant rocket motors with non-uniform port geometry.

Keywords: ignition transient, solid rockets, starting transient, thrust transient

Procedia PDF Downloads 420

Authors: Kaddour Fellague Mohammed

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The world has seen in recent years, significant developments affected various aspects of life and influenced the different types of institutions, thus was born a new world is a world of globalization, which dominated the scientific revolution and the tremendous technological developments, and that contributed to the re-formation of human resources in contemporary organizations, and made patterns new regulatory and at the same time raised and strongly values and new ideas, the organizations have become more flexible, and faster response to consumer and environmental conditions, and exceeded the problem of time and place in the framework of communication and human interaction and use of advanced information technology and adoption mainly mechanism in running its operations , focused on performance and based strategic thinking and approach in order to achieve its strategic goals high degrees of superiority and excellence, this new reality created an increasing need for a new type of human resources, quality aims to renew and aspire to be a strategic player in managing the organization and drafting of various strategies, think globally and act locally, to accommodate local variables in the international markets, which began organizations tend to strongly as well as the ability to work under different cultures. Human resources management of the most important management functions to focus on the human element, which is considered the most valuable resource of the Department and the most influential in productivity at all, that the management and development of human resources Tattabra a cornerstone in the majority of organizations which aims to strengthen the organizational capacity, and enable companies to attract and rehabilitation of the necessary competencies and are able to keep up with current and future challenges, human resources can contribute to and strongly in achieving the objectives and profit organization, and even expand more than contribute to the creation of new jobs to alleviate unemployment and achieve full operation, administration and human resources mean short optimal use of the human element is available and expected, where he was the efficiency and capabilities, and experience of this human element, and his enthusiasm for the work stop the efficiency and success in reaching their goals, so interested administration scientists developed the principles and foundations that help to make the most of each individual benefit in the organization through human resources management, these foundations start of the planning and selection, training and incentives and evaluation, which is not separate from each other, but are integrated with each other as a system systemic order to reach the efficient functioning of the human resources management and has been the organization as a whole in the context of development sustainable.

Keywords: configuration, training, development, human resources, operating

Procedia PDF Downloads 405

Authors: Sibashish Baksi, Ujjaini Sarkar, Sudeshna Saha

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In the present study, hydrolysis of Pinus roxburghi wood powder was carried out with Viscozyme, and kinetics of the hydrolysis has been investigated. Finely ground sawdust is submerged into 2% aqueous peroxide solution (pH=11.5) and pretreated through autoclaving, probe sonication, and alkaline peroxide pretreatment. Afterward, the pretreated material is subjected to hydrolysis. A chain of experiments was executed with delignified biomass (50 g/l) and varying enzyme concentrations (24.2–60.5 g/l). In the present study, 14.32 g/l of glucose, along with 7.35 g/l of xylose, have been recovered with a viscozyme concentration of 48.8 g/l and the same condition was treated as optimum condition. Additionally, thermal deactivation of viscozyme has been investigated and found to be gradually decreasing with escalated enzyme loading from 48.4 g/l (dissociation constant= 0.05 h⁻¹) to 60.5 g/l (dissociation constant= 0.02 h⁻¹). The hydrolysis reaction is a pseudo first-order reaction, and therefore, the rate of the hydrolysis can be expressed as a fractal-like kinetic equation that communicates between the product concentration and hydrolytic time t. It is seen that the value of rate constant (K) increases from 0.008 to 0.017 with augmented enzyme concentration from 24.2 g/l to 60.5 g/l. Greater value of K is associated with stronger enzyme binding capacity of the substrate mass. However, escalated concentration of supplied enzyme ensures improved interaction with more substrate molecules resulting in an enhanced de-polymerization of the polymeric sugar chains per unit time which eventually modifies the physiochemical structure of biomass. All fractal dimensions are in between 0 and 1. Lower the value of fractal dimension, more easily the biomass get hydrolyzed. It can be seen that with increased enzyme concentration from 24.2 g/l to 48.4 g/l, the values of fractal dimension go down from 0.1 to 0.044. This indicates that the presence of more enzyme molecules can more easily hydrolyze the substrate. However, an increased value has been observed with a further increment of enzyme concentration to 60.5g/l because of diffusional limitation. It is evident that the hydrolysis reaction system is a heterogeneous organization, and the product formation rate depends strongly on the enzyme diffusion resistances caused by the rate-limiting structures of the substrate-enzyme complex. Value of the rate constant increases from 1.061 to 2.610 with escalated enzyme concentration from 24.2 to 48.4 g/l. As the rate constant is proportional to Fick’s diffusion coefficient, it can be assumed that with a higher concentration of enzyme, a larger amount of enzyme mass dM diffuses into the substrate through the surface dF per unit time dt. Therefore, a higher rate constant value is associated with a faster diffusion of enzyme into the substrate. Regression analysis of time curves with various enzyme concentrations shows that diffusion resistant constant increases from 0.3 to 0.51 for the first two enzyme concentrations and again decreases with enzyme concentration of 60.5 g/l. During diffusion in a differential scale, the enzyme also experiences a greater resistance during diffusion of larger dM through dF in dt.

Keywords: viscozyme, glucose, fractal kinetics, thermal deactivation

Procedia PDF Downloads 88

Authors: Samantha Meyerholz

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MSKCC offers patients cutting edge cancer care with the highest quality standards. However, many patients and industry members do not realize that the operations of the Immunology Histology Lab (IHC) are the backbone for carrying out this mission. The IHC lab manufactures blocks and slides containing critical tissue samples that will be read by a Pathologist to diagnose and dictate a patient’s treatment course. The lab processes 200 requests daily, leading to the generation of approximately 2,000 slides and 1,100 blocks each day. Lab material is transported through labeling, cutting, staining and sorting manufacturing stations, while being managed by multiple techs throughout the space. The quality of the stain as well as wait times associated with processing requests, is directly associated with patients receiving rapid treatments and having a wider range of care options. This project aims to improve slide request turnaround time for rush and non-rush cases, while increasing the quality of each request filled (no missing slides or poorly stained items). Rush cases are to be filled in less than 24 hours, while standard cases are allotted a 48 hour time period. Reducing turnaround times enable patients to communicate sooner with their clinical team regarding their diagnosis, ultimately leading faster treatments and potentially better outcomes. Additional project goals included streamlining tech and material workflow, while reducing waste and increasing efficiency. This project followed a DMAIC structure with emphasis on lean and ergonomic principles that could be integrated into an evolving lab culture. Load times and batching processes were analyzed using process mapping, FMEA analysis, waste analysis, engineering observation, 5S and spaghetti diagramming. Reduction of lab technician movement as well as their body position at each workstation was of top concern to pathology leadership. With new equipment being brought into the lab to carry out workflow improvements, screen and tool placement was discussed with the techs in focus groups, to reduce variation and increase comfort throughout the workspace. 5S analysis was completed in two phases in the IHC lab, helping to drive solutions that reduced rework and tech motion. The IHC lab plans to continue utilizing these techniques to further reduce the time gap between tissue analysis and cancer care.

Keywords: engineering, ergonomics, healthcare, lean

Procedia PDF Downloads 200

Authors: Hendrick Maxil Zárate Rocha, Ricardo da Silva Pereira, Manoel Fernandes Martins Nogueira, Carlos R. Pereira Belchior, Maria Emilia de Lima Tostes

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This study investigates experimentally the effects of hydrogen addition in the intake manifold of a diesel generator operating with a 7% biodiesel-diesel oil blend (B7). An experimental apparatus setup was used to conduct performance and emissions tests in a single cylinder, air cooled diesel engine. This setup consisted of a generator set connected to a wirewound resistor load bank that was used to vary engine load. In addition, a flowmeter was used to determine hydrogen volumetric flowrate and a digital anemometer coupled with an air box to measure air flowrate. Furthermore, a digital precision electronic scale was used to measure engine fuel consumption and a gas analyzer was used to determine exhaust gas composition and exhaust gas temperature. A thermopar was installed near the exhaust collection to measure cylinder temperature. In-cylinder pressure was measured using an AVL Indumicro data acquisition system with a piezoelectric pressure sensor. An AVL optical encoder was installed in the crankshaft and synchronized with in-cylinder pressure in real time. The experimental procedure consisted of injecting hydrogen into the engine intake manifold at different mass concentrations of 2,6,8 and 10% of total fuel mass (B7 + hydrogen), which represented energy fractions of 5,15, 20 and 24% of total fuel energy respectively. Due to hydrogen addition, the total amount of fuel energy introduced increased and the generators fuel injection governor prevented any increases of engine speed. Several conclusions can be stated from the test results. A reduction in specific fuel consumption as a function of hydrogen concentration increase was noted. Likewise, carbon dioxide emissions (CO2), carbon monoxide (CO) and unburned hydrocarbons (HC) decreased as hydrogen concentration increased. On the other hand, nitrogen oxides emissions (NOx) increased due to average temperatures inside the cylinder being higher. There was also an increase in peak cylinder pressure and heat release rate inside the cylinder, since the fuel ignition delay was smaller due to hydrogen content increase. All this indicates that hydrogen promotes faster combustion and higher heat release rates and can be an important additive to all kind of fuels used in diesel generators.

Keywords: diesel engine, hydrogen, dual fuel, combustion analysis, performance, emissions

Procedia PDF Downloads 330

Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

Procedia PDF Downloads 36

Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

Procedia PDF Downloads 46

Authors: B. Bernabela, P. Bles, A. Bloecker, D. DeRock, M. van Es, M. Gerritse, T. de Jongh, W. Lansing, M. Martinot, J. van de Wetering

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A heated debate has been taking place concerning research and teaching at Dutch universities for the last few years. The ministry of science and education has published reports on its strategy to improve university curricula and position the Netherlands as a globally competitive knowledge economy. These reports have provoked an uproar of responses from think tanks, concerned academics, and the media. At the center of the debate is disagreement over who should determine the Dutch university curricula and how these curricula should look. Many stakeholders in the higher education system have voiced their opinion, and some have not been heard. The result is that the diversity of visions is ignored or taken for granted in the official reports. Recognizing this gap in stakeholder analysis, the aim of this paper is to bring attention to the wide range of perspectives on who should be responsible for designing higher education curricula. Based on a previous analysis by the Rathenau Institute, we distinguish five different groups of stakeholders: government, business sector, university faculty and administration, students, and the societal sector. We conducted semi-structured, in-depth interviews with representatives from each stakeholder group, and distributed quantitative questionnaires to people in the societal sector (i.e. people not directly affiliated with universities or graduates). Preliminary data suggests that the stakeholders have different target points concerning the university curricula. Representatives from the governmental sector tend to place special emphasis on the link between research and education, while representatives from the business sector rather focus on greater opportunities for students to obtain practical experience in the job market. Responses from students reflect a belief that they should be able to influence the curriculum in order to compete with other students on the international job market. On the other hand, university faculty expresses concern that focusing on the labor market puts undue pressure on students and compromises the quality of education. Interestingly, the opinions of members of ‘society’ seem to be relatively unchanged by political and economic shifts. Following a comprehensive analysis of the data, we believe that our results will make a significant contribution to the debate on university education in the Netherlands. These results should be regarded as a foundation for further research concerning the direction of Dutch higher education, for only if we take into account the different opinions and views of the various stakeholders can we decide which steps to take. Moreover, the Dutch experience offers lessons to other countries as well. As the internationalization of higher education is occurring faster than ever before, universities throughout Europe and globally are experiencing many of the same pressures.

Keywords: Dutch University curriculum, higher education, participants’ opinions, stakeholder perspectives

Procedia PDF Downloads 317

Authors: Michael N. O'Sullivan, Con Sheahan

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Researchers have spent decades developing tools and techniques to aid teams in the new product development (NPD) process. Despite this, it is evident that there is a huge gap between their academic prevalence and their industry adoption. For the fuzzy front-end, in particular, there is a wide range of tools to choose from, including the Kano Model, the House of Quality, and many others. In fact, there are so many tools that it can often be difficult for teams to know which ones to use and how they interact with one another. Moreover, while the benefits of using these tools are obvious to industrialists, they are rarely used as they carry a learning curve that is too steep and they become too complex to manage over time. In essence, it is commonly believed that they are simply not worth the effort required to learn and use them. This research explores a streamlined process for the fuzzy front-end, assembling the most effective tools and making them accessible to everyone. The process was developed iteratively over the course of 3 years, following over 80 final year NPD teams from engineering, design, technology, and construction as they carried a product from concept through to production specification. Questionnaires, focus groups, and observations were used to understand the usability issues with the tools involved, and a human-centred design approach was adopted to produce a solution to these issues. The solution takes the form of physical toolkit, similar to a board game, which allows the team to play through an example of a new product development in order to understand the process and the tools, before using it for their own product development efforts. A complimentary website is used to enhance the physical toolkit, and it provides more examples of the tools being used, as well as deeper discussions on each of the topics, allowing teams to adapt the process to their skills, preferences and product type. Teams found the solution very useful and intuitive and experienced significantly less confusion and mistakes with the process than teams who did not use it. Those with a design background found it especially useful for the engineering principles like Quality Function Deployment, while those with an engineering or technology background found it especially useful for design and customer requirements acquisition principles, like Voice of the Customer. Products developed using the toolkit are added to the website as more examples of how it can be used, creating a loop which helps future teams understand how the toolkit can be adapted to their project, whether it be a small consumer product or a large B2B service. The toolkit unlocks the potential of these beneficial tools to those in industry, both for large, experienced teams and for inexperienced start-ups. It allows users to assess the market potential of their product concept faster and more effectively, arriving at the product design stage with technical requirements prioritized according to their customers’ needs and wants.

Keywords: new product development, fuzzy front-end, usability, Kano model, quality function deployment, voice of customer

Procedia PDF Downloads 92

Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

Abstract:

Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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