Search results for: stability optimization

Authors: Y. Moldes-Diz, M. Gamallo, G. Eibes, C. Vazquez-Vazquez, G. Feijoo, J. M. Lema, M. T. Moreira

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Laccases (benzenediol oxygen oxidoreductases, EC 1.10.3.2) are excellent biocatalysts for biotechnological and environmental applications because of their high activity, selectivity, and specificity. Specifically, these characteristics allow them to perform the oxidation of recalcitrant compounds with simple requirements for the catalysis (presence of molecular oxygen). Nevertheless, the low stability under unfavorable conditions (pH, inactivating agents or temperature) and high production costs still limits their use for practical applications. Immobilization of enzymes has proven particularly valuable to avoid some of the aforementioned drawbacks. Magnetic nanoparticles (MNPs) have received increasing attention as carriers for enzyme immobilization since they can potentially provide an easy recovery of the biocatalyst from the reaction medium under an external magnetic field. In the present work, silica-coated magnetic nanoparticles (Fe3O4@SiO2) were prepared, characterized and used for laccase immobilization by covalent binding. The synthesis of Fe3O4@SiO2 was performed in a two-step procedure: co-precipitation and reverse microemulsion. The influence of immobilization conditions: concentrations of the functionalization agent (3-aminopropyl-triethoxy-silane) and the cross-linker (glutaraldehyde) as well as the influence of pH, T or inactivating agents were evaluated. In general, immobilized laccase showed superior stability compared to that of free enzyme. The reusability of the biocatalyst was demonstrated in successive batch reactions, where enzyme activity was maintained above 65% after 8 cycles of oxidation of the substrate 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonate).

Keywords: silica-coated magnetic nanoparticles, laccase, immobilization, regeneration

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Authors: Iulia E. Falcan

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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

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Authors: Istvan Szilagyi, Marko Pavlovic, Paul Rouster

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Antioxidant enzymes are the most efficient defense systems against reactive oxygen species, which cause severe damage in living organisms and industrial products. However, their supplementation is problematic due to their high sensitivity to the environmental conditions. Immobilization on carrier nanoparticles is a promising research direction towards the improvement of their functional and colloidal stability. In that way, their applications in biomedical treatments and manufacturing processes in the food, textile and cosmetic industry can be extended. The main goal of the present research was to prepare and formulate antioxidant bionanocomposites composed of superoxide dismutase (SOD) enzyme, anionic clay (layered double hydroxide, LDH) nanoparticle and heparin (HEP) polyelectrolyte. To characterize the structure and the colloidal stability of the obtained compounds in suspension and solid state, electrophoresis, dynamic light scattering, transmission electron microscopy, spectrophotometry, thermogravimetry, X-ray diffraction, infrared and fluorescence spectroscopy were used as experimental techniques. LDH-SOD composite was synthesized by enzyme immobilization on the clay particles via electrostatic and hydrophobic interactions, which resulted in a strong adsorption of the SOD on the LDH surface, i.e., no enzyme leakage was observed once the material was suspended in aqueous solutions. However, the LDH-SOD showed only limited resistance against salt-induced aggregation and large irregularly shaped clusters formed during short term interval even at lower ionic strengths. Since sufficiently high colloidal stability is a key requirement in most of the applications mentioned above, the nanocomposite was coated with HEP polyelectrolyte to develop highly stable suspensions of primary LDH-SOD-HEP particles. HEP is a natural anticoagulant with one of the highest negative line charge density among the known macromolecules. The experimental results indicated that it strongly adsorbed on the oppositely charged LDH-SOD surface leading to charge inversion and to the formation of negatively charged LDH-SOD-HEP. The obtained hybrid materials formed stable suspension even under extreme conditions, where classical colloid chemistry theories predict rapid aggregation of the particles and unstable suspensions. Such a stabilization effect originated from electrostatic repulsion between the particles of the same sign of charge as well as from steric repulsion due to the osmotic pressure raised during the overlap of the polyelectrolyte chains adsorbed on the surface. In addition, the SOD enzyme kept its structural and functional integrity during the immobilization and coating processes and hence, the LDH-SOD-HEP bionanocomposite possessed excellent activity in decomposition of superoxide radical anions, as revealed in biochemical test reactions. In conclusion, due to the improved colloidal stability and the good efficiency in scavenging superoxide radical ions, the developed enzymatic system is a promising antioxidant candidate for biomedical or other manufacturing processes, wherever the aim is to decompose reactive oxygen species in suspensions.

Keywords: clay, enzyme, polyelectrolyte, formulation

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Authors: Wenjuan Lu

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China and Hungary have risen from a friendly and comprehensive cooperative relationship to a comprehensive strategic partnership in recent years, and the economic and trade relations between the two countries have developed smoothly. As an important country along the ‘Belt and Road’, Hungary and China have strong economic complementarities and have unique advantages in carrying China's industrial transfer and economic transformation and development. The construction of the China-Hungary Economic and Trade Cooperation Zone, which was initiated by the ‘Sino-Hungarian Borsod Industrial Zone’ and the ‘Hungarian Central European Trade and Logistics Cooperation Park’ has promoted infrastructure construction, optimized production capacity, promoted industrial restructuring, and formed brand and agglomeration effects. Enhancing the influence of Chinese companies in the European market has also promoted economic development in Hungary and even in Central and Eastern Europe. However, as the China-Hungary Economic and Trade Cooperation Zone is still in its infancy, there are still shortcomings such as small scale, single function, and no prominent platform. In the future, based on the needs of China's cooperation with ‘17+1’ and China-Hungary cooperation, on the basis of appropriately expanding the scale of economic and trade cooperation zones and appropriately increasing the number of economic and trade cooperation zones, it is better to focus on optimizing and adjusting its functions and highlighting different economic and trade cooperation. The differentiated function of the trade zones strengthens the multi-faceted cooperation of economic and trade cooperation zones and highlights its role as a platform for cooperation in information, capital, and services.

Keywords: ‘One Belt, One Road’ Initiative, China-Hungary economic and trade cooperation zone, function optimization, Central and Eastern Europe

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Authors: Eashan Hatti

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In software development, programmers often must make a choice between high-level programming and high-performance programs. High-level programming encourages the use of complex, pervasive abstractions. However, the use of these abstractions degrades performance-high performance demands that programs be low-level. In a compiler, the optimizer attempts to let the user have both. The optimizer takes high-level, abstract code as an input and produces low-level, performant code as an output. However, there is a problem with having the optimizer be a built-in part of the compiler. Domain-specific abstractions implemented as libraries are common in high-level languages. As a language’s library ecosystem grows, so does the number of abstractions that programmers will use. If these abstractions are to be performant, the optimizer must be extended with new optimizations to target them, or these abstractions must rely on existing general-purpose optimizations. The latter is often not as effective as needed. The former presents too significant of an effort for the compiler developers, as they are the only ones who can extend the language with new optimizations. Thus, the language becomes more high-level, yet the optimizer – and, in turn, program performance – falls behind. Programmers are again confronted with a choice between high-level programming and high-performance programs. To investigate a potential solution to this problem, we developed Peridot, a prototype programming language. Peridot’s main contribution is that it enables library developers to easily extend the language with new optimizations themselves. This allows the optimization workload to be taken off the compiler developers’ hands and given to a much larger set of people who can specialize in each problem domain. Because of this, optimizations can be much more effective while also being much more numerous. To enable this, Peridot supports metaprogramming designed for implementing program transformations. The language is split into two fragments or “levels”, one for metaprogramming, the other for high-level general-purpose programming. The metaprogramming level supports logic programming. Peridot’s key idea is that optimizations are simply implemented as metaprograms. The meta level supports several specific features which make it particularly suited to implementing optimizers. For instance, metaprograms can automatically deduce equalities between the programs they are optimizing via unification, deal with variable binding declaratively via higher-order abstract syntax, and avoid the phase-ordering problem via non-determinism. We have found that this design centered around logic programming makes optimizers concise and easy to write compared to their equivalents in functional or imperative languages. Overall, implementing Peridot has shown that its design is a viable solution to the problem of writing code which is both high-level and performant.

Keywords: optimization, metaprogramming, logic programming, abstraction

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Authors: Aliaa M. El-Borai, Ehab A. Beltagy, Eman E. Gadallah, Samy A. ElAssar

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Bioremediation technology is now used for treatment instead of traditional metal removal methods. A strain was isolated from Marsa Alam, Red sea, Egypt showed high resistance to high lead concentration and was identified by the 16S rRNA gene sequencing technique as Halomonas sp. ES015. Medium optimization was carried out using Plackett-Burman design, and the most significant factors were yeast extract, casamino acid and inoculums size. The optimized media obtained by the statistical design raised the removal efficiency from 84% to 99% from initial concentration 250 ppm of lead. Moreover, Box-Behnken experimental design was applied to study the relationship between yeast extract concentration, casamino acid concentration and inoculums size. The optimized medium increased removal efficiency to 97% from initial concentration 500 ppm of lead. Immobilized Halomonas sp. ES015 cells on sponge cubes, using optimized medium in loop bioremediation column, showed relatively constant lead removal efficiency when reused six successive cycles over the range of time interval. Also metal removal efficiency was not affected by flow rate changes. Finally, the results of this research refer to the possibility of lead bioremediation by free or immobilized cells of Halomonas sp. ES015. Also, bioremediation can be done in batch cultures and semicontinuous cultures using column technology.

Keywords: bioremediation, lead, Box–Behnken, Halomonas sp. ES015, loop bioremediation, Plackett-Burman

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Authors: Charlene N. T. Mfangnia, Henri Tonnang, Berge Tsanou, Jeremy Herren

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The Microsporidia MB found in the populations of anopheles is a recently discovered symbiont responsible for the Plasmodium transmission blocking. From early studies, it was established that the symbiont can be transmitted vertically and horizontally. The present study uses compartmental mathematical modelling approach to investigate the dynamics of Microsporidia transmission in the mosquito population with the mindset of establishing a mechanism for use to control malaria. Data and information obtained from laboratory experiments are used to estimate the model parameters with and without temperature dependency of mosquito traits. We carry out the mathematical analysis focusing on the equilibria states and their stability for the autonomous model. Through the modelling experiments, we are able to assess and confirm the contribution of vertical and horizontal transmission in the proliferation of Microsporidia MB in the mosquito population. In addition, the basic and target reproductions are computed, and some long-term behaviours of the model, such as the local (and global) stability of equilibrium points, are rigorously analysed and illustrated numerically. We establish the conditions responsible for the low prevalence of the symbiont-infected mosquitoes observed in nature. Moreover, we identify the male death rate, the mating rate and the attractiveness of MB-positive mosquitoes as mosquito traits that significantly influence the spread of Microsporidia MB. Furthermore, we highlight the influence of temperature in the establishment and persistence of MB-infected mosquitoes in a given area.

Keywords: microsporidia MB, vertical transmission, horizontal transmission, compartmental modelling approach, temperature-dependent mosquito traits, malaria, plasmodium-transmission blocking

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Authors: Hyun Seop Uhm, Yong Ho Choi, Ji Eun Kim, Young Hoon Lee

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Weapon-target assignment (WTA) is a problem that assigns available launchers to appropriate targets in order to defend assets. Various algorithms for WTA have been developed over past years for both in the static and dynamic environment (denoted by SWTA and DWTA respectively). Due to the problem requirement to be solved in a relevant computational time, WTA has suffered from the solution efficiency. As a result, SWTA and DWTA problems have been solved in the limited situation of the battlefield. In this paper, the general situation under continuous time is considered by Time based Weapon Target Assignment (TWTA) problem. TWTA are studied using the mixed integer programming model, and three heuristic algorithms; decomposed opt-opt, decomposed opt-greedy, and greedy algorithms are suggested. Although the TWTA optimization model works inefficiently when it is characterized by a large size, the decomposed opt-opt algorithm based on the linearization and decomposition method extracted efficient solutions in a reasonable computation time. Because the computation time of the scheduling part is too long to solve by the optimization model, several algorithms based on greedy is proposed. The models show lower performance value than that of the decomposed opt-opt algorithm, but very short time is needed to compute. Hence, this paper proposes an improved method by applying decomposition to TWTA, and more practical and effectual methods can be developed for using TWTA on the battlefield.

Keywords: air and missile defense, weapon target assignment, mixed integer programming, piecewise linearization, decomposition algorithm, military operations research

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Authors: Chi-Yuan Huang, Mei-Chuan Kuo, Ching-Yi Hsiao

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In this study, acids with various chain lengths (C₆, C₈, C₁₀ and C₁₂) modified by methane sulfonic acid (MSA) and temperature were used to modify tapioca starch (TPS), then the glycerol (GA) were added into modified starch, to prepare new blends. The mechanical properties, thermal properties and physical properties of blends were studied. This investigation was divided into two parts.  First, the biodegradable materials were used such as starch and glycerol with hexanedioic acid (HA), suberic acid (SBA), sebacic acid (SA), decanedicarboxylic acid (DA) manufacturing with different temperatures (90, 110 and 130 °C). And then, the solution was added into modified starch to prepare the blends by using single-screw extruder. The FT-IR patterns indicated that the characteristic peak of C=O in ester was observed at 1730 cm^-1. It is proved that different chain length acids (C₆, C₈, C₁₀ and C₁₂) reacted with glycerol by esterification and these are used to plasticize blends during extrusion. In addition, the blends would improve the hydrolysis and thermal stability. The water contact angle increased from 43.0° to 64.0°.  Second, the HA (110 °C), SBA (110 °C), SA (110 °C), and DA blends (130 °C) were used in study, because they possessed good mechanical properties, water resistances and thermal stability. On the other hand, the various contents (0, 0.005, 0.010, 0.020 g) of MSA were also used to modify the mechanical properties of blends. We observed that the blends were added to MSA, and then the FT-IR patterns indicated that the C=O ester appeared at 1730 cm^-1. For this reason, the hydrophobic blends were produced. The water contact angle of the MSA blends increased from 55.0° to 71.0°. Although break elongation of the MSA blends reduced from the original 220% to 128%, the stress increased from 2.5 MPa to 5.1 MPa. Therefore, the optimal composition of blends was the DA blend (130 °C) with adding of MSA (0.005 g).

Keywords: chain length acids, methane sulfonic acid, Tapioca starch (TPS), tensile stress

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Michael T. Lobmann, Camilla Wellstein, Stefan Zerbe

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Vegetation plays an important role for the stabilization of slopes against erosion processes, such as shallow erosion and landslides. Plant roots reinforce the soil, increase soil cohesion and often cross possible shear planes. Hence, plant roots reduce the risk of slope failure. Generally, shrub and tree roots penetrate deeper into the soil vertically, while roots of forbs and grasses are concentrated horizontally in the topsoil and organic layer. Therefore, shrubs and trees have a higher potential for stabilization of slopes with deep soil layers than forbs and grasses. Consequently, research mainly focused on the vertical root effects of shrubs and trees. Nevertheless, a better understanding of the stabilizing effects of grasses and forbs is needed for better evaluation of the stability of natural and artificial slopes with herbaceous vegetation. Despite the importance of vertical root effects, field observations indicate that horizontal root effects also play an important role for slope stabilization. Not only forbs and grasses, but also some shrubs and trees form tight horizontal networks of fine and coarse roots and rhizomes in the topsoil. These root networks increase soil cohesion and horizontal tensile strength. Available methods for physical measurements, such as shear-box tests, pullout tests and singular root tensile strength measurement can only provide a detailed picture of vertical effects of roots on slope stabilization. However, the assessment of horizontal root effects is largely limited to computer modeling. Here, a method for measurement of in-situ cumulative horizontal root tensile strength is presented. A traction machine was developed that allows fixation of rectangular grass sods (max. 30x60cm) on the short ends with a 30x30cm measurement zone in the middle. On two alpine grass slopes in South Tyrol (northern Italy), 30x60cm grass sods were cut out (max. depth 20cm). Grass sods were pulled apart measuring the horizontal tensile strength over 30cm width over the time. The horizontal tensile strength of the sods was measured and compared for different soil depths, hydrological conditions, and root physiological properties. The results improve our understanding of horizontal root effects on slope stabilization and can be used for improved evaluation of grass slope stability.

Keywords: grassland, horizontal root effect, landslide, mountain, pasture, shallow erosion

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Authors: Michael A. Unbehauen, Gregory D. Sloan, Alberto J. Squatrito

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Missile proliferation and global stability are intrinsically linked. Missile threats continually appear at the forefront of global security issues. North Korea’s recently demonstrated nuclear and intercontinental ballistic missile (ICBM) capabilities, for the first time since the Cold War, renewed public interest in strategic missile defense capabilities. To protect from limited ICBM attacks from so-called rogue actors, the United States developed the Ground-based Midcourse Defense (GMD) system. This study examines if the GMD missile defense shield has contributed to a safer world or triggered a new arms race. Based upon increased missile-related developments and the lack of adherence to international missile treaties, it is generally perceived that the GMD system is a destabilizing factor for global security. By examining the current state of arms control treaties as well as existing missile arsenals and ongoing efforts in technologies to overcome U.S. missile defenses, this study seeks to analyze the contribution of GMD to global stability. A thorough investigation cannot ignore that, through the establishment of this limited capability, the U.S. violated longstanding, successful weapons treaties and caused concern among states that possess ICBMs. GMD capability contributes to the perception that ICBM arsenals could become ineffective, creating an imbalance in favor of the United States, leading to increased global instability and tension. While blame for the deterioration of global stability and non-adherence to arms control treaties is often placed on U.S. missile defense, the facts do not necessarily support this view. The notion of a renewed arms race due to GMD is supported neither by current missile arsenals nor by the inevitable development of new and enhanced missile technology, to include multiple independently targeted reentry vehicles (MIRVs), maneuverable reentry vehicles (MaRVs), and hypersonic glide vehicles (HGVs). The methodology in this study encapsulates a period of time, pre- and post-GMD introduction, while analyzing international treaty adherence, missile counts and types, and research in new missile technologies. The decline in international treaty adherence, coupled with a measurable increase in the number and types of missiles or research in new missile technologies during the period after the introduction of GMD, could be perceived as a clear indicator of GMD contributing to global instability. However, research into improved technology (MIRV, MaRV and HGV) prior to GMD, as well as a decline of various global missile inventories and testing of systems during this same period, would seem to invalidate this theory. U.S. adversaries have exploited the perception of the U.S. missile defense shield as a destabilizing factor as a pretext to strengthen and modernize their militaries and justify their policies. As a result, it can be concluded that global stability has not significantly decreased due to GMD; but rather, the natural progression of technological and missile development would inherently include innovative and dynamic approaches to target engagement, deterrence, and national defense.

Keywords: arms control, arms race, global security, GMD, ICBM, missile defense, proliferation

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Authors: Hanwei Gao, Louis Jezequel, Eric Cabrol, Bernard Vitry

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The chassis system is composed of complex elements that take up all the loads from the tire-ground contact area and thus it plays an important role in numerous specifications such as durability, comfort, crash, etc. During the development of new vehicle projects in Renault, durability validation is always the main focus while deployment of comfort comes later in the project. Therefore, sometimes design choices have to be reconsidered because of the natural incompatibility between these two specifications. Besides, robustness is also an important point of concern as it is related to manufacturing costs as well as the performance after the ageing of components like shock absorbers. In this paper an approach is proposed aiming to realize a multi-objective optimization between chassis endurance and comfort while taking the random factors into consideration. The adaptive-sparse polynomial chaos expansion method (PCE) with Chebyshev polynomial series has been applied to predict responses’ uncertainty intervals of a system according to its uncertain-but-bounded parameters. The approach can be divided into three steps. First an initial design of experiments is realized to build the response surfaces which represent statistically a black-box system. Secondly within several iterations an optimum set is proposed and validated which will form a Pareto front. At the same time the robustness of each response, served as additional objectives, is calculated from the pre-defined parameter intervals and the response surfaces obtained in the first step. Finally an inverse strategy is carried out to determine the parameters’ tolerance combination with a maximally acceptable degradation of the responses in terms of manufacturing costs. A quarter car model has been tested as an example by applying the road excitations from the actual road measurements for both endurance and comfort calculations. One indicator based on the Basquin’s law is defined to compare the global chassis durability of different parameter settings. Another indicator related to comfort is obtained from the vertical acceleration of the sprung mass. An optimum set with best robustness has been finally obtained and the reference tests prove a good robustness prediction of Chebyshev PCE method. This example demonstrates the effectiveness and reliability of the approach, in particular its ability to save computational costs for a complex system.

Keywords: chassis durability, Chebyshev polynomials, multi-objective optimization, polynomial chaos expansion, ride comfort, robust design

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Authors: Charline Monnier, Rudolf Andrys, Irene Castellino, Lucie Zemanova

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Due to their inherent sustainability and compatibility with green chemistry principles, enzymes are attracting increasing attention for various applications like bioremediation or biocatalysis. These natural catalysts boast remarkable substrate specificity and operate under mild biological conditions. However, their intrinsic limitations, such as instability at high temperatures or in organic solvents, impede their wider applicability. Enzyme immobilization on supportive matrices emerges as a promising strategy to address these challenges. This approach not only facilitates enzyme reusability but also offers the potential to modulate their stability, activity, and selectivity. The present study investigates the immobilization and application of two distinct groups of hydrolases on supportive matrices: PETases, naturally capable of PolyEthylene Terephthalate (PET) degradation, and cholinesterases (ChEs), key enzymes in neurotransmitter regulation. All tested enzymes will be immobilized on porous and non-porous particles using both covalent and non-covalent methods. Additionally, the stability of PETases and cholinesterases will be explored, followed by exposure to denaturing conditions to assess their resilience under harsh conditions. Furthermore, due to the exceptional catalytic efficiency and selectivity, their biocatalytic efficiency will be tested using xenobiotic substrates, aiming to establish them as replacements for conventional chemical catalysts in environmentally friendly processes. By exploiting the power of enzyme immobilization, this research strives to unlock the full potential of these biocatalysts for sustainable and efficient technological advancements.

Keywords: biocatalysis, bioremediation, enzyme efficiency, enzyme immobilization, green chemistry

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Authors: Xin-Yu Li, Dung-Ying Lin

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Fleet availability is a crucial indicator for an aircraft fleet. However, in practice, fleet planning involves many resource and safety constraints, such as annual and monthly flight training targets and maximum engine usage limits. Due to safety considerations, engines must be removed for mandatory maintenance and replacement of key components. This situation is known as the "threshold." The annual number of thresholds is a key factor in maintaining fleet availability. However, the traditional method heavily relies on experience and manual planning, which may result in ineffective engine usage and affect the flight missions. This study aims to address the challenges of fleet planning and availability maintenance in aircraft fleets with resource and safety constraints. The goal is to effectively optimize engine usage and maintenance tasks. This study has four objectives: minimizing the number of engine thresholds, minimizing the monthly lack of flight hours, minimizing the monthly excess of flight hours, and minimizing engine disassembly frequency. To solve the resulting formulation, this study uses parametric programming techniques and ϵ-constraint method to reformulate multi-objective problems into single-objective problems, efficiently generating Pareto fronts. This method is advantageous when handling multiple conflicting objectives. It allows for an effective trade-off between these competing objectives. Empirical results and managerial insights will be provided.

Keywords: aircraft fleet, engine utilization planning, multi-objective optimization, parametric method, Pareto optimality

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Authors: Rupam Saikia, Ashim Kanti Dey

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Sonapur is an intense hilly region on the border of Assam and Meghalaya lying in North-East India and is very near to a seismic fault named as Dauki besides which makes the region seismically active. Besides, these recently two earthquakes of magnitude 6.7 and 6.9 have struck North-East India in January and April 2016. Also, the slope concerned for this study is adjacent to NH 44 which for a long time has been a sole important connecting link to the states of Manipur and Mizoram along with some parts of Assam and so has been a cause of considerable loss to life and property since past decades as there has been several recorded incidents of landslide, road-blocks, etc. mostly during the rainy season which comes into news. Based on this issue this paper reports a static and dynamic slope stability analysis of Sonapur which has been carried out in MIDAS GTS NX. The slope being highly unreachable due to terrain and thick vegetation in-situ test was not feasible considering the current scope available so disturbed soil sample was collected from the site for the determination of strength parameters. The strength parameters were so determined for varying relative density with further variation in water content. The slopes were analyzed considering plane strain condition for three slope heights of 5 m, 10 m and 20 m which were then further categorized based on slope angles 30, 40, 50, 60, and 70 considering the possible extent of steepness. Initially static analysis under dry state was performed then considering the worst case that can develop during rainy season the slopes were analyzed for fully saturated condition along with partial degree of saturation with an increase in the waterfront. Furthermore, dynamic analysis was performed considering the El-Centro Earthquake which had a magnitude of 6.7 and peak ground acceleration of 0.3569g at 2.14 sec for the slope which were found to be safe during static analysis under both dry and fully saturated condition. Some of the conclusions were slopes with inclination above 40 onwards were found to be highly vulnerable for slopes of height 10 m and above even under dry static condition. Maximum horizontal displacement showed an exponential increase with an increase in inclination from 30 to 70. The vulnerability of the slopes was seen to be further increased during rainy season as even slopes of minimal steepness of 30 for height 20 m was seen to be on the verge of failure. Also, during dynamic analysis slopes safe during static analysis were found to be highly vulnerable. Lastly, as a part of the study a comparative study on Strength Reduction Method (SRM) versus Limit Equilibrium Method (LEM) was also carried out and some of the advantages and disadvantages were figured out.

Keywords: dynamic analysis, factor of safety, slope stability, strength reduction method

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Jannika Dombrowski, Sabine Ambros, Ulrich Kulozik

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Several drying techniques are used to preserve sensitive substances such as probiotic lactic acid bacteria. With the aim to better understand differences between these processes, this work gives new insights into structural variations resulting from different preservation methods and their impact on product quality and storage stability. Industrially established methods (freeze drying, spray drying) were compared to upcoming vacuum, microwave-freeze, and microwave-vacuum drying. For freeze and microwave-freeze dried samples, survival and activity maintained 100%, whereas vacuum and microwave-vacuum dried cultures achieved 30-40% survival. Spray drying yielded in lowest viability. The results are directly related to temperature and oxygen content during drying. Interestingly, most storage stable products resulted from vacuum and microwave-vacuum drying due to denser product structures as determined by helium pycnometry and SEM images. Further, lower water adsorption velocities were responsible for lower inactivation rates. Concluding, resulting product structures as well as survival rates and storage stability mainly depend on the type of water removal instead of energy input. Microwave energy compared to conductive heating did not lead to significant differences regarding the examined factors. Correlations could be proven for three investigated microbial strains. The presentation will be completed by an overview on the energy efficiency of the presented methods.

Keywords: drying techniques, energy efficiency, lactic acid bacteria, probiotics, survival rates, structure characterization

Procedia PDF Downloads 238

Authors: Xiao-Dong Wang, Wei-Mon Yan

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The flow field design in the bipolar plates affects the performance of the proton exchange membrane (PEM) fuel cell. This work adopted a combined optimization procedure, including a simplified conjugate-gradient method and a completely three-dimensional, two-phase, non-isothermal fuel cell model, to look for optimal flow field design for a single serpentine fuel cell of size 9×9 mm with five channels. For the direct solution, the two-fluid method was adopted to incorporate the heat effects using energy equations for entire cells. The model assumes that the system is steady; the inlet reactants are ideal gases; the flow is laminar; and the porous layers such as the diffusion layer, catalyst layer and PEM are isotropic. The model includes continuity, momentum and species equations for gaseous species, liquid water transport equations in the channels, gas diffusion layers, and catalyst layers, water transport equation in the membrane, electron and proton transport equations. The Bulter-Volumer equation was used to describe electrochemical reactions in the catalyst layers. The cell output power density Pcell is maximized subjected to an optimal set of channel heights, H1-H5, and channel widths, W2-W5. The basic case with all channel heights and widths set at 1 mm yields a Pcell=7260 Wm-2. The optimal design displays a tapered characteristic for channels 1, 3 and 4, and a diverging characteristic in height for channels 2 and 5, producing a Pcell=8894 Wm-2, about 22.5% increment. The reduced channel heights of channels 2-4 significantly increase the sub-rib convection and widths for effectively removing liquid water and oxygen transport in gas diffusion layer. The final diverging channel minimizes the leakage of fuel to outlet via sub-rib convection from channel 4 to channel 5. Near-optimal design without huge loss in cell performance but is easily manufactured is tested. The use of a straight, final channel of 0.1 mm height has led to 7.37% power loss, while the design with all channel widths to be 1 mm with optimal channel heights obtained above yields only 1.68% loss of current density. The presence of a final, diverging channel has greater impact on cell performance than the fine adjustment of channel width at the simulation conditions set herein studied.

Keywords: optimization, flow field design, simplified conjugate-gradient method, serpentine flow field, sub-rib convection

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Authors: Kristopher A. Pruitt, Justin M. Hill

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The purpose of this research is to determine the pacing and nutrition strategies which minimize completion time and carbohydrate intake for athletes competing in ultramarathon races. The model formulation consists of a two-phase optimization. The first-phase mixed-integer nonlinear program (MINLP) determines the minimum completion time subject to the altitude, terrain, and distance of the race, as well as the mass and cardiovascular fitness of the athlete. The second-phase MINLP determines the minimum total carbohydrate intake required for the athlete to achieve the completion time prescribed by the first phase, subject to the flow of carbohydrates through the stomach, liver, and muscles. Consequently, the second phase model provides the optimal pacing and nutrition strategies for a particular athlete for each kilometer of a particular race. Validation of the model results over a wide range of athlete parameters against completion times for real competitive events suggests strong agreement. Additionally, the kilometer-by-kilometer pacing and nutrition strategies, the model prescribes for a particular athlete suggest unconventional approaches could result in lower completion times. Thus, the MINLP provides prescriptive guidance that athletes can leverage when developing pacing and nutrition strategies prior to competing in ultramarathon races. Given the highly-variable topographical characteristics common to many ultramarathon courses and the potential inexperience of many athletes with such courses, the model provides valuable insight to competitors who might otherwise fail to complete the event due to exhaustion or carbohydrate depletion.

Keywords: nutrition, optimization, pacing, ultramarathons

Procedia PDF Downloads 188

Authors: Ahmet Erten, Adil Mustafa, Ayşenur Eser, Özlem Yalçın

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We present a new viscometer based on a microfluidic chip with elastic high aspect ratio micropillar arrays. The displacement of pillar tips in flow direction can be used to analyze viscosity of liquid. In our work, Computational Fluid Dynamics (CFD) is used to analyze pillar displacement of various micropillar array configurations in flow direction at different viscosities. Following CFD optimization, micro-CNC based rapid prototyping is used to fabricate molds for microfluidic chips. Microfluidic chips are fabricated out of polydimethylsiloxane (PDMS) using soft lithography methods with molds machined out of aluminum. Tip displacements of micropillar array (300 µm in diameter and 1400 µm in height) in flow direction are recorded using a microscope mounted camera, and the displacements are analyzed using image processing with an algorithm written in MATLAB. Experiments are performed with water-glycerol solutions mixed at 4 different ratios to attain 1 cP, 5 cP, 10 cP and 15 cP viscosities at room temperature. The prepared solutions are injected into the microfluidic chips using a syringe pump at flow rates from 10-100 mL / hr and the displacement versus flow rate is plotted for different viscosities. A displacement of around 1.5 µm was observed for 15 cP solution at 60 mL / hr while only a 1 µm displacement was observed for 10 cP solution. The presented viscometer design optimization is still in progress for better sensitivity and accuracy. Our microfluidic viscometer platform has potential for tailor made microfluidic chips to enable real time observation and control of viscosity changes in biological or chemical reactions.

Keywords: Computational Fluid Dynamics (CFD), high aspect ratio, micropillar array, viscometer

Procedia PDF Downloads 244

Authors: F. Deng, R. Sanchez, A. Beltran, S. Maestre

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The high nutritional value associated with seafood is related to the presence of essential trace elements. Moreover, seafood is considered an important source of energy, proteins, and long-chain polyunsaturated fatty acids. Generally, seafood is consumed cooked. Consequently, the nutritional value could be degraded. Seafood, such as fish, shellfish, and seaweed, could be considered as one of the main iodine sources. The deficient or excessive consumption of iodine could cause dysfunction and pathologies related to the thyroid gland. The main objective of this work is to evaluated iodine stability in hake (Merluccius) undergone different culinary techniques. The culinary process considered were: boiling, steaming, microwave cooking, baking, cooking en papillote (twisted cover with the shape of a sweet wrapper) and coating with a batter of flour and deep-frying. The determination of iodine was carried by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Regarding sample handling strategies, liquid-liquid extraction has demonstrated to be a powerful pre-concentration and clean-up approach for trace metal analysis by ICP techniques. Extraction with tetramethylammonium hydroxide (TMAH reagent) was used as a sample preparation method in this work. Based on the results, it can be concluded that the stability of iodine was degraded with the cooking processes. The major degradation was observed for the boiling and microwave cooking processes. The content of iodine in hake decreased up to 60% and 52%, respectively. However, if the boiling cooking liquid is preserved, this loss that has been generated during cooking is reduced. Only when the fish was cooked by following the cooking en papillote process the iodine content was preserved.

Keywords: cooking process, ICP-MS, iodine, hake

Procedia PDF Downloads 140

Authors: Muhammad A. Alsubaie, Mubarak K. H. Alhajri, Tarek S. Altowaim

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A repetitive controller designed to accommodate periodic disturbances via state feedback is discussed. Periodic disturbances can be represented by a time delay model in a positive feedback loop acting on system output. A direct use of the small gain theorem solves the periodic disturbances problem via 1) isolating the delay model, 2) finding the overall system representation around the delay model and 3) designing a feedback controller that assures overall system stability and tracking error convergence. This paper addresses uncertainty conditions for the repetitive controller designed in state feedback in either past error feedforward or current error feedback using singular values. The uncertainty investigation is based on the overall system found and the stability condition associated with it; depending on the scheme used, to set an upper/lower limit weighting parameter. This creates a region that should not be exceeded in selecting the weighting parameter which in turns assures performance improvement against system uncertainty. Repetitive control problem can be described in lifted form. This allows the usage of singular values principle in setting the range for the weighting parameter selection. The Simulation results obtained show a tracking error convergence against dynamic system perturbation if the weighting parameter chosen is within the range obtained. Simulation results also show the advantage of weighting parameter usage compared to the case where it is omitted.

Keywords: model mismatch, repetitive control, singular values, state feedback

Procedia PDF Downloads 155

Authors: Chiao-Yi Chen, Dung-Ying Lin

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With the growing awareness of environmental protection and the implementation of government carbon reduction policies, the number of electric vehicles (EVs) has rapidly increased, leading to a surge in charging demand and imposing significant challenges on the existing power grid’s capacity. Traditional urban power grid planning has not adequately accounted for the additional load generated by EV charging, which often strains the infrastructure. This study aims to optimize grid operation and load management by dynamically adjusting EV charging prices based on real-time electricity supply and demand, leveraging consumer demand elasticity to enhance system efficiency. This study uniquely addresses the intricate interplay between urban traffic patterns and power grid dynamics in the context of electric vehicle (EV) adoption. By integrating Hsinchu City's road network with the IEEE 33-bus system, the research creates a comprehensive model that captures both the spatial and temporal aspects of EV charging demand. This approach allows for a nuanced analysis of how traffic flow directly influences the load distribution across the power grid. The strategic placement of charging stations at key nodes within the IEEE 33-bus system, informed by actual road traffic data, enables a realistic simulation of the dynamic relationship between vehicle movement and energy consumption. This integration of transportation and energy systems provides a holistic view of the challenges and opportunities in urban EV infrastructure planning, highlighting the critical need for solutions that can adapt to the ever-changing interplay between traffic patterns and grid capacity. The proposed dynamic pricing strategy effectively reduces peak charging loads, enhances the operational efficiency of charging stations, and maximizes operator profits, all while ensuring grid stability. These findings provide practical insights and a valuable framework for optimizing EV charging infrastructure and policies in future smart cities, contributing to more resilient and sustainable urban energy systems.

Keywords: dynamic pricing, demand elasticity, EV charging, grid load balancing, optimization

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Authors: Olivier Chaigneau, Damianos Oikonomidis, Marie-Cecile Delmas

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GAMBAS (Galileo Advanced features for the Maritime domain: Breakthrough Applications for Safety and security) is a project funded by the European Space Program Agency (EUSPA) aiming at identifying the search-and-rescue and ship security alert system needs for maritime users (including operators and fishing stakeholders) and developing operational concepts to answer these needs. The general objective of the GAMBAS project is to support the deployment of Galileo exclusive features in the maritime domain in order to improve safety and security at sea, detection of illegal activities and associated surveillance means, resilience to natural and human-induced emergency situations, and develop, integrate, demonstrate, standardize and disseminate these new associated capabilities. The project aims to demonstrate: improvement of the SAR (Search And Rescue) and SSAS (Ship Security Alert System) detection and response to maritime distress through the integration of new features into the beacon for SSAS in terms of cost optimization, user-friendly aspects, integration of Galileo and OS NMA (Open Service Navigation Message Authentication) reception for improved authenticated localization performance and reliability, and at sea triggering capabilities, optimization of the responsiveness of RCCs (Rescue Co-ordination Centre) towards the distress situations affecting vessels, the adaptation of the MCCs (Mission Control Center) and MEOLUT (Medium Earth Orbit Local User Terminal) to the data distribution of SSAS alerts.

Keywords: Galileo new advanced features, maritime, safety, security

Procedia PDF Downloads 91

Authors: A. Gopala Krishna, M. Lakshmi Chaitanya, V. Kalyana Manohar

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In the existent analysis, laser micro machining (LMM) of Silicon carbide (SiCp) reinforced Aluminum 7075 Metal Matrix Composite (Al7075/SiCp MMC) was studied. While machining, Because of the intense heat generated, A layer gets formed on the work piece surface which is called recast layer and this layer is detrimental to the surface quality of the component. The recast layer needs to be as small as possible for precise applications. Therefore, The height of recast layer and the depth of groove which are conflicting in nature were considered as the significant manufacturing criteria, Which determines the pursuit of a machining process obtained in LMM of Al7075/10%SiCp composite. The present work formulates the depth of groove and height of recast layer in relation to the machining parameters using the Response Surface Methodology (RSM) and correspondingly, The formulated mathematical models were put to use for optimization. Since the effect of machining parameters on the depth of groove and height of recast layer was contradictory, The problem was explicated as a multi objective optimization problem. Moreover, An evolutionary Non-dominated sorting genetic algorithm (NSGA-II) was employed to optimize the model established by RSM. Subsequently this algorithm was also adapted to achieve the Pareto optimal set of solutions that provide a detailed illustration for making the optimal solutions. Eventually experiments were conducted to affirm the results obtained from RSM and NSGA-II.

Keywords: Laser Micro Machining (LMM), depth of groove, Height of recast layer, Response Surface Methodology (RSM), non-dominated sorting genetic algorithm

Procedia PDF Downloads 344

Authors: Si Yin Tee

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Bimetallic nanostructures have received tremendous interests as a new class of nanomaterials which may have better technological usefulness with distinct properties from those of individual atoms and molecules or bulk matter. They excelled over the monometallic counterparts because of their improved electronic, optical and catalytic performances. The properties and the applicability of these bimetallic nanostructures not only depend on their size and shape, but also on the composition and their fine structure. These bimetallic nanostructures are potential candidates for bio-applications such as biosensing, bioimaging, biodiagnostics, drug delivery, targeted therapeutics, and tissue engineering. Herein, gold-incorporated copper (Cu/Au) nanostructures were synthesized through the controlled disproportionation of Cu⁺-oleylamine complex at 220 ºC to form copper nanowires and the subsequent reaction with Au³⁺ at different temperatures of 140, 220 and 300 ºC. This is to achieve their synergistic effect through the combined use of the merits of low-cost transition and high-stability noble metals. Of these Cu/Au nanostructures, Cu/Au nanotubes display the best performance towards electrochemical non-enzymatic glucose sensing, originating from the high conductivity of gold and the high aspect ratio copper nanotubes with high surface area so as to optimise the electroactive sites and facilitate mass transport. In addition to high sensitivity and fast response, the Cu/Au nanotubes possess high selectivity against interferences from other potential interfering species and excellent reproducibility with long-term stability. By introducing gold into copper nanostructures at a low level of 3, 1 and 0.1 mol% relative to initial copper precursor, a significant electrocatalytic enhancement of the resulting bimetallic Cu/Au nanostructures starts to occur at 1 mol%. Overall, the present fabrication of stable Cu/Au nanostructures offers a promising low-cost platform for sensitive, selective, reproducible and reusable electrochemical sensing of glucose.

Keywords: bimetallic, electrochemical sensing, glucose oxidation, gold-incorporated copper nanostructures

Procedia PDF Downloads 520

Authors: Yili Wang, Jarmo Kinos, Tuire Palonen, Tarja-Riitta Hurme

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This longitudinal study aims to examine how five- and six-year-old children’s peer relationships are formed and fostered during one preschool year in a southwestern Finnish preschool. All 16 kindergarteners participated in the study (at dyad level N=240; i.e., 16 x 15 relationships among the children). The children were divided into four daily groups, based on the table order during the daily routines, and four intervention groups, based on the teachers’ pedagogical plan. During the intervention, one iPad was given to each group in order to stimulate interaction among peers and, thus, enable the children to form new peer relationships. In the data gathering, sociometric nomination techniques were used to investigate the nature (i.e., stability and mutuality) of the peer relationships. The data was collected five times during the year to see what kind of peer relationship changes occurred at the dyad level and the group level, i.e., in establishing and losing friendship ties among the children. Social network analyses were used to analyze the data. The results indicate that the children’s preference for gender segregation was strong compared to age preference and intervention. In all, the number of reciprocal friendship ties and the mutual absence of friendship ties increased towards the end of the year, whereas the number of unilateral friendship ties decreased. This indicates that children’s nominations narrow down; thus, the group structure becomes more crystalized. Instead of extending their friendship networks, children seek stable and mutual relationships with their peers in their middle childhood years. The intervention only had a slightly negative influence on children’s peer relationships.

Keywords: intervention study, peer relationship, preschool education, social network analysis, sociometric ratings

Procedia PDF Downloads 272

Authors: Levent Dumenci, Laura A. Siminoff

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Health literacy has been shown to predict a variety of health outcomes. Reliable identification of persons with limited cancer health literacy (LCHL) has been proved questionable with existing instruments using an arbitrary cut point along a continuum. The CHLT-6, however, uses a latent mixture modeling approach to identify persons with LCHL. The purpose of this study was to estimate two-week and six-month stability of identifying persons with LCHL using the CHLT-6 with a discrete latent variable approach as the underlying measurement structure. Using a test-retest design, the CHLT-6 was administered to cancer patients with two-week (N=98) and six-month (N=51) intervals. The two-week and six-month latent test-retest agreements were 89% and 88%, respectively. The chance-corrected latent agreements estimated from Dumenci’s latent kappa were 0.62 (95% CI: 0.41 – 0.82) and .47 (95% CI: 0.14 – 0.80) for the two-week and six-month intervals, respectively. High levels of latent test-retest agreement between limited and adequate categories of cancer health literacy construct, coupled with moderate to good levels of change-corrected latent agreements indicated that the CHLT-6 classification of limited versus adequate cancer health literacy is relatively stable over time. In conclusion, the measurement structure underlying the instrument allows for estimating classification errors circumventing limitations due to arbitrary approaches adopted by all other instruments. The CHLT-6 can be used to identify persons with LCHL in oncology clinics and intervention studies to accurately estimate treatment effectiveness.

Keywords: limited cancer health literacy, the CHLT-6, discrete latent variable modeling, latent agreement

Procedia PDF Downloads 177