Search results for: linear vector

Authors: Amanda Gregorim Fernandes, Lorena Cardoso Cintra, Rosalia Santos Amorim Jesuino, Fabricia Paula De Faria, Marcio José Poças Fonseca

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Bioethanol is one of the most promising biofuels and able to replace fossil fuels and reduce its different environmental impacts and can be generated from various agroindustrial waste. The Brazil is in first place in bioethanol production to be the largest producer of sugarcane. The bagasse sugarcane (SCB) has lignocellulose which is composed of three major components: cellulose, hemicellulose and lignin. Cellulose is a homopolymer of glucose units connected by glycosidic linkages. Among all species of Penicillium, Penicillium echinulatum has been the focus of attention because they produce high quantities of cellulase and the mutant strain 9A02S1 produces higher enzyme levels compared to the wild. Among the cellulases, the cellobiohydrolases enzymes are the main components of the cellulolytic system of fungi, and are also responsible for most of the potential hydrolytic in enzyme cocktails for the industrial processing of plant biomass and several cellobiohydrolases Penicillium had higher specific activity against cellulose compared to CBH I from Trichoderma reesei. This fact makes it an interesting pattern for higher yields in the enzymatic hydrolysis, and also they are important enzymes in the hydrolysis of crystalline regions of cellulose. Therefore, finding new and more active enzymes become necessary. Meanwhile, β-glycosidases act on soluble substrates and are highly dependent on cellobiohydrolases and endoglucanases action to provide the substrate in the hydrolysis of the biomass, but the cellobiohydrolases and endoglucanases are highly dependent β-glucosidases to maintain efficient hydrolysis. Thus, there is a need to understand the structure-function relationships that govern the catalytic activity of cellulolytic enzymes to elucidate its mechanism of action and optimize its potential as industrial biocatalysts. To evaluate the enzyme β-glucosidase of Penicillium echinulatum (PeBGL1) the gene was synthesized from the assembly sequence from a library in induction conditions and then the PeBGL1 gene was cloned in the vector pPICZαA and transformed into P. pastoris GS115. After processing, the producers of PeBGL1 were analyzed for enzyme activity and protein profile where a band of approximately 100 kDa was viewed. It was also carried out the zymogram. In partial characterization it was determined optimum temperature of 50°C and optimum pH of 6,5. In addition, to increase the secreted recombinant PeBGL1 production by Pichia pastoris, three parameters of P. pastoris culture medium were analysed: methanol, nitrogen source concentrations and the inoculum size. A 23 factorial design was effective in achieving the optimum condition. Altogether, these results point to the potential application of this P. echinulatum β-glucosidase in hydrolysis of cellulose for the production of bioethanol.

Keywords: bioethanol, biotechnology, beta-glucosidase, penicillium echinulatum

Procedia PDF Downloads 216

Authors: Luís Marques, João Rocha, Andreia Fernandes, Maria Moura, Cláudia Caseiro, Filipa Figueiredo, João Nunes

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The implementation of circularity strategies other than recycling, such as reducing the amount of raw material, as well as reusing or sharing existing products, remains marginal. The European Commission announced that the transition towards a more circular economy could lead to the net creation of about 700,000 jobs in Europe by 2030, through additional labour demand from recycling plants, repair services and other circular activities. Efforts to create new circular business models in accordance with completely circular processes, as opposed to linear ones, have increased considerably in recent years. In order to create a societal Circular Economy transition model, it is necessary to include innovative solutions, where startups play a key role. Early-stage startups based on new business models according to circular processes often face difficulties in creating enough impact. The StartUp Zero Program designs a model and approach to increase the flow of startups in the Circular Economy field, focusing on a systemic decision analysis and multi-generational approach, considering Multi-Criteria Decision Analysis to support a decision-making tool, which is also supported by the use of a combination of an Analytical Hierarchy Process and Multi-Attribute Value Theory methods. We define principles, criteria and indicators for evaluating startup prerogatives, quantifying the evaluation process in a unique result. Additionally, this entrepreneurship program spanning 16 months involved more than 2400 young people, from ages 14 to 23, in more than 200 interaction activities.

Keywords: circular economy, entrepreneurship, startups;, multi-criteria decision analysis

Procedia PDF Downloads 63

Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modelling have constantly been a challenge through history for human being. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: auto-calibration, Gilan, large-scale water resources, simulation

Procedia PDF Downloads 307

Authors: Aemro Tazeze Terefe, Mengistu K. Aredo, Abule M. Workagegnehu, Wondimagegn M. Tesfaye

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Climate-induced shocks have been shown to reduce agricultural production and cause fluctuation in output in developing countries. When livelihoods depend on rain-fed agriculture, climate-induced shocks translate into consumption shocks. Despite the substantial improvements in household consumption, climate-induced shocks, and other factors adversely affect consumption dynamics at the household level in Ethiopia. Therefore, household consumption dynamics in the context of climate-induced shocks help to guide resilience capacity and establish appropriate interventions and programs. The research employed three-round panel data based on the Ethiopian Socioeconomic Survey with spatial rainfall data to define unique measures of rainfall variability. The linear dynamic panel model results show that the lagged value of consumption, market shocks, and rainfall variability positively affected consumption dynamics. In contrast, production shocks, temperature, and amount of rainfall had a negative relationship. Coping strategies mitigate adverse climate-induced shocks on consumption aftershocks that smooth consumption over time. Support to increase the resilience capacity of households can involve efforts to make existing livelihoods and forms of production or reductions in the vulnerability of households. Therefore, government interventions are mandatory for asset accumulation agendas that support household coping strategies and respond to shocks. In addition, the dynamic linkage between consumption and significant socioeconomic and institutional factors should be taken into account to minimize the effect of climate-induced shocks on consumption dynamics.

Keywords: climate shock, Ethiopia, fixed-effect model, food security

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Authors: Said Rashid Aal Abdulsallam

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The purpose of this paper is to measure ISO 9001:2008 effectiveness and determines its impact on the performance dimensions in terms of service quality, operational performance and customer satisfaction from the perspectives of both service providers and receivers. The paper is based on an empirical study carried out on all the ISO 9001:2008 certified departments in the Ministry of Education in the Sultanate of Oman. Data were obtained from the certified departments and their equivalent clients through two structured online questionnaires. Exploratory factor analyses are applied to extract the underlying factors of the indicators of ISO 9001 objectives and performance dimensions. Multiple linear regression analyses are also applied in order to determine the impact of ISO 9001 effectiveness on the performance dimensions of the certified departments. The study sample includes all the ISO 9001 certified departments in the Ministry of Education. The study instruments used target both the service providers as well as the service receivers with the purpose of alleviating the subjective nature of the data collected from the service providers who may be biased in favour of ISO 9001 quality management system or their performance. The findings of the study verify the effectiveness of the application of ISO 9001:2008 quality management system. Additionally, the study reveals that the ISO 9001 certified departments have achieved the ISO 9001 the standard's objectives including prevention of nonconformities, continuous improvement and customer satisfaction focus at different rates. The study also proves that there is a significant relation between the achievement of the ISO 9001 standard objectives and the operational performance of the departments. Even though the operational performance service quality of the ISO 9001 certified departments has substantially improved from the perspective of the departments, the customer satisfaction has not notably increased from the perspective of the service receivers.

Keywords: iso 9001, customer satisfaction, operational performance, public organization, quality management

Procedia PDF Downloads 372

Authors: Karina Reiter, Stefan Dullinger, Christoph Plutzar, Dietmar Moser

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Due to population growth and changing patterns of production and consumption, the demand for natural resources and, as a result, the pressure on Earth’s ecosystems are growing. Biodiversity mapping can be a useful tool for assessing species endangerment or detecting hotspots of extinction risks. This paper explores the benefits of using the change in trophic energy flows as a consequence of the human alteration of the biosphere in biodiversity mapping. To this end, multiple linear regression models were developed to explain species richness in areas where there is no human influence (i.e. wilderness) for three taxonomic groups (birds, mammals, amphibians). The models were then applied to predict (I) potential global species richness using potential natural vegetation (NPPpot) and (II) global ‘actual’ species richness after biomass appropriation using NPP remaining in ecosystems after harvest (NPPeco). By calculating the difference between predicted potential and predicted actual species numbers, maps of estimated species richness loss were generated. Results show that biomass appropriation for human use can indeed be linked to biodiversity loss. Areas for which the models predicted high species loss coincide with areas where species endangerment and extinctions are recorded to be particularly high by the International Union for Conservation of Nature and Natural Resources (IUCN). Furthermore, the analysis revealed that while the species distribution maps of the IUCN Red List of Threatened Species used for this research can determine hotspots of biodiversity loss in large parts of the world, the classification system for threatened and extinct species needs to be revised to better reflect local risks of extinction.

Keywords: biodiversity loss, biomass harvest, human appropriation of net primary production, species richness

Procedia PDF Downloads 100

Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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Authors: Tsedeke Lambore Gemecho, Ayele Taye Goshu

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The main objective of this study is to identify the determinants of the number of international migrants in a household and to compare regression models for count response. This study is done by collecting data from total of 2288 household heads of 16 randomly sampled districts in Hadiya and Kembata-Tembaro zones of Southern Ethiopia. The Poisson mixed models, as special cases of the generalized linear mixed model, is explored to determine effects of the predictors: age of household head, farm land size, and household size. Two ethnicities Hadiya and Kembata are included in the final model as dummy variables. Stepwise variable selection has indentified four predictors: age of head, farm land size, family size and dummy variable ethnic2 (0=other, 1=Kembata). These predictors are significant at 5% significance level with count response number of migrant. The Poisson mixed model consisting of the four predictors with random effects districts. Area specific random effects are significant with the variance of about 0.5105 and standard deviation of 0.7145. The results show that the number of migrant increases with heads age, family size, and farm land size. In conclusion, there is a significantly high number of international migration per household in the area. Age of household head, family size, and farm land size are determinants that increase the number of international migrant in households. Community-based intervention is needed so as to monitor and regulate the international migration for the benefits of the society.

Keywords: Poisson regression, GLM, number of migrant, Hadiya and Kembata Tembaro zones

Procedia PDF Downloads 262

Authors: Dawid Stawski, Silviya Halacheva, Dorota Zielińska

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The surface properties of many materials can be readily and predictably modified by the controlled deposition of thin layers containing appropriate functional groups and this research area is now a subject of widespread interest. The layer-by-layer (lbl) method involves depositing oppositely charged layers of polyelectrolytes onto the substrate material which are stabilized due to strong electrostatic forces between adjacent layers. This type of modification affords products that combine the properties of the original material with the superficial parameters of the new external layers. Through an appropriate selection of the deposited layers, the surface properties can be precisely controlled and readily adjusted in order to meet the requirements of the intended application. In the presented paper a variety of anionic (poly(acrylic acid)) and cationic (linear poly(ethylene imine), polymers were successfully deposited onto the polypropylene nonwoven using the lbl technique. The chemical structure of the surface before and after modification was confirmed by reflectance FTIR spectroscopy, volumetric analysis and selective dyeing tests. As a direct result of this work, new materials with greatly improved properties have been produced. For example, following a modification process significant changes in the electrostatic activity of a range of novel nanocomposite materials were observed. The deposition of polyelectrolyte nanolayers was found to strongly accelerate the loss of electrostatically generated charges and to increase considerably the thermal resistance properties of the modified fabric (the difference in T50% is over 20°C). From our results, a clear relationship between the type of polyelectrolyte layer deposited onto the flat fabric surface and the properties of the modified fabric was identified.

Keywords: layer-by-layer technique, polypropylene nonwoven, surface modification, surface properties

Procedia PDF Downloads 410

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

Procedia PDF Downloads 144

Authors: Donald Wright

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The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

Procedia PDF Downloads 113

Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

Procedia PDF Downloads 126

Authors: Jelena R. Pejović, Nina N. Serdar

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This paper presents an analysis of the “Performance-Based” seismic design method, in order to overcome the perceived disadvantages and limitations of the existing seismic design approach based on force, in engineering practice. Bearing in mind, the specificity of the earthquake as a load and the fact that the seismic resistance of the structures solely depends on its behaviour in the nonlinear field, traditional seismic design approach based on force and linear analysis is not adequate. “Performance-Based” seismic design method is based on nonlinear analysis and can be used in everyday engineering practice. This paper presents the application of this method to eight-story high reinforced concrete building with combined structural system (reinforced concrete frame structural system in one direction and reinforced concrete ductile wall system in other direction). The nonlinear time-history analysis is performed on the spatial model of the structure using program Perform 3D, where the structure is exposed to forty real earthquake records. For considered building, large number of results were obtained. It was concluded that using this method we could, with a high degree of reliability, evaluate structural behavior under earthquake. It is obtained significant differences in the response of structures to various earthquake records. Also analysis showed that frame structural system had not performed well at the effect of earthquake records on soil like sand and gravel, while a ductile wall system had a satisfactory behavior on different types of soils.

Keywords: ductile wall, frame system, nonlinear time-history analysis, performance-based methodology, RC building

Procedia PDF Downloads 344

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

Procedia PDF Downloads 95

Authors: Antonia Hoffmann, Andrea Stübner

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Resource scarcity and rising material prices are forcing companies to rethink their business models. The conventional linear system of economic growth and rising social needs further exacerbates the problem of resource scarcity. Therefore, it is necessary to separate economic growth from resource consumption. This can be achieved through the circular economy (CE), which focuses on sustainable product life cycles. However, companies face challenges in implementing CE into their businesses. Small and medium-sized enterprises are particularly affected by these problems, as they have a limited resource base. Collaboration and social interaction between different actors can help to overcome these obstacles. Based on a self-generated sample of 1,023 German small and medium-sized enterprises, we use a questionnaire to investigate the influence of social capital and its three dimensions - structural, relational, and cognitive capital - on the implementation of CE and the mediating effect of dynamic capabilities in explaining these relationships. Using regression analyses and structural equation modeling, we find that social capital is positively associated with CE implementation and dynamic capabilities partially mediate this relationship. Interestingly, our findings suggest that not all social capital dimensions are equally important for CE implementation. We theoretically and empirically explore the network forms of social capital and extend the CE literature by suggesting that dynamic capabilities help organizations leverage social capital to drive the implementation of CE practices. The findings of this study allow us to suggest several implications for managers and institutions. From a practical perspective, our study contributes to building circular production and service capabilities in small and medium-sized enterprises. Various CE activities can transform products and services to contribute to a better and more responsible world.

Keywords: circular economy, dynamic capabilities, SMEs, social capital

Procedia PDF Downloads 54

Authors: Ade Oyedijo

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This paper reports the findings of a study on the strategic and organizational antecedents and effects of two opposing pay patterns used by some manufacturing companies in Lagos Nigeria with particular reference to the behavioural correlates of the pay strategies considered. The assumed relationship between pay strategies and some organizational correlates such as business and corporate strategies and firm size was considered problematic in view of their likely implications for employee motivation and citizenship behaviour and firm performance. The survey research method was used for the study. Structured, close ended questions were used to collect primary data from the respondents. A multipart Likert scale was used to measure the pay orientations of the respondent firms and the job and organizational involvement of the respondent employees. Utilizing hierarchical linear regression method and "t-test" to analyze the data obtained from 48 manufacturing companies of various sizes and strategies, it was found that the dominant pattern of employee compensation in the sampled manufacturing companies. The study also revealed that the choice of a pay strategy was strongly influenced by organizational size as well as the type of business and corporate level strategies adopted by afirm. Firms pursuing a strategy of related and unrelated diversification are more likely to adopt the algorithmic compensation system than single product firms because of their relatively larger size and scope. However; firms that pursue a competitive advantage through a business level strategy of cost efficiency are more likely to use the experiential, variable pay strategy. The study found that an algorithmic compensation strategy is as effective as experiential compensation strategy in the promotion of organizational citizenship behaviour and motivation of employees.

Keywords: compensation, corporate strategy, business strategy, motivation, citizenship behaviour, algorithmic, experiential, organizational commitment, work environment

Procedia PDF Downloads 360

Authors: F. Longo, G. Granello, G. Tecchio, F. Da Porto

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Unreinforced masonry (URM) infill walls are widely used throughout the world, also in seismic prone regions, as partitions in reinforced concrete building frames. Even if they do not represent structural elements, they can dramatically affect both strength and stiffness of RC structures by acting as a diagonal strut, modifying shear and displacements distribution along the building height, with uncertain consequences on structural safety. In the last decades, many refined models have been developed to describe infill walls effect on frame structural behaviour, but generally restricted to in-plane actions. Only very recently some new approaches were implemented to consider in-plane/out-of-plane interaction of URM infill walls in progressive collapse simulations. In the present work, a particularly promising macro-model was adopted for the progressive collapse analysis of infilled RC frames. The model allows to consider the bi-directional interaction in terms of displacement and strength capacity for URM infills, and to remove the infill contribution when the URM wall is supposed to fail during the analysis process. The model was calibrated on experimental data regarding two different URM panels thickness, modelling with particular care the post-critic softening branch. A frame specimen set representing the most common Italian structures was built considering two main normative approaches: a traditional design philosophy, corresponding to structures erected between 50’s-80’s basically designed to support vertical loads, and a seismic design philosophy, corresponding to current criteria that take into account horizontal actions. Non-Linear Static analyses were carried out on the specimen set and some preliminary evaluations were drawn in terms of different performance exhibited by the RC frame when the contemporary effect of the out-of-plane damage is considered for the URM infill.

Keywords: infill Panels macromodels, in plane-out of plane interaction, RC frames, URM infills

Procedia PDF Downloads 492

Authors: T. P. Yu, J. J. Liu, X. L. Zhu, Y. Yin, W. Q. Wang, J. M. Ouyang, F. Q. Shao

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A strong electromagnetic field with E>1015V/m can be supplied by an intense laser such as ELI and HiPER in the near future. Exposing in such a strong laser field, laser-matter interaction enters into the near quantum electrodynamics (QED) regime and highly non-linear physics may occur during the laser-matter interaction. Recently, the multi-photon Breit-Wheeler (BW) process attracts increasing attention because it is capable to produce abundant positrons and it enhances the positron generation efficiency significantly. Here, we propose an all-optical scheme for bright gamma rays and dense positrons generation by irradiating a 1022 W/cm2 laser pulse onto an Al cone filled with near-critical-density plasmas. Two-dimensional (2D) QED particle-in-cell (PIC) simulations show that, the radiation damping force becomes large enough to compensate for the Lorentz force in the cone, causing radiation-reaction trapping of a dense electron bunch in the laser field. The trapped electrons oscillate in the laser electric field and emits high-energy gamma photons in two ways: (1) nonlinear Compton scattering due to the oscillation of electrons in the laser fields, and (2) Compton backwardscattering resulting from the bunch colliding with the reflected laser by the cone tip. The multi-photon Breit-Wheeler process is thus initiated and abundant electron-positron pairs are generated with a positron density ~1027m-3. The scheme is finally demonstrated by full 3D PIC simulations, which indicate the positron flux is up to 109. This compact gamma ray and positron source may have promising applications in future.

Keywords: BW process, electron-positron pairs, gamma rays emission, ultra-intense laser

Procedia PDF Downloads 235

Authors: Paul Narh Doku

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The relationship between parental HIV/AIDS status or death and child mental health is well known, although the role of child maltreatment as a confounder or mediator in this relationship remains uncertain. This study examined the potential path mechanism through child maltreatment mediating the link between HIV/AIDS family dysfunction trajectories and psychosocial problems. A cross-sectional survey was conducted in the Lower Manya Municipal Assembly of Ghana. A questionnaire which consisted of the Strengths and Difficulties Questionnaire (SDQ), Social and Health Assessment (SAHA), Rosenberg Self-Esteem Scale (RSES), and the Conflict Tactics Scale (CTS) was completed by 291 adolescents. Controlling for relevant sociodemographic confounders, mediation analyses using linear regression were fitted to examine whether the association between family dysfunction and psychosocial problems is mediated by child maltreatment. The results indicate that, among adolescents, child maltreatment fully mediated the association between being orphaned by AIDS and self-esteem, delinquency and risky behaviours, and peer problems. Similarly, child maltreatment fully mediated the association between living with an HIV/AIDS-infected parent and self-esteem, delinquency and risky behaviours, depression/emotional problems, and peer problems. Partial mediation was found for hyperactivity. Child maltreatment mediates the association between the family dysfunction trajectories of parental HIV/AIDS or death and psychosocial problems among adolescents. This implies that efforts to address child maltreatment among families affected by HIV/AIDS may be helpful in the prevention of psychosocial problems among these children, thus enhancing their well-being. The findings, therefore, underscore the need for comprehensive psychosocial interventions that address both the unique negative exposures of HIV/AIDS and maltreatment for children affected by HIV.

Keywords: child maltreatment, child abuse, mental health, psychosocial problems, domestic violence, HIV/AIDS, adolescents

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Authors: Yu Guan, Song Lu, Wei Yuan, Heping Zhang

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Gas fire extinguishing system is widely used due to its cleanliness and efficiency, and since its spray will be affected by many factors such as convection and obstacles in jetting region, so in order to evaluate its effectiveness, detecting concentration distribution in the jetting area is indispensable, which is commonly achieved by aspirating concentration detection technique. During the concentration measurement, the response time of detector is a very important parameter, especially for those fire-extinguishing systems with rapid gas dispersion. Long response time will not only underestimate its concentration but also prolong the change of concentration with time. Therefore it is necessary to analyze the factors influencing the response time. In the paper, an aspirating concentration detection method was introduced, which is achieved by using a small critical nozzle and a laminar flowmeter, and because of the response time is mainly related to the gas transport process from sampling site to the sensor, the effects of exhaust pipe size, gas flow rate, and gas concentration on its response time were analyzed. During the research, Bromotrifluoromethane (CBrF₃) was used. The effect of the sampling tube was investigated with different length of 1, 2, 3, 4 and 5 m (5mm in pipe diameter) and different pipe diameter of 3, 4, 5, 6 and 8 mm (3m in length). The effect of gas flow rate was analyzed by changing the throat diameter of the critical nozzle with 0.5, 0.682, 0.75, 0.8, 0.84 and 0.88 mm. The effect of gas concentration on response time was studied with the concentration range of 0-25%. The result showed that the response time increased with the increase of both the length and diameter of the sampling pipe, and the effect of length on response time was linear, but for the effect of diameter, it was exponential. It was also found that as the throat diameter of critical nozzle increased, the response time reduced a lot, in other words, gas flow rate has a great influence on response time. For the effect of gas concentration, the response time increased with the increase of the CBrF₃ concentration, and the slope of the curve was reduced.

Keywords: aspirating concentration detection, fire extinguishing, gaseous agent, response time

Procedia PDF Downloads 244

Authors: Yujiang Wu

Abstract:

As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

Procedia PDF Downloads 59

Authors: Galiya Zhanzakovna Alzhanova, Yelaman Kanatovich Aibuldinov, Zhanar Baktybaevna Iskakova, Gaziz Galymovich Abdiyussupov, Madi Toktasynuly Omirzak, Aizhan Doldashevna Gazizova

Abstract:

The sustainable use of industrial waste has recently increased due to increased environmental problems in landfills. One of the best ways to utilise waste is as a road base material. Industrial waste is a less costly and more efficient way to strengthen local soils than by introducing new additive materials. This study explored the feasibility of utilising red mud, blast furnace slag, and lime production waste to develop environmentally friendly construction materials for stabilising natural loam. Four different ratios of red mud (20, 30, and 40%), blast furnace slag (25, 30, and 35%), lime production waste (4, 6, and 8%), and varied amounts of natural loam were combined to produce nine different mixtures. The results showed that the sample with 40% red mud, 35% blast furnace slag, and 8% lime production waste had the highest strength. The sample's measured compressive strength for 90 days was 7.38 MPa, its water resistance for the same period was 7.12 MPa, and its frost resistance for the same period was 7.35 MP; low linear expansion met the requirements of the Kazakh regulations for first-class building materials. The study of mineral composition showed that there was no contamination with heavy metals or dangerous substances. Road base materials made of red mud, blast furnace slag, lime production waste, and natural loam mix can be employed because of their durability and environmental performance. The chemical and mineral composition of raw materials was determined using X-ray diffraction, X-ray fluorescence, scanning electron microscopy, energy dispersive spectroscopy, atomic absorption spectroscopy, and axial compressive strength were examined.

Keywords: blast furnace slag, lime production waste, natural loam stabilizing, red mud, road base material

Procedia PDF Downloads 65

Authors: E. Nakamachi, S. Tanaka, K. Yamamoto, Y. Morita

Abstract:

In this study, we developed a three-dimensional (3D) direct current electric field (DCEF) stimulation bio-reactor for axonal outgrowth enhancement to generate the neural network of the central nervous system (CNS). By using our newly developed 3D DCEF stimulation bio-reactor, we cultured the rat pheochromocytoma cells (PC12) and investigated the effects on the axonal extension enhancement and network generation. Firstly, we designed and fabricated a 3D bio-reactor, which can load DCEF stimulation on PC12 cells embedded in the collagen gel as extracellular environment. The connection between the electrolyte and the medium using salt bridges for DCEF stimulation was introduced to avoid the cell death by the toxicity of metal ion. The distance between the salt bridges was adopted as the design variable to optimize a structure for uniform DCEF stimulation, where the finite element (FE) analyses results were used. Uniform DCEF strength and electric flux vector direction in the PC12 cells embedded in collagen gel were examined through measurements of the fabricated 3D bio-reactor chamber. Measurement results of DCEF strength in the bio-reactor showed a good agreement with FE results. In addition, the perfusion system was attached to maintain pH 7.2 ~ 7.6 of the medium because pH change was caused by DCEF stimulation loading. Secondly, we disseminated PC12 cells in collagen gel and carried out 3D culture. Finally, we measured the morphology of PC12 cell bodies and neurites by the multiphoton excitation fluorescence microscope (MPM). The effectiveness of DCEF stimulation to enhance the axonal outgrowth and the neural network generation was investigated. We confirmed that both an increase of mean axonal length and axogenesis rate of PC12, which have been exposed 5 mV/mm for 6 hours a day for 4 days in the bioreactor. We found following conclusions in our study. 1) Design and fabrication of DCEF stimulation bio-reactor capable of 3D culture nerve cell were completed. A uniform electric field strength of average value of 17 mV/mm within the 1.2% error range was confirmed by using FE analyses, after the structure determination through the optimization process. In addition, we attached a perfusion system capable of suppressing the pH change of the culture solution due to DCEF stimulation loading. 2) Evaluation of DCEF stimulation effects on PC12 cell activity was executed. The 3D culture of PC 12 was carried out adopting the embedding culture method using collagen gel as a scaffold for four days under the condition of 5.0 mV/mm and 10mV/mm. There was a significant effect on the enhancement of axonal extension, as 11.3% increase in an average length, and the increase of axogenesis rate. On the other hand, no effects on the orientation of axon against the DCEF flux direction was observed. Further, the network generation was enhanced to connect longer distance between the target neighbor cells by DCEF stimulation.

Keywords: PC12, DCEF stimulation, 3D bio-reactor, axonal extension, neural network generation

Procedia PDF Downloads 158

Authors: S. B. Mayil Vealan, C. Sekar

Abstract:

Bisphenol A (BIS A) and 4 Nitrophenol (4N) are the most prevalent environmental endocrine-disrupting chemicals which mimic hormones and have a direct relationship to the development and growth of animal and human reproductive systems. Moreover, intensive exposure to the compound is related to prostate and breast cancer, infertility, obesity, and diabetes. Hence, accurate and reliable determination techniques are crucial for preventing human exposure to these harmful chemicals. Lanthanum Copper Oxide (La₂Cu₂O₅) nanoparticles were synthesized and investigated through various techniques such as scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy. Cyclic voltammetry and square wave voltammetry techniques are employed to evaluate the electrochemical behavior of as-synthesized samples toward the electrochemical detection of Bisphenol A and 4-Nitrophenol. Under the optimal conditions, the oxidation current increased linearly with increasing the concentration of BIS A and 4-N in the range of 0.01 to 600 μM with a detection limit of 2.44 nM and 3.8 nM. These are the lowest limits of detection and the widest linear ranges in the literature for this determination. The method was applied to the simultaneous determination of BIS A and 4-N in real samples (food packing materials and river water) with excellent recovery values ranging from 95% to 99%. Better stability, sensitivity, selectivity and reproducibility, fast response, and ease of preparation made the sensor well-suitable for the simultaneous determination of bisphenol and 4 Nitrophenol. To the best of our knowledge, this is the first report in which La₂Cu₂O₅ nano particles were used as efficient electron mediators for the fabrication of endocrine disruptor (BIS A and 4N) chemical sensors.

Keywords: endocrine disruptors, electrochemical sensor, Food contacting materials, lanthanum cuprates, nanomaterials

Procedia PDF Downloads 52

Authors: Debajyoti Bose

Abstract:

Chitosan has received much attention as a functional biopolymer for diverse applications, especially in pharmaceutics and medicine. Chitosan is a positively charged natural biodegradable and biocompatible polymer. It is a linear polysaccharide consisting of β-1,4 linked monomers of glucosamine and N-acetylglucosamine. Chitosan can be mainly obtained from fungal sources during large fermentation process. In this study,three different fungal strains Aspergillus niger NCIM 1045, Aspergillus oryzae NCIM 645 and Mucor indicus MTCC 3318 were used for the production of chitosan. The growth mediums were optimized for maximum fungal production. The produced chitosan was characterized by determining degree of deacetylation. Chitosan possesses one reactive amino at the C-2 position of the glucosamine residue, and these amines confer important functional properties to chitosan which can be exploited for biofabrication to generate various chemically modified derivatives and explore their potential for pharmaceutical field. Chitosan nanoparticles were prepared by ionic cross-linking with tripolyphosphate (TPP). The major effect on encapsulation and release of protein (e.g. enzyme diastase) in chitosan-TPP nanoparticles was investigated in order to control the loading and release efficiency. It was noted that the chitosan loading and releasing efficiency as a nanocapsule, obtained from different fungal sources was almost near to initial enzyme activity(12026 U/ml) with a negligible loss. This signify, chitosan can be used as a polymeric drug as well as active component or protein carrier material in dosage by design due to its appealing properties such as biocompatibility, biodegradability, low toxicity and relatively low production cost from abundant natural sources. Based upon these initial experiments, studies were also carried out on modification of chitosan based nanocapsules incorporated with physiologically important enzymes and nutraceuticals for target delivery.

Keywords: fungi, chitosan, enzyme, nanocapsule

Procedia PDF Downloads 462

Authors: Chin-Chia Jane

Abstract:

In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

Procedia PDF Downloads 194

Authors: Nadia El Alami El Hassani, Soukaina Motia, Benachir Bouchikhi, Nezha El Bari

Abstract:

Doxycycline (DXy) is a cycline antibiotic, most frequently prescribed to treat bacterial infections in veterinary medicine. However, its broad antimicrobial activity and low cost, lead to an intensive use, which can seriously affect human health. Therefore, its spread in the food products has to be monitored. The scope of this work was to synthetize a sensitive and very selective molecularly imprinted polymer (MIP) for DXy detection in honey samples. Firstly, the synthesis of this biosensor was performed by casting a layer of carboxylate polyvinyl chloride (PVC-COOH) on the working surface of a gold screen-printed electrode (Au-SPE) in order to bind covalently the analyte under mild conditions. Secondly, DXy as a template molecule was bounded to the activated carboxylic groups, and the formation of MIP was performed by a biocompatible polymer by the mean of polyacrylamide matrix. Then, DXy was detected by measurements of differential pulse voltammetry (DPV). A non-imprinted polymer (NIP) prepared in the same conditions and without the use of template molecule was also performed. We have noticed that the elaborated biosensor exhibits a high sensitivity and a linear behavior between the regenerated current and the logarithmic concentrations of DXy from 0.1 pg.mL⁻¹ to 1000 pg.mL⁻¹. This technic was successfully applied to determine DXy residues in honey samples with a limit of detection (LOD) of 0.1 pg.mL⁻¹ and an excellent selectivity when compared to the results of oxytetracycline (OXy) as analogous interfering compound. The proposed method is cheap, sensitive, selective, simple, and is applied successfully to detect DXy in honey with the recoveries of 87% and 95%. Considering these advantages, this system provides a further perspective for food quality control in industrial fields.

Keywords: doxycycline, electrochemical sensor, food control, gold nanoparticles, honey, molecular imprinted polymer

Procedia PDF Downloads 287

Authors: Raya Kathreen T. Fuentes, Christian Owen P. Domingo, Kaisha V. Durana, Kristine Chelsea Shynne M. Evangelista, Nicole A. Feliciano, Kathleen Patricia Q. Ferido, Christianna Joy J. Ferrer

Abstract:

Diabetes Mellitus (DM) is a global public health concern. The foot ulcer is one of the most serious and costly complications of DM. Among the components of diabetes self-management (DSM), foot self-care was found to be one of the best preventive measures for foot ulcers yet is seldom performed. Thus, the purpose of this study is to determine how adequate foot self-care practices (FSP) are among Filipino adults with DM with the following objectives: 1) determine their DSM, 2) describe their FSP, 3) determine the relationship between FSP and DSM, and 4) determine the relationship of FSP to sociodemographic characteristics, disease-related characteristics, social support, and knowledge. A descriptive correlational design was utilized. 114 respondents aged 19-65 were selected through purposive sampling from diabetes clinics. A self-administered questionnaire regarding FSP, DSM, sociodemographic and disease-related characteristics, social support, and knowledge on diabetes were used. Pearson's correlation was utilized to determine the relationship between FSP and DSM while simple linear regression was used to determine the relationship of FSP to the factors aforementioned. Results showed that majority of the respondents have desirable DSM but inadequate FSP. FSP and DSM were shown to be positively correlated but not statistically significant (p = 0.8). Disparity among the two suggests that there is less emphasis on foot self-care compared to other components of DSM. Findings further revealed that patients diagnosed with DM for < 5 years demonstrated more adequate FSP compared to patients diagnosed for > 5 years which may suggest that newly diagnosed patients are more receptive to new information about DSM. Health education on DSM should place more emphasis on FSP. Reiteration of health education and continuous motivation should be done to all DM patients, not just to newly diagnosed patients, to improve compliance to FSP and enhance patient empowerment regarding self-care.

Keywords: diabetes mellitus, diabetes self-management, foot self-care practices, foot ulcer

Procedia PDF Downloads 163

Authors: Ebrahim Ghasemi Ardi, Ai Bing Yu, Run Yu Yang

Abstract:

Current study is aimed to develop an available in-house discrete element method (DEM) code and link it with direct breakage event. So, it became possible to determine the particle breakage and then its fragments size distribution, simultaneous with DEM simulation. It directly applies the particle breakage inside the DEM computation algorithm and if any breakage happens the original particle is replaced with daughters. In this way, the calculation will be followed based on a new updated particles list which is very similar to the real grinding environment. To validate developed model, a grinding ball impacting an unconfined particle bed was simulated. Since considering an entire ball mill would be too computationally demanding, this method provided a simplified environment to test the model. Accordingly, a representative volume of the ball mill was simulated inside a box, which could emulate media (ball)–powder bed impacts in a ball mill and during particle bed impact tests. Mono, binary and ternary particle beds were simulated to determine the effects of granular composition on breakage kinetics. The results obtained from the DEM simulations showed a reduction in the specific breakage rate for coarse particles in binary mixtures. The origin of this phenomenon, commonly known as cushioning or decelerated breakage in dry milling processes, was explained by the DEM simulations. Fine particles in a particle bed increase mechanical energy loss, and reduce and distribute interparticle forces thereby inhibiting the breakage of the coarse component. On the other hand, the specific breakage rate of fine particles increased due to contacts associated with coarse particles. Such phenomenon, known as acceleration, was shown to be less significant, but should be considered in future attempts to accurately quantify non-linear breakage kinetics in the modeling of dry milling processes.

Keywords: particle bed, breakage models, breakage kinetic, discrete element method

Procedia PDF Downloads 166

Authors: Hlaing Zaw Oo, N. Kostromina, V. Osipchik, T. Kravchenko, K. Yakovleva

Abstract:

The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.

Keywords: epoxy resins, modification, vinyl-containing compounds, deformation, strength properties

Procedia PDF Downloads 83