Search results for: dynamic ROI detection

Authors: Razieh Karimi Aghcheh, Christian Kubicek, Joseph Strauss, Gerhard Braus

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Filamentous fungi are of considerable economic and social significance for human health, nutrition and in white biotechnology. These organisms are dominant producers of a range of primary metabolites such as citric acid, microbial lipids (biodiesel) and higher unsaturated fatty acids (HUFAs). In particular, they produce also important but structurally complex secondary metabolites with enormous therapeutic applications in pharmaceutical industry, for example: cephalosporin, penicillin, taxol, zeranol and ergot alkaloids. Several fungal secondary metabolites, which are significantly relevant to human health do not only include antibiotics, but also e.g. lovastatin, a well-known antihypercholesterolemic agent produced by Aspergillus. terreus, or aflatoxin, a carcinogen produced by A. flavus. In addition to their roles for human health and agriculture, some fungi are industrially and commercially important: Species of the ascomycete genus Hypocrea spp. (teleomorph of Trichoderma) have been demonstrated as efficient producer of highly active cellulolytic enzymes. This trait makes them effective in disrupting and depolymerization of lignocellulosic materials and thus applicable tools in number of biotechnological areas as diverse as clothes-washing detergent, animal feed, and pulp and fuel productions. Fungal LaeA/LAE1 (Loss of aflR Expression A) homologs their gene products act at the interphase between secondary metabolisms, cellulase production and development. Lack of the corresponding genes results in significant physiological changes including loss of secondary metabolite and lignocellulose degrading enzymes production. At the molecular level, the encoded proteins are presumably methyltransferases or demethylases which act directly or indirectly at heterochromatin and interact with velvet domain proteins. Velvet proteins bind to DNA and affect expression of secondary metabolites (SMs) genes and cellulases. The dynamic interplay between LaeA/LAE1, velvet proteins and additional interaction partners is the key for an understanding of the coordination of metabolic and morphological functions of fungi and is required for a biotechnological control of the formation of desired bioactive products. Aspergilli and Trichoderma represent different biotechnologically significant species with significant differences in the LaeA/LAE1-Velvet protein machinery and their target proteins. We, therefore, performed a comparative study of the interaction partners of this machinery and the dynamics of the various protein-protein interactions using our robust proteomic and mass spectrometry techniques. This enhances our knowledge about the fungal coordination of secondary metabolism, cellulase production and development and thereby will certainly improve recombinant fungal strain construction for the production of industrial secondary metabolite or lignocellulose hydrolytic enzymes.

Keywords: cellulases, LaeA/1, proteomics, secondary metabolites

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Authors: Andreas Kerstan, Darren Robey, Wesam Alvan, David Troiani

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Over the last 3.5 years, Quantum Cascade Lasers (QCL) technology has become increasingly important in infrared (IR) microscopy. The advantages over fourier transform infrared (FTIR) are that large areas of a few square centimeters can be measured in minutes and that the light intensive QCL makes it possible to obtain spectra with excellent S/N, even with just one scan. A firmly established solution of the laser direct infrared imaging (LDIR) 8700 is the analysis of microplastics. The presence of microplastics in the environment, drinking water, and food chains is gaining significant public interest. To study their presence, rapid and reliable characterization of microplastic particles is essential. Significant technical hurdles in microplastic analysis stem from the sheer number of particles to be analyzed in each sample. Total particle counts of several thousand are common in environmental samples, while well-treated bottled drinking water may contain relatively few. While visual microscopy has been used extensively, it is prone to operator error and bias and is limited to particles larger than 300 µm. As a result, vibrational spectroscopic techniques such as Raman and FTIR microscopy have become more popular, however, they are time-consuming. There is a demand for rapid and highly automated techniques to measure particle count size and provide high-quality polymer identification. Analysis directly on the filter that often forms the last stage in sample preparation is highly desirable as, by removing a sample preparation step it can both improve laboratory efficiency and decrease opportunities for error. Recent advances in infrared micro-spectroscopy combining a QCL with scanning optics have created a new paradigm, LDIR. It offers improved speed of analysis as well as high levels of automation. Its mode of operation, however, requires an IR reflective background, and this has, to date, limited the ability to perform direct “on-filter” analysis. This study explores the potential to combine the filter with an infrared reflective surface filter. By combining an IR reflective material or coating on a filter membrane with advanced image analysis and detection algorithms, it is demonstrated that such filters can indeed be used in this way. Vibrational spectroscopic techniques play a vital role in the investigation and understanding of microplastics in the environment and food chain. While vibrational spectroscopy is widely deployed, improvements and novel innovations in these techniques that can increase the speed of analysis and ease of use can provide pathways to higher testing rates and, hence, improved understanding of the impacts of microplastics in the environment. Due to its capability to measure large areas in minutes, its speed, degree of automation and excellent S/N, the LDIR could also implemented for various other samples like food adulteration, coatings, laminates, fabrics, textiles and tissues. This presentation will highlight a few of them and focus on the benefits of the LDIR vs classical techniques.

Keywords: QCL, automation, microplastics, tissues, infrared, speed

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Authors: Ichiro Takahashi

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One conundrum that macroeconomic theory faces is to explain how an economy can revive from depression, in which the aggregate demand has fallen substantially below its productive capacity. This paper examines an autonomous stabilizing mechanism using an agent-based Wicksell-Keynes macroeconomic model. This paper focuses on the effects of the number of firms and the length of the gestation period for investment that are often assumed to be one in a mainstream macroeconomic model. The simulations found the virtual economy was highly unstable, or more precisely, collapsing when these parameters are fixed at one. This finding may even suggest us to question the legitimacy of these common assumptions. A perpetual decline in capital stock will eventually encourage investment if the capital stock is short-lived because an inactive investment will result in insufficient productive capacity. However, for an economy characterized by a roundabout production method, a gradual decline in productive capacity may not be able to fall below the aggregate demand that is also shrinking. Naturally, one would then ask if our economy cannot rely on an external stimulus such as population growth and technological progress to revive investment, what factors would provide such a buoyancy for stimulating investments? The current paper attempts to answer this question by employing the artificial macroeconomic model mentioned above. The baseline model has the following three features: (1) the multi-period gestation for investment, (2) a large number of heterogeneous firms, (3) demand-constrained firms. The instability is a consequence of the following dynamic interactions. (a) A multiple-period gestation period means that once a firm starts a new investment, it continues to invest over some subsequent periods. During these gestation periods, the excess demand created by the investing firm will spill over to ignite new investment of other firms that are supplying investment goods: the presence of multi-period gestation for investment provides a field for investment interactions. Conversely, the excess demand for investment goods tends to fade away before it develops into a full-fledged boom if the gestation period of investment is short. (b) A strong demand in the goods market tends to raise the price level, thereby lowering real wages. This reduction of real wages creates two opposing effects on the aggregate demand through the following two channels: (1) a reduction in the real labor income, and (2) an increase in the labor demand due to the principle of equality between the marginal labor productivity and real wage (referred as the Walrasian labor demand). If there is only a single firm, a lower real wage will increase its Walrasian labor demand, thereby an actual labor demand tends to be determined by the derived labor demand. Thus, the second positive effect would not work effectively. In contrast, for an economy with a large number of firms, Walrasian firms will increase employment. This interaction among heterogeneous firms is a key for stability. A single firm cannot expect the benefit of such an increased aggregate demand from other firms.

Keywords: agent-based macroeconomic model, business cycle, demand constraint, gestation period, representative agent model, stability

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Authors: Bashar Mahmoud, Lee Mortimer, Michael Fairweather

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New methods have recently been introduced to improve the thermal property values of molten nitrate salts (a binary mixture of NaNO3:KNO3in 60:40 wt. %), by doping them with minute concentration of nanoparticles in the range of 0.5 to 1.5 wt. % to form the so-called: Nano-heat-transfer-fluid, apt for thermal energy transfer and storage applications. The present study aims to assess the stability of these nanofluids using the advanced computational modelling technique, Lagrangian particle tracking. A multi-phase solid-liquid model is used, where the motion of embedded nanoparticles in the suspended fluid is treated by an Euler-Lagrange hybrid scheme with fixed time stepping. This technique enables measurements of various multi-scale forces whose characteristic (length and timescales) are quite different. Two systems are considered, both consisting of 50 nm Al2O3 ceramic nanoparticles suspended in fluids of different density ratios. This includes both water (5 to 95 °C) and molten nitrate salt (220 to 500 °C) at various volume fractions ranging between 1% to 5%. Dynamic properties of both phases are coupled to the ambient temperature of the fluid suspension. The three-dimensional computational region consists of a 1μm cube and particles are homogeneously distributed across the domain. Periodic boundary conditions are enforced. The particle equations of motion are integrated using the fourth order Runge-Kutta algorithm with a very small time-step, Δts, set at 10-11 s. The implemented technique demonstrates the key dynamics of aggregated nanoparticles and this involves: Brownian motion, soft-sphere particle-particle collisions, and Derjaguin, Landau, Vervey, and Overbeek (DLVO) forces. These mechanisms are responsible for the predictive model of aggregation of nano-suspensions. An energy transport-based method of predicting the thermal conductivity of the nanofluids is also used to determine thermal properties of the suspension. The simulation results confirms the effectiveness of the technique. The values are in excellent agreement with the theoretical and experimental data obtained from similar studies. The predictions indicates the role of Brownian motion and DLVO force (represented by both the repulsive electric double layer and an attractive Van der Waals) and its influence in the level of nanoparticles agglomeration. As to the nano-aggregates formed that was found to play a key role in governing the thermal behavior of nanofluids at various particle concentration. The presentation will include a quantitative assessment of these forces and mechanisms, which would lead to conclusions about nanofluids, heat transfer performance and thermal characteristics and its potential application in solar thermal energy plants.

Keywords: thermal energy storage, molten salt, nano-fluids, multi-scale computational modelling

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Authors: Khin Nyunt Yee, Mu Mu Thein

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Detection survey of mango seed and Pulp weevils was undertaken at major mango production areas, Yat Sauk, Taunggyi, Nyaung Shwe and Hopong Townships, in Shan State (South) of Myanmar on two mango cultivars of Sein Ta Lone and Yinkwe from May to August 2016 to coincide with fruiting season to conduct a survey of mango seed and pulp weevils population. The total numbers of 6300 fruits of both mango cultivars were sampled. Among them, 2900 fruits from 5674 fruit bearing plants were collected for Sein Ta Lone cultivar of five well managed, one unmanaged orchards and Urban in Yatsauk Twonship, 400 fruits from only one well managed orchard in Taunggyi Township, 400 fruits from two managed orchards in Nyaung Shwe Township and 400 fruits from one managed orchard in Hopong Township from May to June. 2200 fruits were collected from 4043 fruit bearing plants for Yinkwe Cultivar of four well managed orchards, one unmanaged orchards and one wild tree only in Yat Sauk Township from July to August, 2016. Fruit sample size was 200 fruits /orchard, / wild or /volunteer trees as minimum number. The pulps of all randomly sampling fruits were longitudinal cut open into three slices on each side of fruit and seed were cut longitudinally to inspect the presence of mango weevils. The collected weevils were identified up to species level at Plant Quarantine Laboratory, Plant Protection Division, Department of Agriculture, Ministry of Agriculture, Livestock and Irrigation, Yangon, Myanmar. Mango Pulp and Seed weevils were found on Sein Ta Lone Mango Cultivar in three out of four surveyed Townships except Hopong with the level of infestation ranged from 0.0% to 3.5% of fruits per Township with 0.0% to 39.0% of fruits per orchard. The highest infestation rate per township was 3.5% of fruits (n=400 fruits) in Nyaung Shwe, then, at Yat Suak, the rate was 2.47% (n=2900 fruits). A well-managed orchard at Taung Gyi had 0.75% (n=400 fruits) whereas Hopong was free 0.0% (n=400). The weevils were also recorded on Yinkwe Mango Cultivar in Yatsauk Township where the infestation level was 12.63% of fruits (n=2200) with 0.0% to 67.0% of fruits per orchard. This high level of infestation was obtained by including an absolutely non Integrated Pest Management (non IPM) orchards in both survey with the infestation rates 63.0% of fruits (n=200) and 67.0% of fruits (n=200) respectively on Yinkwe cultivar. Two different species; mango pulp weevil, Sternochetus frigitus, and mango seed weevil Sternochetus olivieri (Faust) of family Curculionidae under the order Coleoptera were recorded. Sternochetus mangiferae was not found during these surveys. Three different developmental stages of mango seed and pulp weevils: larva, pupa and adult were first detected since the first survey in 3rd week of May and mostly were recorded as adult stages in the following surveys in June, July and August The number of Mango pulp weevil was statistically higher than that of mango seed weevils at P < 0.001%. More precise surveys should be carried out national wide to detect the mango weevils.

Keywords: mango pulp weevil, Sternochetus frigitus, mango seed weevil Sternochetus olivieri, faust, Sternochetus mangiferae, fabricius, Sein Ta Lone, Yinkwe mango cultivars, Shan State (South) Myanmar

Procedia PDF Downloads 278

Authors: Shelley Zion

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This study examines the longitudinal impact (10 years) of a course for education leaders designed to encourage the development of critical consciousness surrounding issues of equity, oppression, power, and privilege. The ability to resist and challenge oppression across social and cultural contexts can be acquired through the use of transformative pedagogies that create spaces that use the practice of exploration to make connections between pervasive structural and institutional practices and race and ethnicity. This study seeks to extend this understanding by exploring the longitudinal influence of participating in a course that utilizes transformative pedagogies, course materials, exercises, and activities to encourage the practice of exploration of student experiences with racial and ethnic discrimination with the end goal of providing them with the necessary knowledge and skills that foster their ability to resist and challenge oppression and discrimination -critical action- in their lives. To this end, we use the explanatory power of the theories of critical consciousness development, sociopolitical development, and social identity construction that view exploration as a crucial practice in understanding the role ethnic and racial differences play in creating opportunities or barriers in the lives of individuals. When educators use transformative pedagogies, they create a space where students collectively explore their experiences with racial and ethnic discrimination through course readings, in-class activities, and discussions. The end goal of this exploration is twofold: first, to encourage the student’s ability to understand how differences are identified, given meaning to, and used to position them in specific places and spaces in their world; second, to scaffold students’ ability to make connections between their individual and collective differences and particular institutional and structural practices that create opportunities or barriers in their lives. Studies have found the formal exploration of students’ individual and collective differences in relation to their experiences with racial and ethnic discrimination results in developing an understanding of the roles race and ethnicity play in their lives. To trace the role played by exploration in identity construction, we utilize an integrative approach to identity construction informed by multiple theoretical frameworks grounded in cultural studies, social psychology, and sociology that understand social-cultural, racial, and ethnic -identities as dynamic and ever-changing based on context-specific environments. Stuart Hall refers to this practice as taking “symbolic detours through the past” while reflecting on the different ways individuals have been positioned based on their roots (group membership) and also how they, in turn, chose to position themselves through collective sense-making of the various meanings their differences carried through the routes they have taken. The practice of exploration in the construction of ethnic-racial identities has been found to be beneficial to sociopolitical development.

Keywords: political polarization, civic participation, democracy, education

Procedia PDF Downloads 28

Authors: Ali Ahmed Ali Al-Juboori, H. Zhu, D. Wexler, H. Li, C. Lu, J. McLeod, S. Pannila, J. Barnes

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A number of studies have focused on the formation mechanics of white etching layer and its origin in the railway operation. Until recently, the following hypotheses consider the precise mechanics of WELs formation: (i) WELs are the result of thermal process caused by wheel slip; (ii) WELs are mechanically induced by severe plastic deformation; (iii) WELs are caused by a combination of thermo-mechanical process. The mechanisms discussed above lead to occurrence of white etching layers on the area of wheel and rail contact. This is because the contact patch which is the active point of the wheel on the rail is exposed to highest shear stresses which result in localised severe plastic deformation; and highest rate of heat caused by wheel slipe during excessive traction or braking effort. However, if the WELs are not on the running band area, it would suggest that there is another cause of WELs formation. In railway system, particularly electrified railway, arcing phenomenon has been occurring more often and regularly on the rails. In electrified railway, the current is delivered to the train traction motor via contact wires and then returned to the station via the contact between the wheel and the rail. If the contact between the wheel and the rail is temporarily losing, due to dynamic vibration, entrapped dirt or water, lubricant effect or oxidation occurrences, high current can jump through the gap and results in arcing. The other resources of arcing also include the wheel passage the insulated joint and lightning on a train during bad weather. During the arcing, an extensive heat is generated and speared over a large area of top surface of rail. Thus, arcing is considered another heat source in the rail head (rather than wheel slipe) that results in microstructural changes and white etching layer formation. A head hardened (HH) rail steel, cut from a curved rail truck was used for the investigation. Samples were sectioned from a depth of 10 mm below the rail surface, where the material is considered to be still within the hardened layer but away from any microstructural changes on the top surface layer caused by train passage. These samples were subjected to electrical discharges by using Gas Tungsten Arc Welding (GTAW) machine. The arc current was controlled and moved along the samples surface in the direction of travel, as indicated by an arrow. Five different conditions were applied on the surface of the samples. Samples containing pre-existed WELs, taken from ex-service rail surface, were also considered in this study for comparison. Both simulated and ex-serviced WELs were characterised by advanced methods including SEM, TEM, TKD, EDS, XRD. Samples for TEM and TKFD were prepared by Focused Ion Beam (FIB) milling. The results showed that both simulated WELs by electrical arcing and ex-service WEL comprise similar microstructure. Brown etching layer was found with WELs and likely induced by a concurrent tempering process. This study provided a clear understanding of new formation mechanics of WELs which contributes to track maintenance procedure.

Keywords: white etching layer, arcing, brown etching layer, material characterisation

Procedia PDF Downloads 99

Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

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Authors: Domenico Carmelo Mongelli

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The context is that of great uncertainty in the 27 countries belonging to the European Union which has adopted an epochal measure: the elimination of internal combustion engines for the traction of road vehicles starting from 2035 with complete replacement with electric vehicles. If on the one hand there is great concern at various levels for the unpreparedness for this change, on the other the Scientific Community is not preparing accurate studies on the problem, as the scientific literature deals with single aspects of the issue, moreover addressing the issue at the level of individual countries, losing sight of the global implications of the issue for the entire EU. The aim of the research is to fill these gaps: the technological, plant engineering, environmental, economic and employment aspects of the energy transition in question are addressed and connected to each other, comparing the current situation with the different scenarios that could exist in 2035 and in the following years until total disposal of the internal combustion engine vehicle fleet for the entire EU. The methodologies adopted by the research consist in the analysis of the entire life cycle of electric vehicles and batteries, through the use of specific databases, and in the dynamic simulation, using specific calculation codes, of the application of the results of this analysis to the entire EU electric vehicle fleet from 2035 onwards. Energy balance sheets will be drawn up (to evaluate the net energy saved), plant balance sheets (to determine the surplus demand for power and electrical energy required and the sizing of new plants from renewable sources to cover electricity needs), economic balance sheets (to determine the investment costs for this transition, the savings during the operation phase and the payback times of the initial investments), the environmental balances (with the different energy mix scenarios in anticipation of 2035, the reductions in CO2eq and the environmental effects are determined resulting from the increase in the production of lithium for batteries), the employment balances (it is estimated how many jobs will be lost and recovered in the reconversion of the automotive industry, related industries and in the refining, distribution and sale of petroleum products and how many will be products for technological innovation, the increase in demand for electricity, the construction and management of street electric columns). New algorithms for forecast optimization are developed, tested and validated. Compared to other published material, the research adds an overall picture of the energy transition, capturing the advantages and disadvantages of the different aspects, evaluating the entities and improvement solutions in an organic overall picture of the topic. The results achieved allow us to identify the strengths and weaknesses of the energy transition, to determine the possible solutions to mitigate these weaknesses and to simulate and then evaluate their effects, establishing the most suitable solutions to make this transition feasible.

Keywords: engines, Europe, mobility, transition

Procedia PDF Downloads 38

Authors: Alexander Harrison Greer, Edward King, Elijah Lee, Safa Obuz, Ruhao Sun, Aditya Sardesai, Toby Ma, Daniel Chow, Bryce Broadus, Calvin Costner, Troy Barnes, Biagio DeSimone, Yeshwin Sankuratri, Yiheng Chen, Holly Golecki

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Although a relatively new field, soft robotics is experiencing a rise in applicability in the secondary school setting through The Soft Robotics Toolkit, shared fabrication resources and a design competition. Exposing students outside of university research groups to this rapidly growing field allows for development of the soft robotics industry in new and imaginative ways. Soft robotic actuators have remained difficult to implement in classrooms because of their relative cost or difficulty of fabrication. Traditionally, a two-part molding system is used; however, this configuration often results in delamination. In an effort to make soft robotics more accessible to young students, we aim to develop a simple, single-mold method of fabricating soft robotic actuators from common household materials. These actuators are made by embedding a soluble polymer insert into silicone. These inserts can be made from hand-cut polystyrene, 3D-printed polyvinyl alcohol (PVA) or acrylonitrile butadiene styrene (ABS), or molded sugar. The insert is then dissolved using an appropriate solvent such as water or acetone, leaving behind a negative form which can be pneumatically actuated. The resulting actuators are seamless, eliminating the instability of adhering multiple layers together. The benefit of this approach is twofold: it simplifies the process of creating a soft robotic actuator, and in turn, increases its effectiveness and durability. To quantify the increased durability of the single-mold actuator, it was tested against the traditional two-part mold. The single-mold actuator could withstand actuation at 20psi for 20 times the duration when compared to the traditional method. The ease of fabrication of these actuators makes them more accessible to hobbyists and students in classrooms. After developing these actuators, they were applied, in collaboration with a ceramics teacher at our school, to a glove used to transfer nuanced hand motions used to throw pottery from an expert artist to a novice. We quantified the improvement in the users’ pottery-making skill when wearing the glove using image analysis software. The seamless actuators proved to be robust in this dynamic environment. Seamless soft robotic actuators created by high school students show the applicability of the Soft Robotics Toolkit for secondary STEM education and outreach. Making students aware of what is possible through projects like this will inspire the next generation of innovators in materials science and robotics.

Keywords: pneumatic actuator fabrication, soft robotic glove, soluble polymers, STEM outreach

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Authors: Margherita Tufarelli, Leonardo Giliberti, Elena Pucci

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The fashion industry's interest in virtuality is linked, on the one hand, to the emotional and immersive possibilities of digital resources and the resulting languages and, on the other, to the greater efficiency that can be achieved throughout the value chain. The interaction between digital innovation and deep-rooted manufacturing traditions today translates into a paradigm shift for the entire fashion industry where, for example, the traditional values of industrial secrecy and know-how give way to experimentation in an open as well as participatory way, and the complete emancipation of virtual reality from actual 'reality'. The contribution aims to investigate the theme of digitisation in the Italian fashion industry, analysing its opportunities and the criticalities that have hindered its diffusion. There are two reasons why the most common approach in the fashion sector is still analogue: (i) the fashion product lives in close contact with the human body, so the sensory perception of materials plays a central role in both the use and the design of the product, but current technology is not able to restore the sense of touch; (ii) volumes are obtained by stitching flat surfaces that once assembled, given the flexibility of the material, can assume almost infinite configurations. Managing the fit and styling of virtual garments involves a wide range of factors, including mechanical simulation, collision detection, and user interface techniques for garment creation. After briefly reviewing some of the salient historical milestones in the resolution of problems related to the digital simulation of deformable materials and the user interface for the procedures for the realisation of the clothing system, the paper will describe the operation and possibilities offered today by the latest generation of specialised software. Parametric avatars and digital sartorial approach; drawing tools optimised for pattern making; materials both from the point of view of simulated physical behaviour and of aesthetic performance, tools for checking wearability, renderings, but also tools and procedures useful to companies both for dialogue with prototyping software and machinery and for managing the archive and the variants to be made. The article demonstrates how developments in technology and digital procedures now make it possible to intervene in different stages of design in the fashion industry. An integrated and additive process in which the constructed 3D models are usable both in the prototyping and communication of physical products and in the possible exclusively digital uses of 3D models in the new generation of virtual spaces. Mastering such tools requires the acquisition of specific digital skills and, at the same time, traditional skills for the design of the clothing system, but the benefits are manifold and applicable to different business dimensions. We are only at the beginning of the global digital transformation: the emergence of new professional figures and design dynamics leaves room for imagination, but in addition to applying digital tools to traditional procedures, traditional fashion know-how needs to be transferred into emerging digital practices to ensure the continuity of the technical-cultural heritage beyond the transformation.

Keywords: digital fashion, digital technology and couture, digital fashion communication, 3D garment simulation

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Authors: Elias Jemal Abdella

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The Blue Nile River is an important shared resource of Ethiopia, Sudan and also, because it is the major contributor of water to the main Nile River, Egypt. Despite the potential benefits of regional cooperation and integrated joint basin management, all three countries continue to pursue unilateral plans for development. Besides, there is great uncertainty about the likely impacts of climate change in water availability for existing as well as proposed irrigation and hydropower projects in the Blue Nile Basin. The main objective of this study is to quantitatively assess the impact of climate change on the hydrological regime of the upper Blue Nile basin, western Ethiopia. Three models were combined, a dynamic Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate model (RCM) that is used to determine climate projections for the Upper Blue Nile basin for Representative Concentration Pathways (RCPs) 4.5 and 8.5 greenhouse gas emissions scenarios for the period 2021-2050. The outputs generated from multimodel ensemble of four (4) CORDEX-RCMs (i.e., rainfall and temperature) were used as input to a Soil and Water Assessment Tool (SWAT) hydrological model which was setup, calibrated and validated with observed climate and hydrological data. The outputs from the SWAT model (i.e., projections in river flow) were used as input to a Water Evaluation and Planning (WEAP) water resources model which was used to determine the water resources implications of the changes in climate. The WEAP model was set-up to simulate three development scenarios. Current Development scenario was the existing water resource development situation, Medium-term Development scenario was planned water resource development that is expected to be commissioned (i.e. before 2025) and Long-term full Development scenario were all planned water resource development likely to be commissioned (i.e. before 2050). The projected change of mean annual temperature for period (2021 – 2050) in most of the basin are warmer than the baseline (1982 -2005) average in the range of 1 to 1.4oC, implying that an increase in evapotranspiration loss. Subbasins which already distressed from drought may endure to face even greater challenges in the future. Projected mean annual precipitation varies from subbasin to subbasin; in the Eastern, North Eastern and South western highland of the basin a likely increase of mean annual precipitation up to 7% whereas in the western lowland part of the basin mean annual precipitation projected to decrease by 3%. The water use simulation indicates that currently irrigation demand in the basin is 1.29 Bm3y-1 for 122,765 ha of irrigation area. By 2025, with new schemes being developed, irrigation demand is estimated to increase to 2.5 Bm3y-1 for 277,779 ha. By 2050, irrigation demand in the basin is estimated to increase to 3.4 Bm3y-1 for 372,779 ha. The hydropower generation simulation indicates that 98 % of hydroelectricity potential could be produced if all planned dams are constructed.

Keywords: Blue Nile River, climate change, hydropower, SWAT, WEAP

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Authors: Massimo Ferrari, Maria Sole Pagliari

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Pollution is a classic example of economic externality: agents who produce it do not face direct costs from emissions. Therefore, there are no direct economic incentives for reducing pollution. One way to address this market failure would be directly taxing emissions. However, because emissions are global, governments might as well find it optimal to wait let foreign countries to tax emissions so that they can enjoy the benefits of lower pollution without facing its direct costs. In this paper, we first document the empirical relation between pollution and economic output with static and dynamic regression methods. We show that there is a negative relation between aggregate output and the stock of pollution (measured as the stock of CO₂ emissions). This relationship is also highly non-linear, increasing at an exponential rate. In the second part of the paper, we develop and estimate a two-country, two-sector model for the US and the euro area. With this model, we aim at analyzing how the public sector should respond to higher emissions and what are the direct costs that these policies might have. In the model, there are two types of firms, brown firms (which produce a polluting technology) and green firms. Brown firms also produce an externality, CO₂ emissions, which has detrimental effects on aggregate output. As brown firms do not face direct costs from polluting, they do not have incentives to reduce emissions. Notably, emissions in our model are global: the stock of CO₂ in the economy affects all countries, independently from where it is produced. This simplified economy captures the main trade-off between emissions and production, generating a classic market failure. According to our results, the current level of emission reduces output by between 0.4 and 0.75%. Notably, these estimates lay in the upper bound of the distribution of those delivered by studies in the early 2000s. To address market failure, governments should step in introducing taxes on emissions. With the tax, brown firms pay a cost for polluting hence facing the incentive to move to green technologies. Governments, however, might also adopt a beggar-thy-neighbour strategy. Reducing emissions is costly, as moves production away from the 'optimal' production mix of brown and green technology. Because emissions are global, a government could just wait for the other country to tackle climate change, ripping the benefits without facing any costs. We study how this strategic game unfolds and show three important results: first, cooperation is first-best optimal from a global prospective; second, countries face incentives to deviate from the cooperating equilibria; third, tariffs on imported brown goods (the only retaliation policy in case of deviation from the cooperation equilibrium) are ineffective because the exchange rate would move to compensate. We finally study monetary policy under when costs for climate change rise and show that the monetary authority should react stronger to deviations of inflation from its target.

Keywords: climate change, general equilibrium, optimal taxation, monetary policy

Procedia PDF Downloads 133

Authors: Jinlu Ruan, Liang Chen, Bo Liu, Xiaoping Ouyang, Zhichao Zhu, Zhongbing Zhang, Shiyi He, Mengxuan Xu

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Plastic scintillators play an important role in the measurement of a mixed neutron/gamma pulsed radiation, neutron radiography and pulse shape discrimination technology. In some research, these luminescent properties are necessary that photons produced by the interactions between a plastic scintillator and radiations can be detected as much as possible by the photoelectric detectors and more photons can be emitted from the scintillators along a specific direction where detectors are located. Unfortunately, a majority of these photons produced are trapped in the plastic scintillators due to the total internal reflection (TIR), because there is a significant light-trapping effect when the incident angle of internal scintillation light is larger than the critical angle. Some of these photons trapped in the scintillator may be absorbed by the scintillator itself and the others are emitted from the edges of the scintillator. This makes the light extraction of plastic scintillators very low. Moreover, only a small portion of the photons emitted from the scintillator easily can be detected by detectors effectively, because the distribution of the emission directions of this portion of photons exhibits approximate Lambertian angular profile following a cosine emission law. Therefore, enhancing the light extraction efficiency and adjusting the emission angular profile become the keys for improving the number of photons detected by the detectors. In recent years, photonic crystal structures have been covered on inorganic scintillators to enhance the light extraction efficiency and adjust the angular profile of scintillation light successfully. However, that, preparation methods of photonic crystals will deteriorate performance of plastic scintillators and even destroy the plastic scintillators, makes the investigation on preparation methods of photonic crystals for plastic scintillators and luminescent properties of plastic scintillators with photonic crystal structures inadequate. Although we have successfully made photonic crystal structures covered on the surface of plastic scintillators by a modified self-assembly technique and achieved a great enhance of light extraction efficiency without evident angular-dependence for the angular profile of scintillation light, the preparation of photonic crystal structures with large area (the diameter is larger than 6cm) and perfect periodic structure is still difficult. In this paper, large area photonic crystals on the surface of scintillators were prepared by nanoimprint lithography firstly, and then a conformal layer with material of high refractive index on the surface of photonic crystal by atomic layer deposition technique in order to enhance the stability of photonic crystal structures and increase the number of leaky modes for improving the light extraction efficiency. The luminescent properties of the plastic scintillator with photonic crystals prepared by the mentioned method are compared with those of the plastic scintillator without photonic crystal. The results indicate that the number of photons detected by detectors is increased by the enhanced light extraction efficiency and the angular profile of scintillation light exhibits evident angular-dependence for the scintillator with photonic crystals. The mentioned preparation of photonic crystals is beneficial to scintillation detection applications and lays an important technique foundation for the plastic scintillators to meet special requirements under different application backgrounds.

Keywords: angular profile, atomic layer deposition, light extraction efficiency, plastic scintillator, photonic crystal

Procedia PDF Downloads 170

Authors: S. A. Krutovertsev, A. E. Tarasova, L. S. Krutovertseva, O. M. Ivanova

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The aim of the work was to get stable sensitive films with good sensitivity to ethanolamine (C2H7NO) in air. Ethanolamine is used as adsorbent in different processes of gas purification and separation. Besides it has wide industrial application. Chemical sensors of sorption type are widely used for gas analysis. Their behavior is determined by sensor characteristics of sensitive sorption layer. Forming conditions and characteristics of chemical gas sensors based on nanostructured modified silica films activated by different admixtures have been studied. As additives molybdenum containing polyoxometalates of the eighteen series were incorporated in silica films. The method of hydrolythic polycondensation from tetraethyl orthosilicate solutions was used for forming such films in this work. The method’s advantage is a possibility to introduce active additives directly into an initial solution. This method enables to obtain sensitive thin films with high specific surface at room temperature. Particular properties make polyoxometalates attractive as active additives for forming of gas-sensitive films. As catalyst of different redox processes, they can either accelerate the reaction of the matrix with analyzed gas or interact with it, and it results in changes of matrix’s electrical properties Polyoxometalates based films were deposited on the test structures manufactured by microelectronic planar technology with interdigitated electrodes. Modified silica films were deposited by a casting method from solutions based on tetraethyl orthosilicate and polyoxometalates. Polyoxometalates were directly incorporated into initial solutions. Composite nanostructured films were deposited by drop casting method on test structures with a pair of interdigital metal electrodes formed at their surface. The sensor’s active area was 4.0 x 4.0 mm, and electrode gap was egual 0.08 mm. Morphology of the layers surface were studied with Solver-P47 scanning probe microscope (NT-MDT, Russia), the infrared spectra were investigated by a Bruker EQUINOX 55 (Germany). The conditions of film formation varied during the tests. Electrical parameters of the sensors were measured electronically in real-time mode. Films had highly developed surface with value of 450 m2/g and nanoscale pores. Thickness of them was 0,2-0,3 µm. The study shows that the conditions of the environment affect markedly the sensors characteristics, which can be improved by choosing of the right procedure of forming and processing. Addition of polyoxometalate into silica film resulted in stabilization of film mass and changed markedly of electrophysical characteristics. Availability of Mn3P2Mo18O62 into silica film resulted in good sensitivity and selectivity to ethanolamine. Sensitivity maximum was observed at weight content of doping additive in range of 30–50% in matrix. With ethanolamine concentration changing from 0 to 100 ppm films’ conductivity increased by 10-12 times. The increase of sensor’s sensitivity was received owing to complexing reaction of tested substance with cationic part of polyoxometalate. This fact results in intramolecular redox reaction which sharply change electrophysical properties of polyoxometalate. This process is reversible and takes place at room temperature.

Keywords: ethanolamine, gas analysis, polyoxometalate, silica film

Procedia PDF Downloads 190

Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

Procedia PDF Downloads 90

Authors: Ignitia Motjolopane

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Small and medium enterprises (SMEs) play an important role in economies by contributing to economic growth and employment. In the fourth industrial revolution, the convergence of technologies and the changing nature of work created pressures on economies globally. Generative artificial intelligence (AI) may support SMEs in exploring, exploiting, and transforming business models to align with their growth aspirations. SMEs' growth aspirations fall into four categories: subsistence, income, growth, and speculative. Subsistence-oriented firms focus on meeting basic financial obligations and show less motivation for business model innovation. SMEs focused on income, growth, and speculation are more likely to pursue business model innovation to support growth strategies. SMEs' strategic goals link to distinct business model innovation paths depending on whether SMEs are starting a new business, pursuing growth, or seeking profitability. Integrating generative artificial intelligence in start-up SME business model innovation enhances value creation, user-oriented innovation, and SMEs' ability to adapt to dynamic changes in the business environment. The existing literature may lack comprehensive frameworks and guidelines for effectively integrating generative AI in start-up reiterative business model innovation paths. This paper examines start-up business model innovation path with generative artificial intelligence. A theoretical approach is used to examine start-up-focused SME reiterative business model innovation path with generative AI. Articulating how generative AI may be used to support SMEs to systematically and cyclically build the business model covering most or all business model components and analyse and test the BM's viability throughout the process. As such, the paper explores generative AI usage in market exploration. Moreover, market exploration poses unique challenges for start-ups compared to established companies due to a lack of extensive customer data, sales history, and market knowledge. Furthermore, the paper examines the use of generative AI in developing and testing viable value propositions and business models. In addition, the paper looks into identifying and selecting partners with generative AI support. Selecting the right partners is crucial for start-ups and may significantly impact success. The paper will examine generative AI usage in choosing the right information technology, funding process, revenue model determination, and stress testing business models. Stress testing business models validate strong and weak points by applying scenarios and evaluating the robustness of individual business model components and the interrelation between components. Thus, the stress testing business model may address these uncertainties, as misalignment between an organisation and its environment has been recognised as the leading cause of company failure. Generative AI may be used to generate business model stress-testing scenarios. The paper is expected to make a theoretical and practical contribution to theory and approaches in crafting a robust business model innovation path with generative artificial intelligence in start-up SMEs.

Keywords: business models, innovation, generative AI, small medium enterprises

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Authors: Aliya K. Salahova

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Scientific thinking, characterized by purposeful knowledge-seeking and the harmonization of theory and facts, holds a crucial role in preparing young minds for an increasingly complex and technologically advanced world. This abstract presents a research study aimed at fostering scientific thinking in early childhood, focusing on children aged 5 to 9 years, through experiential learning in Kids Science Labs (STEM). The study utilized a longitudinal exploration design, spanning 240 weeks from September 2018 to April 2023, to evaluate the effectiveness of the Kids Science Labs program in developing scientific thinking skills. Participants in the research comprised 72 children drawn from local schools and community organizations. Through a formative psychology-pedagogical experiment, the experimental group engaged in weekly STEM activities carefully designed to stimulate scientific thinking, while the control group participated in daily art classes for comparison. To assess the scientific thinking abilities of the participants, a registration table with evaluation criteria was developed. This table included indicators such as depth of questioning, resource utilization in research, logical reasoning in hypotheses, procedural accuracy in experiments, and reflection on research processes. The data analysis revealed dynamic fluctuations in the number of children at different levels of scientific thinking proficiency. While the development was not uniform across all participants, a main leading factor emerged, indicating that the Kids Science Labs program and formative experiment exerted a positive impact on enhancing scientific thinking skills in children within this age range. The study's findings support the hypothesis that systematic implementation of STEM activities effectively promotes and nurtures scientific thinking in children aged 5-9 years. Enriching education with a specially planned STEM program, tailoring scientific activities to children's psychological development, and implementing well-planned diagnostic and corrective measures emerged as essential pedagogical conditions for enhancing scientific thinking abilities in this age group. The results highlight the significant and positive impact of the systematic-activity approach in developing scientific thinking, leading to notable progress and growth in children's scientific thinking abilities over time. These findings have promising implications for educators and researchers, emphasizing the importance of incorporating STEM activities into educational curricula to foster scientific thinking from an early age. This study contributes valuable insights to the field of science education and underscores the potential of STEM-based interventions in shaping the future scientific minds of young children.

Keywords: Scientific thinking, education, STEM, intervention, Psychology, Pedagogy, collaborative learning, longitudinal study

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Authors: Farzan Gity, Lida Ansari, Ian M. Povey, Roger E. Nagle, James C. Greer

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Titanium nitride (TiN) films have been widely used in variety of fields, due to its unique electrical, chemical, physical and mechanical properties, including low electrical resistivity, chemical stability, and high thermal conductivity. In microelectronic devices, thin continuous TiN films are commonly used as diffusion barrier and metal gate material. However, as the film thickness decreases below a few nanometers, electrical properties of the film alter considerably. In this study, the physical and electrical characteristics of 1.5nm to 22nm thin films deposited by Plasma-Enhanced Atomic Layer Deposition (PE-ALD) using Tetrakis(dimethylamino)titanium(IV), (TDMAT) chemistry and Ar/N2 plasma on 80nm SiO2 capped in-situ by 2nm Al2O3 are investigated. ALD technique allows uniformly-thick films at monolayer level in a highly controlled manner. The chemistry incorporates low level of oxygen into the TiN films forming titanium oxynitride (TiON). Thickness of the films is characterized by Transmission Electron Microscopy (TEM) which confirms the uniformity of the films. Surface morphology of the films is investigated by Atomic Force Microscopy (AFM) indicating sub-nanometer surface roughness. Hall measurements are performed to determine the parameters such as carrier mobility, type and concentration, as well as resistivity. The >5nm-thick films exhibit metallic behavior; however, we have observed that thin film resistivity is modulated significantly by film thickness such that there are more than 5 orders of magnitude increment in the sheet resistance at room temperature when comparing 5nm and 1.5nm films. Scattering effects at interfaces and grain boundaries could play a role in thickness-dependent resistivity in addition to quantum confinement effect that could occur at ultra-thin films: based on our measurements the carrier concentration is decreased from 1.5E22 1/cm3 to 5.5E17 1/cm3, while the mobility is increased from < 0.1 cm2/V.s to ~4 cm2/V.s for the 5nm and 1.5nm films, respectively. Also, measurements at different temperatures indicate that the resistivity is relatively constant for the 5nm film, while for the 1.5nm film more than 2 orders of magnitude reduction has been observed over the range of 220K to 400K. The activation energy of the 2.5nm and 1.5nm films is 30meV and 125meV, respectively, indicating that the TiON ultra-thin films are exhibiting semiconducting behaviour attributing this effect to a metal-semiconductor transition. By the same token, the contact is no longer Ohmic for the thinnest film (i.e., 1.5nm-thick film); hence, a modified lift-off process was developed to selectively deposit thicker films allowing us to perform electrical measurements with low contact resistance on the raised contact regions. Our atomic scale simulations based on molecular dynamic-generated amorphous TiON structures with low oxygen content confirm our experimental observations indicating highly n-type thin films.

Keywords: activation energy, ALD, metal-semiconductor transition, resistivity, titanium oxynitride, ultra-thin film

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Authors: N. Rambabu, H. Gururaj, Reynold Washington, Oommen George

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Motivation: Under the USAID Strengthening Health Outcomes through Private Sector (SHOPS-TB) initiative, Karnataka Health Promotion Trust (KHPT) with technical support of Abt associates is implementing a TB prevention and care model in Karnataka State, South India. KHPT is the interface agency between the public and private sectors, and providers and the target community facilitating early TB case detection and enhancing treatment compliance through private health care providers (pHCP) engagement in RNTCP. The project coverage is 0.84 million urban poor from 663 slums in 12 districts of Karnataka. Problem Statement: India with the highest burden of global TB (26%) and two million cases annually, accounts for approximately one fifth of the global incidence. WHO estimates 300,000 people die from TB annually in India. India expanded the coverage of Directly Observed Treatment, Short-course chemotherapy (DOTS) to the entire country as early as 2006. However, the performance of RNTCP has not been uniform across states. While the national annual new smear-positive (NSP) case notification rate is 53, it is much lower at 47 in Karnataka. A third of TB patients in India reside in urban slums. Approach: Under SHOPS, KHPT actively engages with communities through key opinion leaders and community structures. Interpersonal communication, by Outreach workers through house-to-house visits and at aggregation points, is the primary method used for communication about TB and its management and to increase demand for sputum examination and DOTS. pHCP are mapped, trained and mentored by KHPT. ORWs also provide patient and family counseling on TB treatment, side effects and adherence, screen close contacts of index patients especially children under 6 years of age and screen co-morbidities including HIV, diabetes and malnutrition and risk factors including alcoholism, tobacco use, occupational hazards making appropriate accompanied or documented referrals. A treatment ‘buddy’ system for the patients involving close friends or family members, ICT-based support, DOTS Prerana (inspiration) groups of TB patients, family members and community, DOTS Mitra (friend) helpline services are also used for care and support services. Results: The intervention educated 39988 slum dwellers, referred 1731 chest symptomatics, tested 1061 patients and initiated 248 patients on anti-TB treatment within three months of intervention through continuous community engagement. Conclusions: The intervention’s potential to increase access to preferred health care providers, reduce patient and health system delays in diagnosis and initiation of treatment, improve health seeking behaviour and enhance compliance of pHCPs to standard treatment protocols is being monitored. Initial results are promising.

Keywords: DOTS, KHPT, health outcomes, public and private sector

Procedia PDF Downloads 294

Authors: Jara Kaye S. Villanueva, M. Rosario Concepcion O. Ang

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For the past few years, Philippines has depended most of its energy source on oil, coal, and fossil fuel. According to the Department of Energy (DOE), the dominance of coal in the energy mix will continue until the year 2020. The expanding energy needs in the country have led to increasing efforts to promote and develop renewable energy. This research is a part of the government initiative in preparation for renewable energy development and expansion in the country. The Philippine Renewable Energy Resource Mapping from Light Detection and Ranging (LiDAR) Surveys is a three-year government project which aims to assess and quantify the renewable energy potential of the country and to put them into usable maps. This study focuses on the site suitability analysis of the four renewable energy sources – biomass (coconut, corn, rice, and sugarcane), hydro, solar, and wind energy. The site assessment is a key component in determining and assessing the most suitable locations for the construction of renewable energy power plants. This method maximizes the use of both the technical methods in resource assessment, as well as taking into account the environmental, social, and accessibility aspect in identifying potential sites by utilizing and integrating two different methods: the Multi-Criteria Decision Analysis (MCDA) method and Geographic Information System (GIS) tools. For the MCDA, Analytical Hierarchy Processing (AHP) is employed to determine the parameters needed for the suitability analysis. To structure these site suitability parameters, various experts from different fields were consulted – scientists, policy makers, environmentalists, and industrialists. The need to have a well-represented group of people to consult with is relevant to avoid bias in the output parameter of hierarchy levels and weight matrices. AHP pairwise matrix computation is utilized to derive weights per level out of the expert’s gathered feedback. Whereas from the threshold values derived from related literature, international studies, and government laws, the output values were then consulted with energy specialists from the DOE. Geospatial analysis using GIS tools translate this decision support outputs into visual maps. Particularly, this study uses Euclidean distance to compute for the distance values of each parameter, Fuzzy Membership algorithm which normalizes the output from the Euclidean Distance, and the Weighted Overlay tool for the aggregation of the layers. Using the Natural Breaks algorithm, the suitability ratings of each of the map are classified into 5 discrete categories of suitability index: (1) not suitable (2) least suitable, (3) suitable, (4) moderately suitable, and (5) highly suitable. In this method, the classes are grouped based on the best groups similar values wherein each subdivision are set from the rest based on the big difference in boundary values. Results show that in the entire Philippine area of responsibility, biomass has the highest suitability rating with rice as the most suitable at 75.76% suitability percentage, whereas wind has the least suitability percentage with score 10.28%. Solar and Hydro fall in the middle of the two, with suitability values 28.77% and 21.27%.

Keywords: site suitability, biomass energy, hydro energy, solar energy, wind energy, GIS

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Authors: F. Infante, W. Kaal, S. Perfetto, S. Herold

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In the last decade the demand of wireless sensors and low-power electric devices for condition monitoring in mechanical structures has been strongly increased. Networks of wireless sensors can potentially be applied in a huge variety of applications. Due to the reduction of both size and power consumption of the electric components and the increasing complexity of mechanical systems, the interest of creating dense nodes sensor networks has become very salient. Nevertheless, with the development of large sensor networks with numerous nodes, the critical problem of powering them is drawing more and more attention. Batteries are not a valid alternative for consideration regarding lifetime, size and effort in replacing them. Between possible alternative solutions for durable power sources useable in mechanical components, vibrations represent a suitable source for the amount of power required to feed a wireless sensor network. For this purpose, energy harvesting from structural vibrations has received much attention in the past few years. Suitable vibrations can be found in numerous mechanical environments including automotive moving structures, household applications, but also civil engineering structures like buildings and bridges. Similarly, a dynamic vibration absorber (DVA) is one of the most used devices to mitigate unwanted vibration of structures. This device is used to transfer the primary structural vibration to the auxiliary system. Thus, the related energy is effectively localized in the secondary less sensitive structure. Then, the additional benefit of harvesting part of the energy can be obtained by implementing dedicated components. This paper describes the design process of an energy harvesting tuned vibration absorber (EHTVA) for rotating systems using piezoelectric elements. The energy of the vibration is converted into electricity rather than dissipated. The device proposed is indeed designed to mitigate torsional vibrations as with a conventional rotational TVA, while harvesting energy as a power source for immediate use or storage. The resultant rotational multi degree of freedom (MDOF) system is initially reduced in an equivalent single degree of freedom (SDOF) system. The Den Hartog’s theory is used for evaluating the optimal mechanical parameters of the initial DVA for the SDOF systems defined. The performance of the TVA is operationally assessed and the vibration reduction at the original resonance frequency is measured. Then, the design is modified for the integration of active piezoelectric patches without detuning the TVA. In order to estimate the real power generated, a complex storage circuit is implemented. A DC-DC step-down converter is connected to the device through a rectifier to return a fixed output voltage. Introducing a big capacitor, the energy stored is measured at different frequencies. Finally, the electromechanical prototype is tested and validated achieving simultaneously reduction and harvesting functions.

Keywords: energy harvesting, piezoelectricity, torsional vibration, vibration absorber

Procedia PDF Downloads 118

Authors: A. Rahim Baharudin, Nor Arinee binti Mat Saaud, Muhammad Afiq Azman, Farah Adiba A. Sani

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Objectives: This paper shares the case study on the engineering analysis, data analysis, and real-time data comparison for qualifying the stand wires' minimum breaking load and safe working load upon loadout operation for a new project and, at the same time, eliminate the risk due to discrepancies and unalignment of COMPANY Technical Standards to Industry Standards and Practices. This paper demonstrates “Lean Construction” for COMPANY’s Project by sustaining fit-for-purpose Technical Requirements of Loadout Strand Wire Factor of Safety (F.S). The case study utilizes historical engineering data from a few loadout operations by skidding methods from different projects. It is also demonstrating and qualifying the skidding wires' minimum breaking load and safe working load used for loadout operation for substructure and other facilities for the future. Methods: Engineering analysis and comparison of data were taken as referred to the international standard and internal COMPANY standard requirements. Data was taken from nine (9) previous projects for both topsides and jacket facilities executed at the several local fabrication yards where load out was conducted by three (3) different service providers with emphasis on four (4) basic elements: i) Industry Standards for Loadout Engineering and Operation Reference: COMPANY internal standard was referred to superseded documents of DNV-OS-H201 and DNV/GL 0013/ND. DNV/GL 0013/ND and DNVGL-ST-N001 do not mention any requirements of Strand Wire F.S of 4.0 for Skidding / Pulling Operations. ii) Reference to past Loadout Engineering and Execution Package: Reference was made to projects delivered by three (3) major offshore facilities operators. Strand Wire F.S observed ranges from 2.0 MBL (Min) to 2.5 MBL (Max). No Loadout Operation using the requirements of 4.0 MBL was sighted from the reference. iii) Strand Jack Equipment Manufacturer Datasheet Reference: Referring to Strand Jack Equipment Manufactured Datasheet by different loadout service providers, it is shown that the Designed F.S for the equipment is also ranging between 2.0 ~ 2.5. Eight (8) Strand Jack Datasheet Model was referred to, ranging from 15 Mt to 850 Mt Capacity; however, there are NO observations of designed F.S 4.0 sighted. iv) Site Monitoring on Actual Loadout Data and Parameter: Max Load on Strand Wire was captured during 2nd Breakout, which is during Static Condition of 12.9 MT / Strand Wire (67.9% Utilization). Max Load on Strand Wire for Dynamic Conditions during Step 8 and Step 12 is 9.4 Mt / Strand Wire (49.5% Utilization). Conclusion: This analysis and study demonstrated the adequacy of strand wires supplied by the service provider were technically sufficient in terms of strength, and via engineering analysis conducted, the minimum breaking load and safe working load utilized and calculated for the projects were satisfied and operated safely for the projects. It is recommended from this study that COMPANY’s technical requirements are to be revised for future projects’ utilization.

Keywords: construction, load out, minimum breaking load, safe working load, strand jacking, skidding

Procedia PDF Downloads 81

Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

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The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

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Authors: Animesh Pan, Geoffrey D. Bothun

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With the development of nanotechnology, research in multifunctional delivery systems has a new pace and dimension. An incipient challenge is to design an all-in-one delivery system that can be used for multiple purposes, including tumor targeting therapy, radio-frequency (RF-), near-infrared (NIR-), light-, or pH-induced controlled release, photothermal therapy (PTT), photodynamic therapy (PDT), and medical diagnosis. In this regard, various inorganic nanoparticles (NPs) are known to show great potential as the 'functional components' because of their fascinating and tunable physicochemical properties and the possibility of multiple theranostic modalities from individual NPs. Magnetic, luminescent, and plasmonic properties are the three most extensively studied and, more importantly biomedically exploitable properties of inorganic NPs. Although successful attempts of combining any two of them above mentioned functionalities have been made, integrating them in one system has remained challenge. Keeping those in mind, controlled designs of complex colloidal nanoparticle system are one of the most significant challenges in nanoscience and nanotechnology. Therefore, systematic and planned studies providing better revelation are demanded. We report a multifunctional delivery platform-based liposome loaded with drug, iron-oxide magnetic nanoparticles (MNPs), and a gold shell on the surface of liposomes, were synthesized using a lipid with polyelectrolyte (layersomes) templating technique. MNPs and the anti-cancer drug doxorubicin (DOX) were co-encapsulated inside liposomes composed by zwitterionic phophatidylcholine and anionic phosphatidylglycerol using reverse phase evaporation (REV) method. The liposomes were coated with positively charge polyelectrolyte (poly-L-lysine) to enrich the interface with gold anion, exposed to a reducing agent to form a gold nanoshell, and then capped with thio-terminated polyethylene glycol (SH-PEG2000). The core-shell nanostructures were characterized by different techniques like; UV-Vis/NIR scanning spectrophotometer, dynamic light scattering (DLS), transmission electron microscope (TEM). This multifunctional system achieves a variety of functions, such as radiofrequency (RF)-triggered release, chemo-hyperthermia, and NIR laser-triggered for photothermal therapy. Herein, we highlight some of the remaining major design challenges in combination with preliminary studies assessing therapeutic objectives. We demonstrate an efficient loading and delivery system to significant cell death of human cancer cells (A549) with therapeutic capabilities. Coupled with RF and NIR excitation to the doxorubicin-loaded core-shell nanostructure helped in securing targeted and controlled drug release to the cancer cells. The present core-shell multifunctional system with their multimodal imaging and therapeutic capabilities would be eminent candidates for cancer theranostics.

Keywords: cancer thernostics, multifunctional nanostructure, photothermal therapy, radiofrequency targeting

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Authors: Ewa Bednorz, Marek Polrolniczak, Bartosz Czernecki, Arkadiusz Marek Tomczyk

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This study is meant as a contribution to the research of the upwelling phenomenon, which is one of the most pronounced examples of the sea-atmosphere coupling. The aim is to confirm the atmospheric forcing of the sea waters circulation and sea surface temperature along the variously oriented Baltic Sea coasts and to find out macroscale and regional circulation patterns triggering upwelling along different sections of this relatively small and semi-closed sea basin. The mean daily sea surface temperature data from the summer seasons (June–August) of the years 1982–2017 made the basis for the detection of upwelling cases. For the atmospheric part of the analysis, monthly indices of the Northern Hemisphere macroscale circulation patterns were used. Besides, in order to identify the local direction of airflow, the daily zonal and meridional regional circulation indices were constructed and introduced to the analysis. Finally, daily regional circulation patterns over the Baltic Sea region were distinguished by applying the principal component analysis to the gridded mean daily sea level pressure data. Within the Baltic Sea, upwelling is the most frequent along the zonally oriented northern coast of the Gulf of Finland, southern coasts of Sweden, and along the middle part of the western Gulf of Bothnia coast. Among the macroscale circulation patterns, the Scandinavian type (SCAND), with a primary circulation center located over Scandinavia, has the strongest impact on the horizontal flow of surface sea waters in the Baltic Sea, which triggers upwelling. An anticyclone center over Scandinavia in the positive phase of SCAND enhances the eastern airflow, which increases upwelling frequency along southeastern Baltic coasts. It was proved in the study that the zonal circulation has a stronger impact on upwelling occurrence than the meridional one, and it could increase/decrease a chance of upwelling formation by more than 70% in some coastal sections. Positive and negative phases of six distinguished regional daily circulation patterns made 12 different synoptic situations which were analyzed in the terms of their influence on the upwelling formation. Each of them revealed some impact on the frequency of upwelling in some coastal section of the Baltic Sea; however, two kinds of synoptic situations seemed to have the strongest influence, namely, the first kind representing pressure patterns enhancing the zonal flow and the second kind representing synoptic patterns with a cyclone/anticyclone centers over southern Scandinavia. Upwelling occurrence appeared to be particularly strongly reliant on the atmospheric conditions in some specific coastal sections, namely: the Gulf of Finland, the south eastern Baltic coasts (Polish and Latvian-Lithuanian section), and the western part of the Gulf of Bothnia. Concluding, it can be stated that atmospheric conditions strongly control the occurrence of upwelling within the Baltic Sea basin. Both local and macroscale circulation patterns expressed by the location of the pressure centers influence the frequency of this phenomenon; however, the impact strength varies, depending on the coastal region. Acknowledgment: This research was funded by the National Science Centre, Poland, grant number 2016/21/B/ST10/01440.

Keywords: Baltic Sea, circulation patterns, coastal upwelling, synoptic conditions

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 361

Authors: Pavel Bulai, Taras Pitlik, Tatsiana Kulahava, Timofei Lipski

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The method of Electrocardiography (ECG) interpretation for post-exercise recovery tracking was developed. Metabolic indices (aerobic and anaerobic) were designed using ECG-derived features. This study reports the associations between aerobic and anaerobic indices and classical parameters of the person’s physiological state, including blood biochemistry, glycogen concentration and VO2max changes. During the study 9 participants, healthy, physically active medium trained men and women, which trained 2-4 times per week for at least 9 weeks, fulfilled (i) ECG monitoring using Apple Watch Series 4 (AWS4); (ii) blood biochemical analysis; (iii) maximal oxygen consumption (VO2max) test, (iv) bioimpedance analysis (BIA). ECG signals from a single-lead wrist-wearable device were processed with detection of QRS-complex. Aerobic index (AI) was derived as the normalized slope of QR segment. Anaerobic index (ANI) was derived as the normalized slope of SJ segment. Biochemical parameters, glycogen content and VO2max were evaluated eight times within 3-60 hours after training. ECGs were recorded 5 times per day, plus before and after training, cycloergometry and BIA. The negative correlation between AI and blood markers of the muscles functional status including creatine phosphokinase (r=-0.238, p < 0.008), aspartate aminotransferase (r=-0.249, p < 0.004) and uric acid (r = -0.293, p<0.004) were observed. ANI was also correlated with creatine phosphokinase (r= -0.265, p < 0.003), aspartate aminotransferase (r = -0.292, p < 0.001), lactate dehydrogenase (LDH) (r = -0.190, p < 0.050). So, when the level of muscular enzymes increases during post-exercise fatigue, AI and ANI decrease. During recovery, the level of metabolites is restored, and metabolic indices rising is registered. It can be concluded that AI and ANI adequately reflect the physiology of the muscles during recovery. One of the markers of an athlete’s physiological state is the ratio between testosterone and cortisol (TCR). TCR provides a relative indication of anabolic-catabolic balance and is considered to be more sensitive to training stress than measuring testosterone and cortisol separately. AI shows a strong negative correlation with TCR (r=-0.437, p < 0.001) and correctly represents post-exercise physiology. In order to reveal the relation between the ECG-derived metabolic indices and the state of the cardiorespiratory system, direct measurements of VO2max were carried out at various time points after training sessions. The negative correlation between AI and VO2max (r = -0.342, p < 0.001) was obtained. These data testifying VO2max rising during fatigue are controversial. However, some studies have revealed increased stroke volume after training, that agrees with findings. It is important to note that post-exercise increase in VO2max does not mean an athlete’s readiness for the next training session, because the recovery of the cardiovascular system occurs over a substantially longer period. Negative correlations registered for ANI with glycogen (r = -0.303, p < 0.001), albumin (r = -0.205, p < 0.021) and creatinine (r = -0.268, p < 0.002) reflect the dehydration status of participants after training. Correlations between designed metabolic indices and physiological parameters revealed in this study can be considered as the sufficient evidence to use these indices for assessing the state of person’s aerobic and anaerobic metabolic systems after training during fatigue, recovery and supercompensation.

Keywords: aerobic index, anaerobic index, electrocardiography, supercompensation

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Authors: Yih-Wenn Laih

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In recent times, the dependence and co-movement among international financial markets have become stronger than in the past, as evidenced by commentaries in the news media and the financial sections of newspapers. Studying the co-movement between returns in financial markets is an important issue for portfolio management and risk management. The realization of co-movement helps investors to identify the opportunities for international portfolio management in terms of asset allocation and pricing. Since the election of the new Prime Minister, Shinzo Abe, in November 2012, the yen has weakened against the US dollar from the 80 to the 120 level. The policies, known as “Abenomics,” are to encourage private investment through a more aggressive mix of monetary and fiscal policy. Given the close economic relations and competitions among Asia markets, it is interesting to discover the co-movement relations, affected by the depreciation of yen, between stock market of Japan and 5 major Asia stock markets, including China, Hong Kong, Korea, Singapore, and Taiwan. Specifically, we devote ourselves to measure the co-movement of stock markets between Japan and each one of the 5 Asia stock markets in terms of rank correlation coefficients. To compute the coefficients, return series of each stock market is first fitted by a skewed-t GARCH (generalized autoregressive conditional heteroscedasticity) model. Secondly, to measure the dependence structure between matched stock markets, we employ the symmetrized Joe-Clayton (SJC) copula to calculate the probability density function of paired skewed-t distributions. The joint probability density function is then utilized as the scoring scheme to optimize the sequence alignment by dynamic programming method. Finally, we compute the rank correlation coefficients (Kendall's  and Spearman's ) between matched stock markets based on their aligned sequences. We collect empirical data of 6 stock indexes from Taiwan Economic Journal. The data is sampled at a daily frequency covering the period from January 1, 2013 to July 31, 2015. The empirical distributions of returns indicate fatter tails than the normal distribution. Therefore, the skewed-t distribution and SJC copula are appropriate for characterizing the data. According to the computed Kendall’s τ, Korea has the strongest co-movement relation with Japan, followed by Taiwan, China, and Singapore; the weakest is Hong Kong. On the other hand, the Spearman’s ρ reveals that the strength of co-movement between markets with Japan in decreasing order are Korea, China, Taiwan, Singapore, and Hong Kong. We explore the effects of “Abenomics” on Asia stock markets by measuring the co-movement relation between Japan and five major Asia stock markets in terms of rank correlation coefficients. The matched markets are aligned by a hybrid method consisting of GARCH, copula and sequence alignment. Empirical experiments indicate that Korea has the strongest co-movement relation with Japan. The strength of China and Taiwan are better than Singapore. The Hong Kong market has the weakest co-movement relation with Japan.

Keywords: co-movement, depreciation of Yen, rank correlation, stock market

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Authors: J. Gabrielczyk, J. Kluitmann, T. Dammeyer, H. J. Jördening

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High-level expression of proteins in bacteria often causes production of insoluble protein aggregates, called inclusion bodies (IB). They contain mainly one type of protein and offer an easy and efficient way to get purified protein. On the other hand, proteins in IB are normally devoid of function and therefore need a special treatment to become active. Most refolding techniques aim at diluting the solubilizing chaotropic agents. Unfortunately, optimal refolding conditions have to be found empirically for every protein. For large-scale applications, a simple refolding process with high yields and high final enzyme concentrations is still missing. The constructed plasmid pASK-IBA63b containing the sequence of fructosyltransferase (FTF, EC 2.4.1.162) from Bacillus subtilis NCIMB 11871 was transformed into E. coli BL21 (DE3) Rosetta. The bacterium was cultivated in a fed-batch bioreactor. The produced FTF was obtained mainly as IB. For refolding experiments, five different amounts of IBs were solubilized in urea buffer with protein concentration of 0.2-8.5 g/L. Solubilizates were refolded with batch or continuous dialysis. The refolding yield was determined by measuring the protein concentration of the clear supernatant before and after the dialysis. Particle size was measured by dynamic light scattering. We tested the solubilization properties of fructosyltransferase IBs. The particle size measurements revealed that the solubilization of the aggregates is achieved at urea concentration of 5M or higher and confirmed by absorption spectroscopy. All results confirm previous investigations that refolding yields are dependent upon initial protein concentration. In batch dialysis, the yields dropped from 67% to 12% and 72% to 19% for continuous dialysis, in relation to initial concentrations from 0.2 to 8.5 g/L. Often used additives such as sucrose and glycerol had no effect on refolding yields. Buffer screening indicated a significant increase in activity but also temperature stability of FTF with citrate/phosphate buffer. By adding citrate to the dialysis buffer, we were able to increase the refolding yields to 82-47% in batch and 90-74% in the continuous process. Further experiments showed that in general, higher ionic strength of buffers had major impact on refolding yields; doubling the buffer concentration increased the yields up to threefold. Finally, we achieved corresponding high refolding yields by reducing the chamber volume by 75% and the amount of buffer needed. The refolded enzyme had an optimal activity of 12.5±0.3 x104 units/g. However, detailed experiments with native FTF revealed a reaggregation of the molecules and loss in specific activity depending on the enzyme concentration and particle size. For that reason, we actually focus on developing a process of simultaneous enzyme refolding and immobilization. The results of this study show a new approach in finding optimal refolding conditions for inclusion bodies at high concentrations. Straightforward buffer screening and increase of the ionic strength can optimize the refolding yield of the target protein by 400%. Gentle removal of chaotrope with continuous dialysis increases the yields by an additional 65%, independent of the refolding buffer applied. In general time is the crucial parameter for successful refolding of solubilized proteins.

Keywords: dialysis, inclusion body, refolding, solubilization

Procedia PDF Downloads 275