Search results for: computational intelligence

Authors: Mehdi Behbahani, Sebastian Rible, Charles Moulinec, Yvan Fournier, Mike Nicolai, Paolo Crosetto

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Computational Fluid Dynamics blood-flow simulations are increasingly used to develop and validate blood-contacting medical devices. This study shows that numerical simulations can provide additional and accurate estimates of relevant hemodynamic indicators (e.g., recirculation zones or wall shear stresses), which may be difficult and expensive to obtain from in-vivo or in-vitro experiments. The most recent FDA (Food and Drug Administration) benchmark consisted of a simplified centrifugal blood pump model that contains fluid flow features as they are commonly found in these devices with a clear focus on highly turbulent phenomena. The FDA centrifugal blood pump study is composed of six test cases with different volumetric flow rates ranging from 2.5 to 7.0 liters per minute, pump speeds, and Reynolds numbers ranging from 210,000 to 293,000. Within the frame of this study different turbulence models were tested including RANS models, e.g. k-omega, k-epsilon and a Reynolds Stress Model (RSM) and, LES. The partitioners Hilbert, METIS, ParMETIS and SCOTCH were used to create an unstructured mesh of 76 million elements and compared in their efficiency. Computations were performed on the JUQUEEN BG/Q architecture applying the highly parallel flow solver Code SATURNE and typically using 32768 or more processors in parallel. Visualisations were performed by means of PARAVIEW. Different turbulence models including all six flow situations could be successfully analysed and validated against analytical considerations and from comparison to other data-bases. It showed that an RSM represents an appropriate choice with respect to modeling high-Reynolds number flow cases. Especially, the Rij-SSG (Speziale, Sarkar, Gatzki) variant turned out to be a good approach. Visualisation of complex flow features could be obtained and the flow situation inside the pump could be characterized.

Keywords: blood flow, centrifugal blood pump, high performance computing, scalability, turbulence

Procedia PDF Downloads 379

Authors: Selin Küçük

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Pre-industrial architecture is integration of natural and subsequent properties by intelligence and experience. Since various settlements relatively industrialized or non-industrialized at any time, ‘pre-industrial’ term does not refer to a definite time. Natural properties, which are existent conditions and materials in natural local environment, are climate, geomorphology and local materials. Subsequent properties, which are all anthropological comparatives, are culture of societies, requirements of people and construction techniques that people use. Yet, after industrialization, technology took technique’s place, cultural effects are manipulated, requirements are changed and local/natural properties are almost disappeared in architecture. Technology is universal, global and expands simply; conversely technique is time and experience dependent and should has a considerable cultural background. This research is about construction techniques according to natural properties of a region and classification of these techniques. Understanding local architecture is only possible by searching its background which is hard to reach. There are always changes in positive and negative in architectural techniques through the time. Archaeological layers of a region sometimes give more accurate information about transformation of architecture. However, natural properties of any region are the most helpful elements to perceive construction techniques. Many international sources from different cultures are interested in local architecture by mentioning natural properties separately. Unfortunately, there is no literature deals with this subject as far as systematically in the correct way. This research aims to improve a clear perspective of local architecture existence by categorizing archetypes according to natural properties. The ultimate goal of this research is generating a clear classification of local architecture independent from subsequent (anthropological) properties over the world such like a handbook. Since local architecture is the most sustainable architecture with refer to its economic, ecologic and sociological properties, there should be an excessive information about construction techniques to be learned from. Constructing the same buildings in all over the world is one of the main criticism of modern architectural system. While this critics going on, the same buildings without identity increase incrementally. In post-industrial term, technology widely took technique’s place, yet cultural effects are manipulated, requirements are changed and natural local properties are almost disappeared in architecture. These study does not offer architects to use local techniques, but it indicates the progress of pre-industrial architectural evolution which is healthier, cheaper and natural. Immigration from rural areas to developing/developed cities should be prohibited, thus culture and construction techniques can be preserved. Since big cities have psychological, sensational and sociological impact on people, rural settlers can be convinced to not to immigrate by providing new buildings designed according to natural properties and maintaining their settlements. Improving rural conditions would remove the economical and sociological gulf between cities and rural. What result desired to arrived in, is if there is no deformation (adaptation process of another traditional buildings because of immigration) or assimilation in a climatic region, there should be very similar solutions in the same climatic regions of the world even if there is no relationship (trade, communication etc.) among them.

Keywords: climate zones, geomorphology, local architecture, local materials

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Authors: Mahtab Makaremi Masouleh, Günter Wozniak

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This work is part of a major research project concerning the design of a light temporary installable textile flood control structure. The motivation for this work is the great need of applying light structures for the protection of coastal areas from detrimental effects of rapid water runoff. The prime objective of the study is the numerical analysis of the interaction among free surface water flow and slender shaped pliable structures, playing a key role in safety performance of the intended system. First, the behavior of down scale membrane is examined under hydrostatic pressure by the Abaqus explicit solver, which is part of the finite element based commercially available SIMULIA software. Then the procedure to achieve a stable and convergent solution for strongly coupled media including fluids and structures is explained. A partitioned strategy is imposed to make both structures and fluids be discretized and solved with appropriate formulations and solvers. In this regard, finite element method is again selected to analyze the structural domain. Moreover, computational fluid dynamics algorithms are introduced for solutions in flow domains by means of a commercial package of Star CCM+. Likewise, SIMULIA co-simulation engine and an implicit coupling algorithm, which are available communication tools in commercial package of the Star CCM+, enable powerful transmission of data between two applied codes. This approach is discussed for two different cases and compared with available experimental records. In one case, the down scale membrane interacts with open channel flow, where the flow velocity increases with time. The second case illustrates, how the full scale flexible flood barrier behaves when a massive flotsam is accelerated towards it.

Keywords: finite element formulation, finite volume algorithm, fluid-structure interaction, light pliable structure, VOF multiphase model

Procedia PDF Downloads 180

Authors: Thanh N. Do

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This paper addresses the modeling of two critical behaviors of concrete material in reinforced concrete components: (1) the increase in strength and ductility due to confining stresses from surrounding transverse steel reinforcements, and (2) the progressive deterioration in strength and stiffness due to high strain and/or cyclic loading. To improve the state-of-the-art, the author presents a new 3D constitutive model of concrete material based on plasticity and continuum damage mechanics theory to simulate both the confinement effect and the strength deterioration in reinforced concrete components. The model defines a yield function of the stress invariants and a compressive damage threshold based on the level of confining stresses to automatically capture the increase in strength and ductility when subjected to high compressive stresses. The model introduces two damage variables to describe the strength and stiffness deterioration under tensile and compressive stress states. The damage formulation characterizes well the degrading behavior of concrete material, including the nonsymmetric strength softening in tension and compression, as well as the progressive strength and stiffness degradation under primary and follower load cycles. The proposed damage model is implemented in a general purpose finite element analysis program allowing an extensive set of numerical simulations to assess its ability to capture the confinement effect and the degradation of the load-carrying capacity and stiffness of structural elements. It is validated against a collection of experimental data of the hysteretic behavior of reinforced concrete columns and shear walls under different load histories. These correlation studies demonstrate the ability of the model to describe vastly different hysteretic behaviors with a relatively consistent set of parameters. The model shows excellent consistency in response determination with very good accuracy. Its numerical robustness and computational efficiency are also very good and will be further assessed with large-scale simulations of structural systems.

Keywords: concrete, damage-plasticity, shear wall, confinement

Procedia PDF Downloads 166

Authors: Mballa Abanda Serge, Henda Gnakate Biba, Romaric Guemno Kuate, Akono Rufine Nicole, Petfiang Sidonie, Bella Sidonie

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The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization, It designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and world music or variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, entanglement, langauge, science

Procedia PDF Downloads 74

Authors: Victor Alves Barros Galvão, Israel Da Silveira Rego, Antonio Carlos Oliveira, Paulo Gilberto De Paula Toro

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The Brazilian hypersonic aerospace vehicle 14-X B, VHA 14-X B, is a vehicle integrated with the hypersonic airbreathing propulsion system based on supersonic combustion (scramjet), developing in Aerothermodynamics and hypersonic Prof. Henry T. Nagamatsu Laboratory, to conduct demonstration in atmospheric flight at the speed corresponding to Mach number 7 at an altitude of 30km. In the experimental procedure the hypersonic shock tunnel T3 was used, installed in that laboratory. This device simulates the flow over a model is fixed in the test section and can also simulate different atmospheric conditions. The scramjet technology offers substantial advantages to improve aerospace vehicle performance which flies at a hypersonic speed through the Earth's atmosphere by reducing fuel consumption on board. Basically, the scramjet is an aspirated aircraft engine fully integrated that uses oblique/conic shock waves generated during hypersonic flight, to promote the deceleration and compression of atmospheric air in scramjet inlet. During the hypersonic flight, the vehicle VHA 14-X will suffer atmospheric influences, promoting changes in the vehicle's angles of attack (angle that the mean line of vehicle makes with respect to the direction of the flow). Based on this information, a study is conducted to analyze the influences of changes in the vehicle's angle of attack during the atmospheric flight. Analytical theoretical analysis, simulation computational fluid dynamics and experimental investigation are the methodologies used to design a technological demonstrator prior to the flight in the atmosphere. This paper considers analysis of the thermodynamic properties (pressure, temperature, density, sound velocity) in lower surface of the VHA 14-X B. Also, it considers air as an ideal gas and chemical equilibrium, with and without boundary layer, considering changes in the vehicle's angle of attack (positive and negative in relation to the flow) and bi-dimensional expansion wave theory at the expansion section (Theory of Prandtl-Meyer).

Keywords: angle of attack, experimental hypersonic, hypersonic airbreathing propulsion, Scramjet

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Authors: Nasser Salah Eldin Mohammed Salih Shebka

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Current problematic issues in AI fields are mainly due to those of knowledge representation conceptual theories, which in turn reflected on the entire scope of cognitive sciences. Knowledge representation methods and tools are driven from theoretical concepts regarding human scientific perception of the conception, nature, and process of knowledge acquisition, knowledge engineering and knowledge generation. And although, these theoretical conceptions were themselves driven from the study of the human knowledge representation process and related theories; some essential factors were overlooked or underestimated, thus causing critical methodological deficiencies in the conceptual theories of human knowledge and knowledge representation conceptions. The evaluation criteria of human cumulative knowledge from the perspectives of nature and theoretical aspects of knowledge representation conceptions are affected greatly by the very materialistic nature of cognitive sciences. This nature caused what we define as methodological deficiencies in the nature of theoretical aspects of knowledge representation concepts in AI. These methodological deficiencies are not confined to applications of knowledge representation theories throughout AI fields, but also exceeds to cover the scientific nature of cognitive sciences. The methodological deficiencies we investigated in our work are: - The Segregation between cognitive abilities in knowledge driven models.- Insufficiency of the two-value logic used to represent knowledge particularly on machine language level in relation to the problematic issues of semantics and meaning theories. - Deficient consideration of the parameters of (existence) and (time) in the structure of knowledge. The latter requires that we present a more detailed introduction of the manner in which the meanings of Existence and Time are to be considered in the structure of knowledge. This doesn’t imply that it’s easy to apply in structures of knowledge representation systems, but outlining a deficiency caused by the absence of such essential parameters, can be considered as an attempt to redefine knowledge representation conceptual approaches, or if proven impossible; constructs a perspective on the possibility of simulating human cognition on machines. Furthermore, a redirection of the aforementioned expressions is required in order to formulate the exact meaning under discussion. This redirection of meaning alters the role of Existence and time factors to the Frame Work Environment of knowledge structure; and therefore; knowledge representation conceptual theories. Findings of our work indicate the necessity to differentiate between two comparative concepts when addressing the relation between existence and time parameters, and between that of the structure of human knowledge. The topics presented throughout the paper can also be viewed as an evaluation criterion to determine AI’s capability to achieve its ultimate objectives. Ultimately, we argue some of the implications of our findings that suggests that; although scientific progress may have not reached its peak, or that human scientific evolution has reached a point where it’s not possible to discover evolutionary facts about the human Brain and detailed descriptions of how it represents knowledge, but it simply implies that; unless these methodological deficiencies are properly addressed; the future of AI’s qualitative progress remains questionable.

Keywords: cognitive sciences, knowledge representation, ontological reasoning, temporal logic

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Authors: Michal Bialy, Marcin Szlachetka, Mateusz Paszko

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This paper discusses the CFD results of heat transfer in water channels in the engine body. The research engine was a newly designed Diesel combustion engine. The engine has three cylinders with three pairs of opposed pistons inside. The engine will be able to generate 100 kW mechanical power at a crankshaft speed of 3,800-4,000 rpm. The water channels are in the engine body along the axis of the three cylinders. These channels are around the three combustion chambers. The water channels transfer combustion heat that occurs the cylinders to the external radiator. This CFD research was based on the ANSYS Fluent software and aimed to optimize the geometry of the water channels. These channels should have a maximum flow of heat from the combustion chamber or the external radiator. Based on the parallel simulation research, the boundary and initial conditions enabled us to specify average values of key parameters for our numerical analysis. Our simulation used the average momentum equations and turbulence model k-epsilon double equation. There was also used a real k-epsilon model with a function of a standard wall. The turbulence intensity factor was 10%. The working fluid mass flow rate was calculated for a single typical value, specified in line with the research into the flow rate of automotive engine cooling pumps used in engines of similar power. The research uses a series of geometric models which differ, for instance, in the shape of the cross-section of the channel along the axis of the cylinder. The results are presented as colourful distribution maps of temperature, speed fields and heat flow through the cylinder walls. Due to limitations of space, our paper presents the results on the most representative geometric model only. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A. and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: Ansys fluent, combustion engine, computational fluid dynamics CFD, cooling system

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Yasemin Akar, Jan G. Wissink, Herlina Herlina

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The effect of various levels of contamination on the interfacial air–water gas transfer velocity is studied by Direct Numerical Simulation (DNS). The interfacial gas transfer is driven by isotropic turbulence, introduced at the bottom of the computational domain, diffusing upwards. The isotropic turbulence is generated in a separate, concurrently running the large-eddy simulation (LES). The flow fields in the main DNS and the LES are solved using fourth-order discretisations of convection and diffusion. To solve the transport of dissolved gases in water, a fifth-order-accurate WENO scheme is used for scalar convection combined with a fourth-order central discretisation for scalar diffusion. The damping effect of the surfactant contamination on the near surface (horizontal) velocities in the DNS is modelled using horizontal gradients of the surfactant concentration. An important parameter in this model, which corresponds to the level of contamination, is ReMa⁄We, where Re is the Reynolds number, Ma is the Marangoni number, and We is the Weber number. It was previously found that even small levels of contamination (ReMa⁄We small) lead to a significant drop in the interfacial gas transfer velocity KL. It is known that KL depends on both the Schmidt number Sc (ratio of the kinematic viscosity and the gas diffusivity in water) and the surface divergence β, i.e. K_L∝√(β⁄Sc). Previously it has been shown that this relation works well for surfaces with low to moderate contamination. However, it will break down for β close to zero. To study the validity of this dependence in the presence of surface contamination, simulations were carried out for ReMa⁄We=0,0.12,0.6,1.2,6,30 and Sc = 2, 4, 8, 16, 32. First, it will be shown that the scaling of KL with Sc remains valid also for larger ReMa⁄We. This is an important result that indicates that - for various levels of contamination - the numerical results obtained at low Schmidt numbers are also valid for significantly higher and more realistic Sc. Subsequently, it will be shown that - with increasing levels of ReMa⁄We - the dependency of KL on β begins to break down as the increased damping of near surface fluctuations results in an increased damping of β. Especially for large levels of contamination, this damping is so severe that KL is found to be underestimated significantly.

Keywords: contamination, gas transfer, surfactants, turbulence

Procedia PDF Downloads 294

Authors: Alua Masalimova, Dameli Sulubecova, Talgat Isaev, Raushan Magzumova

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The usual relation to nurses of heads of medical organizations in Kazakhstan is to use them only for per performing medical manipulations, but new economic conditions require the introduction of nursing innovations. There is an increasing need for managers of hospital departments and regions of ambulatory clinics to ensure comfortable conditions for doctors, nurses, aides, as well as monitoring marketing technology (the needs and satisfaction of staff work, the patient satisfaction of the department). It is going to the past the nursing activities as physician assistant performing his prescriptions passively. We are suggesting a model for the developing the head nurse as the manager on the example of Blood Service. We have studied in the scientific-production center of blood transfusion head nurses by the standard method of interviewing for involvement in coordinating the flow of information, promoting the competitiveness of the department. Results: the average age of the respondents 43,1 ± 9,8, female - 100%; manager in the Organization – 9,3 ± 10,3 years. Received positive responses to the knowledge of the nearest offices in providing similar medical service - 14,2%. The cost of similar medical services in other competitive organizations did not know 100%, did a study of employee satisfaction Division labour-85,7% answered negatively, the satisfaction donors work staff studied in 50.0% of cases involved in attracting paid Services Division showed a 28.5% of the respondent. Participation in management decisions medical organization: strategic planning - 14,2%, forming analysis report for the year – 14,2%, recruitment-30.0%, equipment-14.2%. Participation in the social and technical designing workplaces Division staff showed 85,0% of senior nurses. Participate in the cohesion of the staff of the Division method of the team used the 10.0% of respondents. Further, we have studied the behavioral competencies for senior sisters: customer focus – 20,0% of respondents have attended, the ability to work in a team – 40,0%. Personal qualities senior nurses were apparent: sociability – 80,0%, the ability to manage information – 40,0%, to make their own decisions - 14,2%, 28,5% creativity, the desire to improve their professionalism – 50,0%. Thus, the modern market conditions dictate this organization, which works for the rights of economic management; include the competence of the post of the senior nurse knowledge and skills of Marketing Management Department. Skills to analyses the information collected and use of management offers superior medical leadership organization. The medical organization in the recruitment of the senior nurse offices take into account personal qualities: flexibility, fluency of thinking, communication skills and ability to work in a team. As well as leadership qualities, ambition, high emotional and social intelligence, that will bring out the medical unit on competitiveness within the country and abroad.

Keywords: blood service, head nurse, manager, skills

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Authors: Helnaz Soltani, J. N. Reddy

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Presence of fluid medium interacting with a structure can lead to failure of the structure. Since developing efficient computational model for fluid-structure interaction (FSI) problems has broader impact to realistic problems encountered in aerospace industry, ship industry, oil and gas industry, and so on, one can find an increasing need to find a method in order to investigate the effect of fluid domain on structural response. A coupled finite element formulation of problems involving FSI issue is an accurate method to predict the response of structures in contact with a fluid medium. This study proposes a finite element approach in order to study the transient response of the structures interacting with a fluid medium. Since beam and plate are considered to be the fundamental elements of almost any structure, the developed method is applied to beams and plates benchmark problems in order to demonstrate its efficiency. The formulation is a combination of the various structure theories and the solid-fluid interface boundary condition, which is used to represent the interaction between the solid and fluid regimes. Here, three different beam theories as well as three different plate theories are considered to model the solid medium, and the Navier-Stokes equation is used as the theoretical equation governed the fluid domain. For each theory, a coupled set of equations is derived where the element matrices of both regimes are calculated by Gaussian quadrature integration. The main feature of the proposed methodology is to model the fluid domain as an added mass; the external distributed force due to the presence of the fluid. We validate the accuracy of such formulation by means of some numerical examples. Since the formulation presented in this study covers several theories in literature, the applicability of our proposed approach is independent of any structure geometry. The effect of varying parameters such as structure thickness ratio, fluid density and immersion depth, are studied using numerical simulations. The results indicate that maximum vertical deflection of the structure is affected considerably in the presence of a fluid medium.

Keywords: beam and plate, finite element analysis, fluid-structure interaction, transient response

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Authors: Heikki Ruohomaa, Vesa Salminen

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Regions are facing huge competition to attract companies, businesses, inhabitants, students, etc. This way to improve living and business environment, which is rapidly changing due to digitalization. On the other hand, from the industry's point of view, the availability of a skilled labor force and an innovative environment are crucial factors. In this context, qualified staff has been seen to utilize the opportunities of digitalization and respond to the needs of future skills. World Manufacturing Forum has stated in the year 2019- report that in next five years, 40% of workers have to change their core competencies. Through digital transformation, new technologies like cloud, mobile, big data, 5G- infrastructure, platform- technology, data- analysis, and social networks with increasing intelligence and automation, enterprises can capitalize on new opportunities and optimize existing operations to achieve significant business improvement. Digitalization will be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, the education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The Fourth Industrial Revolution will bring unprecedented change to societies, education organizations and business environments. This article aims to identify how education, education content, the way education has proceeded, and overall whole the education business is changing. Most important is how we should respond to this inevitable co- evolution. Methodology: The study aims to verify how the learning process is boosted by new digital content, new learning software and tools, and customer-oriented learning environments. The change of education programs and individual education modules can be supported by applied research projects. You can use them in making proof- of- the concept of new technology, new ways to teach and train, and through the experiences gathered change education content, way to educate and finally education business as a whole. Major findings: Applied research projects can prove the concept- phases on real environment field labs to test technology opportunities and new tools for training purposes. Customer-oriented applied research projects are also excellent for students to make assignments and use new knowledge and content and teachers to test new tools and create new ways to educate. New content and problem-based learning are used in future education modules. This article introduces some case study experiences on customer-oriented digital transformation projects and how gathered knowledge on new digital content and a new way to educate has influenced education. The case study is related to experiences of research projects, customer-oriented field labs/learning environments and education programs of Häme University of Applied Sciences.

Keywords: education process, digitalization content, digital tools for education, learning environments, transdisciplinary co-operation

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Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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Authors: Gaurav Prabhudesai, Gaetan Brill

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The sun's energy source comes from a hydrogen-to-helium thermonuclear reaction, generating a temperature of about 5760 K on its outer layer. On account of this high temperature, energy is radiated by the sun, a part of which reaches the earth. This sunlight, even after losing part of its energy en-route to scattering and absorption, provides a time and space averaged solar flux of 174.7 W/m^2 striking the earth’s surface. According to one study, the solar energy striking earth’s surface in one and a half hour is more than the energy consumption that was recorded in the year 2001 from all sources combined. Thus, technology for extraction of solar energy holds much promise for solving energy crisis. Of the many technologies developed in this regard, Concentrating Solar Power (CSP) plants with central solar tower and receiver system are very impressive because of their capability to provide a renewable energy that can be stored in the form of heat. One design of central receiver towers is an open cavity where sunlight is concentrated into by using mirrors (also called heliostats). This concentrated solar flux produces high temperature inside the cavity which can be utilized in an energy conversion process. The amount of energy captured is reduced by losses occurring at the cavity through all three modes viz., radiation to the atmosphere, conduction to the adjoining structure and convection. This study investigates the natural convection losses to the environment from the receiver. Computational fluid dynamics were used to simulate the fluid flow and heat transfer of the receiver; since no analytical solution can be obtained and no empirical correlations exist for the given geometry. The results provide guide lines for predicting natural convection losses for hexagonal and circular shaped open cavities. Additionally, correlations are given for various inclination angles and aspect ratios. These results provide methods to minimize natural convection through careful design of receiver geometry and modification of the inclination angle, and aspect ratio of the cavity.

Keywords: concentrated solar power (CSP), central receivers, natural convection, CFD, open cavities

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Authors: Christina Hagen, Pragathi Kamale Gurmurthy, Thorsten M. Buzug

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CFD simulations are performed in the upper airway of a patient suffering from obstructive sleep apnea (OSA) that is a sleep related breathing disorder characterized by repetitive partial or complete closures of the upper airways. The simulations are aimed at getting a better understanding of the pathophysiological flow patterns in an OSA patient. The simulation is compared to medical data of a sleep endoscopic examination under sedation. A digital model consisting of surface triangles of the upper airway is extracted from the MR images by a region growing segmentation process and is followed by a careful manual refinement. The computational domain includes the nasal cavity with the nostrils as the inlet areas and the pharyngeal volume with an outlet underneath the larynx. At the nostrils a flat inflow velocity profile is prescribed by choosing the velocity such that a volume flow rate of 150 ml/s is reached. Behind the larynx at the outlet a pressure of -10 Pa is prescribed. The stationary incompressible Navier-Stokes equations are numerically solved using finite elements. A grid convergence study has been performed. The results show an amplification of the maximal velocity of about 2.5 times the inlet velocity at a constriction of the pharyngeal volume in the area of the tongue. It is the same region that also shows the highest pressure drop from about 5 Pa. This is in agreement with the sleep endoscopic examinations of the same patient under sedation showing complete contractions in the area of the tongue. CFD simulations can become a useful tool in the diagnosis and therapy of obstructive sleep apnea by giving insight into the patient’s individual fluid dynamical situation in the upper airways giving a better understanding of the disease where experimental measurements are not feasible. Within this study, it could been shown on one hand that constriction areas within the upper airway lead to a significant pressure drop and on the other hand a good agreement of the area of pressure drop and the area of contraction could be shown.

Keywords: biomedical engineering, obstructive sleep apnea, pharynx, upper airways

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Authors: Kausar Harun, Ahmad Azmin Mohamad

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Zinc oxide (ZnO) has been extensively used in optoelectronic devices, with recent interest as photoanode material in dye-sensitize solar cell. Numerous methods employed to experimentally synthesized ZnO, while some are theoretically-modeled. Both approaches provide information on ZnO properties, but theoretical calculation proved to be more accurate and timely effective. Thus, integration between these two methods is essential to intimately resemble the properties of synthesized ZnO. In this study, experimentally-grown ZnO nanoparticles were prepared by sol-gel storage method with zinc acetate dihydrate and methanol as precursor and solvent. A 1 M sodium hydroxide (NaOH) solution was used as stabilizer. The optimum time to produce ZnO nanoparticles were recorded as 12 hours. Phase and structural analysis showed that single phase ZnO produced with wurtzite hexagonal structure. Further work on quantitative analysis was done via Rietveld-refinement method to obtain structural and crystallite parameter such as lattice dimensions, space group, and atomic coordination. The lattice dimensions were a=b=3.2498Å and c=5.2068Å which were later used as main input in first-principles calculations. By applying density-functional theory (DFT) embedded in CASTEP computer code, the structure of synthesized ZnO was built and optimized using several exchange-correlation functionals. The generalized-gradient approximation functional with Perdew-Burke-Ernzerhof and Hubbard U corrections (GGA-PBE+U) showed the structure with lowest energy and lattice deviations. In this study, emphasize also given to the modification of valence electron energy level to overcome the underestimation in DFT calculation. Both Zn and O valance energy were fixed at Ud=8.3 eV and Up=7.3 eV, respectively. Hence, the following electronic and optical properties of synthesized ZnO were calculated based on GGA-PBE+U functional within ultrasoft-pseudopotential method. In conclusion, the incorporation of Rietveld analysis into first-principles calculation was valid as the resulting properties were comparable with those reported in literature. The time taken to evaluate certain properties via physical testing was then eliminated as the simulation could be done through computational method.

Keywords: density functional theory, first-principles, Rietveld-refinement, ZnO nanoparticles

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Authors: Shahin A. Abdel-Naby, James P. Colgan, Michael S. Pindzola

Abstract:

A time-dependent close-coupling method is developed to calculate a total, double and triple autoionization rates for hollow atomic ions of four-electron systems. This work was motivated by recent observations of the four-electron Auger process in near K-edge photoionization of C+ ions. The time-dependent close-coupled equations are solved using lattice techniques to obtain a discrete representation of radial wave functions and all operators on a four-dimensional grid with uniform spacing. Initial excited states are obtained by relaxation of the Schrodinger equation in imaginary time using a Schmidt orthogonalization method involving interior subshells. The radial wave function grids are partitioned over the cores on a massively parallel computer, which is essential due to the large memory requirements needed to store the coupled-wave functions and the long run times needed to reach the convergence of the ionization process. Total, double, and triple autoionization rates are obtained by the propagation of the time-dependent close-coupled equations in real-time using integration over bound and continuum single-particle states. These states are generated by matrix diagonalization of one-electron Hamiltonians. The total autoionization rates for each L excited state is found to be slightly above the single autoionization rate for the excited configuration using configuration-average distorted-wave theory. As expected, we find the double and triple autoionization rates to be much smaller than the total autoionization rates. Future work can be extended to study electron-impact triple ionization of atoms or ions. The work was supported in part by grants from the American University of Sharjah and the US Department of Energy. Computational work was carried out at the National Energy Research Scientific Computing Center (NERSC) in Berkeley, California, USA.

Keywords: hollow atoms, autoionization, auger rates, time-dependent close-coupling method

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Authors: Ali Raza, Rizwan Latif, Syed Adnan Qasim, Imran Shafi

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Diesel engines are most efficient and reliable in terms of efficiency, reliability, and adaptability. Most of the research and development up till now have been directed towards High Speed Diesel Engine, for Commercial use. In these engines, objective is to optimize maximum acceleration by reducing exhaust emission to meet international standards. In high torque low speed engines, the requirement is altogether different. These types of engines are mostly used in Maritime Industry, Agriculture Industry, Static Engines Compressors Engines, etc. On the contrary, high torque low speed engines are neglected quite often and are eminent for low efficiency and high soot emissions. One of the most effective ways to overcome these issues is by efficient combustion in an engine cylinder. Fuel spray dynamics play a vital role in defining mixture formation, fuel consumption, combustion efficiency and soot emissions. Therefore, a comprehensive understanding of the fuel spray characteristics and atomization process in high torque low speed diesel engine is of great importance. Evaporation in the combustion chamber has a rigorous effect on the efficiency of the engine. In this paper, multiphase evaporation of fuel is modeled for high torque low speed engine using the CFD (computational fluid dynamics) codes. Two distinct phases of evaporation are modeled using modeling soft wares. The basic model equations are derived from the energy conservation equation and Naiver-Stokes equation. O’Rourke model is used to model the evaporation phases. The results obtained showed a generous effect on the efficiency of the engine. Evaporation rate of fuel droplet is increased with the increase in vapor pressure. An appreciable reduction in size of droplet is achieved by adding the convective heat effects in the combustion chamber. By and large, an overall increase in efficiency is observed by modeling distinct evaporation phases. This increase in efficiency is due to the fact that droplet size is reduced and vapor pressure is increased in the engine cylinder.

Keywords: diesel fuel, CFD, evaporation, multiphase

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Authors: Giulia Magi Meconi, Nicholas Ballard, José M. Asua, Ronen Zangi

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Experimental and computational studies are combined to elucidate the adsorption proprieties of ionic and nonionic surfactants on hydrophobic polymer surface such us poly(styrene). To present these two types of surfactants, sodium dodecyl sulfate and poly(ethylene glycol)-block-poly(ethylene), commonly utilized in emulsion polymerization, are chosen. By applying quartz crystal microbalance with dissipation monitoring it is found that, at low surfactant concentrations, it is easier to desorb (as measured by rate) ionic surfactants than nonionic surfactants. From molecular dynamics simulations, the effective, attractive force of these nonionic surfactants to the surface increases with the decrease of their concentration, whereas, the ionic surfactant exhibits mildly the opposite trend. The contrasting behavior of ionic and nonionic surfactants critically relies on two observations obtained from the simulations. The first is that there is a large degree of interweavement between head and tails groups in the adsorbed layer formed by the nonionic surfactant (PEO/PE systems). The second is that water molecules penetrate this layer. In the disordered layer, these nonionic surfactants generate at the surface, only oxygens of the head groups present at the interface with the water phase or oxygens next to the penetrating waters can form hydrogen bonds. Oxygens inside this layer lose this favorable energy, with a magnitude that increases with the surfactants density at the interface. This reduced stability of the surfactants diminishes their driving force for adsorption. All that is shown to be in accordance with experimental results on the dynamics of surfactants desorption. Ionic surfactants assemble into an ordered structure and the attraction to the surface was even slightly augmented at higher surfactant concentration, in agreement with the experimentally determined adsorption isotherm. The reason these two types of surfactants behave differently is because the ionic surfactant has a small head group that is strongly hydrophilic, whereas the head groups of the nonionic surfactants are large and only weakly attracted to water.

Keywords: emulsion polymerization process, molecular dynamics simulations, polymer surface, surfactants adsorption

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: B. Donkova, M. Nedyalkova, D. Mehandjiev

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Sparingly soluble manganese oxalate is an appropriate precursor for the preparation of nanosized manganese oxides, which have a wide range of technological application. During the precipitation of manganese oxalate, three crystal forms could be obtained – α-MnC₂O₄.2H₂O (SG C2/c), γ-MnC₂O₄.2H₂O (SG P212121) and orthorhombic MnC₂O₄.3H₂O (SG Pcca). The thermolysis of α-MnC₂O₄.2H₂O has been extensively studied during the years, while the literature data for the other two forms has been quite scarce. The aim of the present communication is to highlight the influence of the initial crystal structure on the decomposition mechanism of these three forms, their magnetic properties, the structure of the anhydrous oxalates, as well as the nature of the obtained oxides. For the characterization of the samples XRD, SEM, DTA, TG, DSC, nitrogen adsorption, and in situ magnetic measurements were used. The dehydration proceeds in one step with α-MnC₂O₄.2H2O and γ-MnC₂O₄.2H₂O, and in three steps with MnC₂O₄.3H2O. The values of dehydration enthalpy are 97, 149 and 132 kJ/mol, respectively, and the last two were reported for the first time, best to our knowledge. The magnetic measurements show that at room temperature all samples are antiferomagnetic, however during the dehydration of α-MnC₂O₄.2H₂O the exchange interaction is preserved, for MnC₂O₄.3H₂O it changes to ferromagnetic above 35°C, and for γ-MnC₂O₄.2H₂O it changes twice from antiferomagnetic to ferromagnetic above 70°C. The experimental results for magnetic properties are in accordance with the computational results obtained with Wien2k code. The difference in the initial crystal structure of the forms used determines different changes in the specific surface area during dehydration and different extent of Mn(II) oxidation during decomposition in the air; both being highest at α-MnC₂O₄.2H₂O. The isothermal decomposition of the different oxalate forms shows that the type and physicochemical properties of the oxides, obtained at the same annealing temperature depend on the precursor used. Based on the results from the non-isothermal and isothermal experiments, and from different methods used for characterization of the sample, a comparison of the nature, mechanism and peculiarities of the thermolysis of the different crystal forms of manganese oxalate was made, which clearly reveals the influence of the initial crystal structure. Acknowledgment: 'Science and Education for Smart Growth', project BG05M2OP001-2.009-0028, COST Action MP1306 'Modern Tools for Spectroscopy on Advanced Materials', and project DCOST-01/18 (Bulgarian Science Fund).

Keywords: crystal structure, magnetic properties, manganese oxalate, thermal behavior

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Authors: Mamunur Rashid, Jialin Yan

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The current years have witnessed a rapid evolution and integration of artificial intelligence (AI) in various fields, prominently influencing the education industry. Acknowledging this transformative wave, AI tools like ChatGPT and Grammarly have undeniably introduced perspectives and skills, enriching the educational experiences of higher education students. The prevalence of AI utilization in higher education also drives an increasing number of researchers' attention in various dimensions. Departments, offices, and professors in universities also designed and released a set of policies and guidelines on using AI effectively. In regard to this, the study targets exploring and analyzing graduate students' perspectives regarding AI guidelines set by teachers. A mixed-methods study will be mainly conducted in this study, employing in-depth interviews and focus groups to investigate and collect students' perspectives. Relevant materials, such as syllabi and course instructions, will also be analyzed through the documentary analysis to facilitate understanding of the study. Surveys will also be used for data collection and students' background statistics. The integration of both interviews and surveys will provide a comprehensive array of student perspectives across various academic disciplines. The study is anchored in the theoretical framework of self-determination theory (SDT), which emphasizes and explains the students' perspective under the AI guidelines through three core needs: autonomy, competence, and relatedness. This framework is instrumental in understanding how AI guidelines influence students' intrinsic motivation and sense of empowerment in their learning environments. Through qualitative analysis, the study reveals a sense of confusion and uncertainty among students regarding the appropriate application and ethical considerations of AI tools, indicating potential challenges in meeting their needs for competence and autonomy. The quantitative data further elucidates these findings, highlighting a significant communication gap between students and educators in the formulation and implementation of AI guidelines. The critical findings of this study mainly come from two aspects: First, the majority of graduate students are uncertain and confused about relevant AI guidelines given by teachers. Second, this study also demonstrates that the design and effectiveness of course materials, such as the syllabi and instructions, also need to adapt in regard to AI policies. It indicates that certain of the existing guidelines provided by teachers lack consideration of students' perspectives, leading to a misalignment with students' needs for autonomy, competence, and relatedness. More emphasize and efforts need to be dedicated to both teacher and student training on AI policies and ethical considerations. To conclude, in this study, graduate students' perspectives on teacher-provided AI guidelines are explored and reflected upon, calling for additional training and strategies to improve how these guidelines can be better disseminated for their effective integration and adoption. Although AI guidelines provided by teachers may be helpful and provide new insights for students, educational institutions should take a more anchoring role to foster a motivating, empowering, and student-centered learning environment. The study also provides some relevant recommendations, including guidance for students on the ethical use of AI and AI policy training for teachers in higher education.

Keywords: higher education policy, graduate students’ perspectives, higher education teacher, AI guidelines, AI in education

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Authors: dr. Bendes Ákos

Abstract:

Digital skepticism, a critical stance towards digital technology and its pervasive influence on society, presents significant challenges when analyzed from a legal philosophical perspective. This abstract aims to explore the intersection of digital skepticism and legal philosophy, emphasizing the implications for justice, rights, and the rule of law in the digital age. Digital skepticism arises from concerns about privacy, security, and the ethical implications of digital technology. It questions the extent to which digital advancements enhance or undermine fundamental human values. Legal philosophy, which interrogates the foundations and purposes of law, provides a framework for examining these concerns critically. One key area where digital skepticism and legal philosophy intersect is in the realm of privacy. Digital technologies, particularly data collection and surveillance mechanisms, pose substantial threats to individual privacy. Legal philosophers must grapple with questions about the limits of state power and the protection of personal autonomy. They must consider how traditional legal principles, such as the right to privacy, can be adapted or reinterpreted in light of new technological realities. Security is another critical concern. Digital skepticism highlights vulnerabilities in cybersecurity and the potential for malicious activities, such as hacking and cybercrime, to disrupt legal systems and societal order. Legal philosophy must address how laws can evolve to protect against these new forms of threats while balancing security with civil liberties. Ethics plays a central role in this discourse. Digital technologies raise ethical dilemmas, such as the development and use of artificial intelligence and machine learning algorithms that may perpetuate biases or make decisions without human oversight. Legal philosophers must evaluate the moral responsibilities of those who design and implement these technologies and consider the implications for justice and fairness. Furthermore, digital skepticism prompts a reevaluation of the concept of the rule of law. In an increasingly digital world, maintaining transparency, accountability, and fairness becomes more complex. Legal philosophers must explore how legal frameworks can ensure that digital technologies serve the public good and do not entrench power imbalances or erode democratic principles. Finally, the intersection of digital skepticism and legal philosophy has practical implications for policy-making. Legal scholars and practitioners must work collaboratively to develop regulations and guidelines that address the challenges posed by digital technology. This includes crafting laws that protect individual rights, ensure security, and promote ethical standards in technology development and deployment. In conclusion, digital skepticism provides a crucial lens for examining the impact of digital technology on law and society. A legal philosophical approach offers valuable insights into how legal systems can adapt to protect fundamental values in the digital age. By addressing privacy, security, ethics, and the rule of law, legal philosophers can help shape a future where digital advancements enhance, rather than undermine, justice and human dignity.

Keywords: legal philosophy, privacy, security, ethics, digital skepticism

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Authors: Zakaria Baka, Halima Alem

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Cancer is a major worldwide health problem that has caused around ten million deaths in 2020. In addition, efforts to develop new anti-cancer drugs still face a high failure rate. This is partly due to the lack of preclinical models that recapitulate in-vivo drug responses. Indeed conventional cell culture approach (known as 2D cell culture) is far from reproducing the complex, dynamic and three-dimensional environment of tumors. To set up more in-vivo-like cancer models, 3D bioprinting seems to be a promising technology due to its ability to achieve 3D scaffolds containing different cell types with controlled distribution and precise architecture. Moreover, the introduction of microfluidic technology makes it possible to simulate in-vivo dynamic conditions through the so-called “cancer-on-chip” platforms. Whereas several cancer types have been modeled through the cancer-on-chip approach, such as lung cancer and breast cancer, only a few works describing ovarian cancer models have been described. The aim of this work is to combine 3D bioprinting and microfluidic technics with setting up a 3D dynamic model of ovarian cancer. In the first phase, alginate-gelatin hydrogel containing SKOV3 cells was used to achieve tumor-like structures through an extrusion-based bioprinter. The desired form of the tumor-like mass was first designed on 3D CAD software. The hydrogel composition was then optimized for ensuring good and reproducible printability. Cell viability in the bioprinted structures was assessed using Live/Dead assay and WST1 assay. In the second phase, these bioprinted structures will be included in a microfluidic device that allows simultaneous testing of different drug concentrations. This microfluidic dispositive was first designed through computational fluid dynamics (CFD) simulations for fixing its precise dimensions. It was then be manufactured through a molding method based on a 3D printed template. To confirm the results of CFD simulations, doxorubicin (DOX) solutions were perfused through the dispositive and DOX concentration in each culture chamber was determined. Once completely characterized, this model will be used to assess the efficacy of anti-cancer nanoparticles developed in the Jean Lamour institute.

Keywords: 3D bioprinting, ovarian cancer, cancer-on-chip models, microfluidic techniques

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Authors: Evgeniya V. Gavrilova, Sofya S. Belova

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The present study was aimed at clarifying the relationship between general intellectual abilities and efficiency in free recall and rhymed words generation task after incidental exposure to linguistic stimuli. The theoretical frameworks stress that general intellectual abilities are based on intentional mental strategies. In this context, it seems to be crucial to examine the efficiency of incidentally presented information processing in cognitive task and its relation to general intellectual abilities. The sample consisted of 32 Russian students. Participants were exposed to pairs of words. Each pair consisted of two common nouns or two city names. Participants had to decide whether a city name was presented in each pair. Thus words’ semantics was processed intentionally. The city names were considered to be focal stimuli, whereas common nouns were considered to be peripheral stimuli. Along with that each pair of words could be rhymed or not be rhymed, but this phonemic aspect of stimuli’s characteristic (rhymed and non-rhymed words) was processed incidentally. Then participants were asked to produce as many rhymes as they could to new words. The stimuli presented earlier could be used as well. After that, participants had to retrieve all words presented earlier. In the end, verbal and non-verbal abilities were measured with number of special psychometric tests. As for free recall task intentionally processed focal stimuli had an advantage in recall compared to peripheral stimuli. In addition all the rhymed stimuli were recalled more effectively than non-rhymed ones. The inverse effect was found in words generation task where participants tended to use mainly peripheral stimuli compared to focal ones. Furthermore peripheral rhymed stimuli were most popular target category of stimuli that was used in this task. Thus the information that was processed incidentally had a supplemental influence on efficiency of stimuli processing as well in free recall as in word generation task. Different patterns of correlations between intellectual abilities and efficiency in different stimuli processing in both tasks were revealed. Non-verbal reasoning ability correlated positively with free recall of peripheral rhymed stimuli, but it was not related to performance on rhymed words’ generation task. Verbal reasoning ability correlated positively with free recall of focal stimuli. As for rhymed words generation task, verbal intelligence correlated negatively with generation of focal stimuli and correlated positively with generation of all peripheral stimuli. The present findings lead to two key conclusions. First, incidentally processed stimuli had an advantage in free recall and word generation task. Thus incidental information processing appeared to be crucial for subsequent cognitive performance. Secondly, it was demonstrated that incidentally processed stimuli were recalled more frequently by participants with high nonverbal reasoning ability and were more effectively used by participants with high verbal reasoning ability in subsequent cognitive tasks. That implies that general intellectual abilities could benefit from operating by different levels of information processing while cognitive problem solving. This research was supported by the “Grant of President of RF for young PhD scientists” (contract № is 14.Z56.17.2980- MK) and the Grant № 15-36-01348a2 of Russian Foundation for Humanities.

Keywords: focal and peripheral stimuli, general intellectual abilities, incidental information processing

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Authors: Idoia Landa Oregi, Itsaso Gonzalez Ochoantesana, Olatz Nicolas Buxens, Carlo Ferretti

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The impact of citizens in urban transformations has become increasingly important in the pursuit of creating citizen-centered cities. Citizens at the forefront of the urban transformation process are key to establishing resilient, sustainable, and inclusive cities that cater to the needs of all residents. Therefore, collecting data and information directly from citizens is crucial for the sustainable development of cities. Within this context, public participation becomes a pillar for acquiring the necessary information from citizens. Public participation in urban transformation processes establishes a more responsive, equitable, and resilient urban environment. This approach cultivates a sense of shared responsibility and collective progress in building cities that truly serve the well-being of all residents. However, the implementation of public participation practices often overlooks strategies to effectively engage citizens in the processes, resulting in non-successful participatory outcomes. Therefore, this research focuses on identifying and analyzing the critical aspects of citizen engagement during the same participatory urban transformation process in different European contexts: Ermua (Spain), Elva (Estonia) and Matera (Italy). The participatory neighborhood regeneration process is divided into three main stages, to turn social districts into inclusive and smart neighborhoods: (i) the strategic level, (ii) the design level, and (iii) the implementation level. In the initial stage, the focus is on diagnosing the neighborhood and creating a shared vision with the community. The second stage centers around collaboratively designing various action plans to foster inclusivity and intelligence while pushing local economic development within the district. Finally, the third stage ensures the proper co-implementation of the designed actions in the neighborhood. To this date, the presented results critically analyze the key aspects of engagement in the first stage of the methodology, the strategic plan, in the three above-mentioned contexts. It is a multifaceted study that incorporates three case studies to shed light on the various perspectives and strategies adopted by each city. The results indicate that despite of the various cultural contexts, all cities face similar barriers when seeking to enhance engagement. Accordingly, the study identifies specific challenges within the participatory approach across the three cities such as the existence of discontented citizens, communication gaps, inconsistent participation, or administration resistance. Consequently, key learnings of the process indicate that a collaborative sphere needs to be cultivated, educating both citizens and administrations in the aspects of co-governance, giving these practices the appropriate space and their own communication channels. This study is part of the DROP project, funded by the European Union, which aims to develop a citizen-centered urban renewal methodology to transform the social districts into smart and inclusive neighborhoods.

Keywords: citizen-centred cities, engagement, public participation, urban transformation

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Authors: Krunal Thakar

Abstract:

Wire ropes combine high tensile strength and flexibility as compared to other general steel products. They are used in various application areas such as cranes, mining, elevators, bridges, cable cars, etc. The earliest reported use of wire ropes was for mining hoist application in 1830s. Over the period, there have been substantial advancement in the design of wire ropes for various application areas. Under operational conditions, wire ropes are subjected to varying tensile loads and bending loads resulting in material wear and eventual structural failure due to fretting fatigue. The conventional inspection methods to determine wire failure is only limited to outer wires of rope. However, till date, there is no effective mathematical model to examine the inter wire contact forces and wear characteristics. The scope of this paper is to present a computational simulation technique to evaluate inter wire contact forces and wear, which are in many cases responsible for rope failure. Two different type of ropes, IWRC-6xFi(29) and U3xSeS(48) were taken for structural strength evaluation and wear prediction. Both ropes have a double helix twisted wire profile as per JIS standards and are mainly used in cranes. CAD models of both ropes were developed in general purpose design software using in house developed formulation to generate double helix profile. Numerical simulation was done under two different load cases (a) Axial Tension and (b) Bending over Sheave. Different parameters such as stresses, contact forces, wear depth, load-elongation, etc., were investigated and compared between both ropes. Numerical simulation method facilitates the detailed investigation of inter wire contact and wear characteristics. In addition, various selection parameters like sheave diameter, rope diameter, helix angle, swaging, maximum load carrying capacity, etc., can be quickly analyzed.

Keywords: steel wire ropes, numerical simulation, material wear, structural strength, axial tension, bending over sheave

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Francesca Marsili

Abstract:

The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

Procedia PDF Downloads 335