Search results for: periodic function

Authors: Byoungjoon Yu, Jihwan Park, Sujung Sin, Junghyun Im, Minsoo Park, Sehwan Park, Seunghee Park

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In this paper, we propose a technology to monitor the soundness of an Internet-based bridge using a non-conductive inspection function. There has been a collapse accident due to the aging of the bridge structure, and it is necessary to prepare for the deterioration of the bridge. The NDT/SHM system for maintenance of existing bridge structures requires a large number of inspection personnel and expensive inspection costs, and access of expensive and large equipment to measurement points is required. Because current drone inspection equipment can only be inspected through camera, it is difficult to inspect inside damage accurately, and the results of an internal damage evaluation are subjective, and it is difficult for non-specialists to recognize the evaluation results. Therefore, it is necessary to develop NDT/SHM techniques for maintenance of new-concept bridge structures that allow for free movement and real-time evaluation of measurement results. This work is financially supported by Korea Ministry of Land, Infrastructure, and Transport (MOLIT) as 'Smart City Master and Doctor Course Grant Program' and a grant (14SCIP-B088624-01) from Construction Technology Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: Structural Health Monitoring, SHM, non-contact sensing, nondestructive testing, NDT, Internet of Things, autonomous self-driving drone

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Authors: Wanhyun Cho, Seongchae Seo, Soonja Kang

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In this work, we propose a variational technique for image contrast enhancement which utilizes global and local information around each pixel. The energy functional is defined by a weighted linear combination of three terms which are called on a local, a global contrast term and dispersion term. The first one is a local contrast term that can lead to improve the contrast of an input image by increasing the grey-level differences between each pixel and its neighboring to utilize contextual information around each pixel. The second one is global contrast term, which can lead to enhance a contrast of image by minimizing the difference between its empirical distribution function and a cumulative distribution function to make the probability distribution of pixel values becoming a symmetric distribution about median. The third one is a dispersion term that controls the departure between new pixel value and pixel value of original image while preserving original image characteristics as well as possible. Second, we derive the Euler-Lagrange equation for true image that can achieve the minimum of a proposed functional by using the fundamental lemma for the calculus of variations. And, we considered the procedure that this equation can be solved by using a gradient decent method, which is one of the dynamic approximation techniques. Finally, by conducting various experiments, we can demonstrate that the proposed method can enhance the contrast of colour images better than existing techniques.

Keywords: color image, contrast enhancement technique, variational approach, Euler-Lagrang equation, dynamic approximation method, EME measure

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Authors: Evangelia-Chrysanthi Kouklari, Evdokia Tagkouli, Vassiliki Ntre, Artemios Pehlivanidis, Stella Tsermentseli, Gerasimos Kolaitis, Katerina Papanikolaou

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Executive Function (EF) is a set of goal-directed cognitive skills essentially needed in problem-solving and social behavior. Developmental EF research has indicated that EF emerges early in life and marks dramatic changes before the age of 5. Research evidence has suggested that it may continue to develop up to adolescence as well, following the development of the prefrontal cortex. Over the last decade, research evidence has suggested distinguished domains of cool and hot EF, but traditionally the development of EF in Autism Spectrum Disorder (ASD) has been examined mainly with tasks that address the “cool” cognitive aspects of EF. Thus, very little is known about the development of “hot” affective EF processes and whether the cross-sectional developmental pathways of cool and hot EF present similarities in ASD. Cool EF has also been proven to have a strong correlation with Theory of Mind (ToM) in young and middle childhood in typical development and in ASD, but information about the relationship of hot EF to ToM skills is minimal. The present study’s objective was to explore the age-related changes of cool and hot EF in ASD participants from middle childhood to adolescence, as well as their relationship to ToM. This study employed an approach of cross-sectional developmental trajectories to investigate patterns of cool and hot EF relative to chronological age within ASD. Eighty-two participants between 7 and 16 years of age were recruited to undertake measures that assessed cool EF (working memory, cognitive flexibility, planning & inhibition), hot EF (affective decision making & delay discounting) and ToM (false belief and mental state/emotion recognition). Results demonstrated that trajectories of all cool EF presented age-related changes in ASD (improvements with age). With regards to hot EF, affective decision-making presented age-related changes, but for delay discounting, there were no statistically significant changes found across younger and older ASD participants. ToM was correlated only to cool EF. Theoretical implications are discussed as the investigation of the cross-sectional developmental trajectories of the broader EF (cool and hot domains) may contribute to better defining cognitive phenotypes in ASD. These findings highlight the need to examine developmental trajectories of both hot and cool EF in research and clinical practice as they may aid in enhancing diagnosis or better-informed intervention programs.

Keywords: autism spectrum disorder, developmental trajectories, executive function, theory of mind

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Authors: Jongsung Kim, Daegun Han, Myungjin Lee, Soojun Kim, Hung Soo Kim

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Recently, the frequency and magnitude of natural disasters are gradually increasing due to climate change. Especially in Korea, large-scale damage caused by heavy rainfall frequently occurs due to rapid urbanization. Therefore, this study proposed a Heavy rain Damage Risk Index (HDRI) using PSR (Pressure – State - Response) structure for heavy rain risk assessment. We constructed pressure index, state index, and response index for the risk assessment of each local government in Gyeonggi-do province, and the evaluation indices were determined by principal component analysis. The indices were standardized using the Z-score method then HDRIs were obtained for 31 local governments in the province. The HDRI is categorized into three classes, say, the safest class is 1st class. As the results, the local governments of the 1st class were 15, 2nd class 7, and 3rd class 9. From the study, we were able to identify the risk class due to the heavy rainfall for each local government. It will be useful to develop the heavy rainfall prediction function by risk class, and this was performed in this issue. Also, this risk class could be used for the decision making for efficient disaster management. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B3005695).

Keywords: natural disaster, heavy rain risk assessment, HDRI, PSR

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Authors: Hsin-Lien Lin, Ju-Hui Fu

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Dendritic cells (DCs) are the major professional antigen-presenting cells for the development of optimal T-cell immunity. DCs can be used as pharmacological targets to screen novel biological modifiers for the treatment of harmful immune responses, such as transplantation rejection. Dryopteris crassirhizoma Nakai (Aspiadaceae) is used for traditional herbal medicine in the region of East Asia. The root of this fern plant has been listed for treating inflammatory diseases. Dryocrassin is the tetrameric phlorophenone component derived from Dryopteris. Here, we tested the immunomodulatory potential of dryocrassin on lipopolysaccharide (LPS)-stimulated activation of mouse bone marrow-derived DCs in vitro and in skin allograft transplantation in vivo. Results demonstrated that dryocrassin reduced the secretion of tumor necrosis factor-α, interleukin-6, and interleukin-12p70 by LPS-stimulated DCs. The expression of LPS-induced major histocompatibility complex class II, CD40, and CD86 on DCs was also blocked by dryocrassin. Moreover, LPS-stimulated DC-elicited allogeneic T-cell proliferation was lessened by dryocrassin. In addition, dryocrassin inhibited LPS-induced activation of IϰB kinase, JNK/p38 mitogen-activated protein kinase, as well as the translocation of NF-ϰB. Treatment with dryocrassin obviously diminished 2,4-dinitro-1-fluorobenzene- induced delayed-type hypersensitivity and prolonged skin allograft survival. Dryocrassin may be one of the potent immunosuppressive agents for transplant rejection through the destruction of DC maturation and function.

Keywords: dryocrassin, dendritic cells, immunosuppression, skin allograft

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Authors: Bastien Batardière, Joon Kwon

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For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

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Authors: Carolina Pereira Lobato Costa, Cristina Pascual-González, Monica Echeverry, Javier LLorca, Carlos Gonzáléz, Juan Pedro Fernández-Bláquez

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Although the potential of PLA self-reinforced composites for bone applications, not much literature addresses optimal manufacturing conditions. In this regard, this paper describes the woven self-reinforced PLA composites manufacturing processes: the commingling of yarns, weaving, and hot pressing and characterizes the manufactured laminates. Different structures and properties can be achieved by varying the hot compaction process parameters (pressure, holding time, and temperature). The specimens manufactured were characterized in terms of thermal properties (DSC), microstructure (C-scan optical microscope and SEM), strength (tensile test), and biocompatibility (MTT assays). Considering the final device, 155 ℃ for 10 min at 2 MPa act as the more appropriate hot pressing parameters. The laminate produced with these conditions has few voids/porosity, a tensile strength of 30.39 ± 1.21 MPa, and a modulus of 4.09 ± 0.24 GPa. Subsequently to the tensile testing was possible to observe fiber pullout from the fracture surfaces, confirming that this material behaves as a composite. From the results, no single laminate can fulfill all the requirements, being necessary to compromise in function of the priority property. Further investigation is required to improve materials' mechanical performance. Subsequently, process parameters and materials configuration can be adjusted depending on the place and type of implant to suit its function.

Keywords: woven fabric, self-reinforced polymer composite, poly(lactic acid), biodegradable

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Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: Yuan-Jye Tseng, Jia-Shu Li

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To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.

Keywords: design for supply chain, design evaluation, functional design, Kansei design, fuzzy analytic network process, technique for order preference by similarity to ideal solution

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Authors: Pratibha, Jyoti Kori

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Particles in industry, harvesting, coal mines, etc. may not necessarily be spherical in shape. In general, it is difficult to find perfectly spherical particle. The prediction of movement and deposition of non spherical particle in distinct airway generation is much more difficult as compared to spherical particles. Moreover, there is extensive inflexibility in deposition between ducts of a particular generation and inside every alveolar duct since particle concentrations can be much bigger than the mean acinar concentration. Consequently, a large number of particles fail to be exhaled during expiration. This study presents a mathematical model for the movement and deposition of those non-spherical particles by using particle aspect ratio and shape factor. We analyse the pulsatile behavior underneath sinusoidal wall oscillation due to periodic breathing condition through a non-Darcian porous medium or inside pulmonary region. Since the fluid is viscous and Newtonian, the generalized Navier-Stokes equation in two-dimensional coordinate system (r, z) is used with boundary-layer theory. Results are obtained for various values of Reynolds number, Womersley number, Forchsheimer number, particle aspect ratio and shape factor. Numerical computation is done by using finite difference scheme for very fine mesh in MATLAB. It is found that the overall air velocity is significantly increased by changes in aerodynamic diameter, aspect ratio, alveoli size, Reynolds number and the pulse rate; while velocity is decreased by increasing Forchheimer number.

Keywords: deposition, interstitial lung diseases, non-Darcian medium, numerical simulation, shape factor

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Authors: Izabela Zielinska

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Kinesio Taping is classified as physiotherapy method supporting rehabilitation and modulating some physiological processes. It is commonly used in sports medicine and orthopedics. This sensory method has influence on muscle function, pain sensation, intensifies lymphatic system as well as improves microcirculation. The aim of this study was to assess the effect of Kinesio Taping in patients with ongoing treatment of peripheral artery disease (PAD). The study group comprised 60 patients (stadium II B at Fontain's scale). All patients were divided into two groups (30 person/each), where 12 weeks long treadmill training was administrated. In the second group, the Kinesio Taping was applied to support the function of the gastrocnemius muscle. The measurements of distance and time until claudication pain, blood flow of arteries in lower limbs and ankle brachial index were taken under evaluation. Examination performed after Kinesio Taping therapy showed statistically significant increase in gait parameters and muscle strength in patients with intermittent claudication. The Kinesio Taping method has clinically significant effects on enhancement of pain-free distance and time until claudication pain in patients with peripheral artery disease. Kinesio Taping application can be used to support non-invasive treatment in patients with intermittent claudication. Kinesio Taping can be employed as an alternative way of therapy for patients with orthopedic or cardiac contraindications to be treated with treadmill training.

Keywords: intermittent claudication, kinesiotaping, peripheral artery disease, treadmill training

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Authors: Hongbin Yang, Mingxue Liao, Changwen Zheng, Mengyao Kong, Chaohui Liu

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Microfacet-based reflection models are widely used to model light reflections for rough surfaces. Microfacet models have become the standard surface material building block for describing specular components with varying roughness; and yet, while they possess many desirable properties as well as produce convincing results, their design ignores important sources of scattering, which can cause a significant loss of energy. Specifically, they only simulate the single scattering on the microfacets and ignore the subsequent interactions. As the roughness increases, the interaction will become more and more important. So a multiple-scattering microfacet model based on specular V-cavity is presented for this important open problem. However, it spends much unnecessary rendering time because of setting the same number of scatterings for different roughness surfaces. In this paper, we design a geometric attenuation term G to compute the BRDF (Bidirectional reflection distribution function) of multiple scattering of rough surfaces. Moreover, we consider determining the number of scattering by deterministic heuristics for different roughness surfaces. As a result, our model produces a similar appearance of the objects with the state of the art model with significantly improved rendering efficiency. Finally, we derive a multiple scattering BRDF based on the original microfacet framework.

Keywords: bidirectional reflection distribution function, BRDF, geometric attenuation term, multiple scattering, V-cavity model

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Authors: Moez Yeddes

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The property of opacity is widely used in the formal verification of security in computer systems and protocols. Opacity is a general language-theoretic scheme of many security properties of systems. Opacity is parametrized with framework in which several security properties of a system can be expressed. A secret behaviour of a system is opaque if a passive attacker can never deduce its occurrence from the system observation. Instead of considering the case of static observability where the set of observable events is fixed off-line or dynamic observability where the set of observable events changes over time depending on the history of the trace, we introduce Orwellian partial observability where unobservable events are not revealed provided that downgrading events never occurs in the future of the trace. Orwellian partial observability is needed to model intransitive information flow. This Orwellian observability is knwon as ipurge function. We show in previous work how to verify opacity for regular secret is opaque for a regular language L w.r.t. an Orwellian projection is PSPACE-complete while it has been proved undecidable even for a regular language L w.r.t. a general Orwellian observation function. In this paper, we address two problems of opacification of a regular secret ϕ for a regular language L w.r.t. an Orwellian projection: Given L and a secret ϕ ∈ L, the first problem consist to compute some minimal regular super-language M of L, if it exists, such that ϕ is opaque for M and the second consists to compute the supremal sub-language M′ of L such that ϕ is opaque for M′. We derive both language-theoretic characterizations and algorithms to solve these two dual problems.

Keywords: security policies, opacity, formal verification, orwellian observation

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Authors: Mohammadreza Nezamirad, Sepideh Amirahmadian, Nasim Sabetpour, Azadeh Yazdi, Amirmasoud Hamedi

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Cavitation inside diesel injector nozzle is investigated using Reynolds-Stress-Navier Stokes equations. Schnerr-Sauer cavitation model is used for modeling cavitation inside diesel injector nozzle. The carrying fluid utilized in the current study is diesel fuel. The flow is verified at the beginning by comparing with the previous experimental data, and it was found that K-Epsilon turbulent model could lead to a better accuracy comparing to K-Omega turbulent model. Moreover, the mass flow rate obtained numerically is compared with the experimental value, and the discrepancy was found to be less than 5 percent which shows the accuracy of the current results. Finally, a real-size four-hole nozzle is investigated, and the flow inside it is visualized based on velocity profile, discharge coefficient, and cavitation number. It was found that the mesh density could be reduced significantly by utilizing periodic boundary conditions. Velocity contour at the mid nozzle showed that the maximum value of velocity occurs at the end of the needle before entering the orifice area. Last but not least, at the same boundary conditions, when different needle heights were utilized, it was found that as needle height increases with an increase in cavitation number, discharge coefficient increases, while the mentioned increases are more tangible at smaller values of needle heights.

Keywords: cavitation, diesel fuel, CFD, real size nozzle, mass flow rate

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Authors: Vemula Amalakrishna, S. Pushpavanam

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Change and motion characterize and persistently reshape the world around us, on scales from molecular to global. The subtle interplay between change (Reaction) and motion (Diffusion) gives rise to an astonishing intricate spatial or temporal pattern. These pattern formation in nature has been intellectually appealing for many scientists since antiquity. Periodic precipitation patterns, also known as Liesegang patterns (LP), are one of the stimulating examples of such self-assembling reaction-diffusion (RD) systems. LP formation has a great potential in micro and nanotechnology. So far, the research on LPs has been concentrated mostly on how these patterns are forming, retrieving information to build a universal mathematical model for them. Researchers have developed various theoretical models to comprehensively construct the geometrical diversity of LPs. To the best of our knowledge, simulation studies of LPs assume an arbitrary value of RD parameters to explain experimental observation qualitatively. In this work, existing models were studied to understand the mechanism behind this phenomenon and challenges pertaining to models were understood and explained. These models are not computationally effective due to the presence of discontinuous precipitation rate in RD equations. To overcome the computational challenges, smoothened Heaviside functions have been introduced, which downsizes the computational time as well. Experiments were performed using a conventional LP system (AgNO₃-K₂Cr₂O₇) to understand the effects of different gels and temperatures on formed LPs. The model is extended for real parameter values to compare the simulated results with experimental data for both 1-D (Cartesian test tubes) and 2-D(cylindrical and Petri dish).

Keywords: reaction-diffusion, spatio-temporal patterns, nucleation and growth, supersaturation

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Authors: Korban Oosthuizen, Robert C. Luckay

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Due to the growing popularity of electric vehicles and the importance of cobalt as part of the cathode material for lithium-ion batteries, demand for this metal is on the rise. Recycling of the cathode materials by means of solvent extraction is an attractive means of recovering cobalt and easing the pressure on limited natural resources. In this study, a series of straight chain and macrocyclic diamine ligands were developed for the selective recovery of cobalt from the solution containing nickel and manganese by means of solvent extraction. This combination of metals is the major cathode material used in electric vehicle batteries. The ligands can be protonated and function as ion-pairing ligands targeting the anionic [CoCl₄]²⁻, a species which is not observed for Ni or Mn. Selectivity for Co was found to be good at very high chloride concentrations and low pH. Longer chains or larger macrocycles were found to enhance selectivity, and linear chains on the amide side groups also resulted in greater selectivity over the branched groups. The cation of the chloride salt used for adjusting chloride concentrations seems to play a major role in extraction through salting-out effects. The ligands developed in this study show good selectivity for Co over Ni and Mn but require very high chloride concentrations to function. This research does, however, open the door for further investigations into using diamines as solvent extraction ligands for the recovery of cobalt from spent lithium-ion batteries.

Keywords: hydrometallurgy, solvent extraction, cobalt, lithium-ion batteries

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Authors: Jatupon Em-Udom, Nirand Pisutha-Arnond

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The phase-field-crystal, PFC, approach is a density-functional-type material model with an atomic resolution on a diffusive timescale. Spatially, the model incorporates periodic nature of crystal lattices and can naturally exhibit elasticity, plasticity and crystal defects such as grain boundaries and dislocations. Temporally, the model operates on a diffusive timescale which bypasses the need to resolve prohibitively small atomic-vibration time steps. The PFC model has been used to study many material phenomena such as grain growth, elastic and plastic deformations and solid-solid phase transformations. In this study, the pressure-controlled dynamic equation for the PFC model was developed to simulate a single-component system under externally applied pressure; these coupled equations are important for studies of deformable systems such as those under constant pressure. The formulation is based on the non-equilibrium thermodynamics and the thermodynamics of crystalline solids. To obtain the equations, the entropy variation around the equilibrium point was derived. Then the resulting driving forces and flux around the equilibrium were obtained and rewritten as conventional thermodynamic quantities. These dynamics equations are different from the recently-proposed equations; the equations in this study should provide more rigorous descriptions of the system dynamics under externally applied pressure.

Keywords: driving forces and flux, evolution equation, non equilibrium thermodynamics, Onsager’s reciprocal relation, phase field crystal model, thermodynamics of single-component solid

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Authors: Mehmet Ali Kisaçam, P. Sema Temizer Ozan, Ayşe Doğan, Gonca Ozan, F. Sarper Türker

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Cardiovascular disease which is one of the most common health problems worldwide has crucial importance because of its’ morbidity and mortality rates. Nitric oxide synthase and arginase use L-arginine as a substrate and produce nitric oxide (NO), citrulline and urea, ornithine respectively. Endothelial dysfunction is characterized by reduced bioavailability of vasodilator and anti-inflammatory molecule NO. The purpose of the study to assess endothelial function via arginase activity and NO levels in patients undergoing coronary artery bypass grafting (CABG) surgery. The study was conducted on 26 patients (14 male, 12 female) undergoing CABG surgery. Blood samples were collected from the subjects before surgery, after the termination and after 24 hours of the surgery. Arginase activity and NO levels measured in collected samples spectrophotometrically. Arginase activity decreased significantly in subjects after the termination of the surgery compared to before surgery data. 24 hours after the surgery there wasn’t any significance in arginase activity as it compared to before surgery and after the termination of the surgery. On the other hand, NO levels increased significantly in the subject after the termination of the surgery. However there was no significant increase in NO levels after 24 hours of the surgery, but there was an insignificant increase compared to before surgery data. The results indicate that after the termination of the surgery vascular and endothelial function improved and after 24 hours of the surgery arginase activity and NO levels returned to normal.

Keywords: arginase, bypass, cordiopulmonary, nitric oxide

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Authors: Aruha Khan, Brynn E. Kankel, Paraskevi Papadopoulou

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In recent years, extensive research upon ‘stress’ has provided insight into its two distinct guises, namely the short–term (fight–or–flight) response versus the long–term (chronic) response. Specifically, the long–term or chronic response is associated with the suppression or dysregulation of immune function. It is also widely noted that the occurrence of cancer is greatly correlated to the suppression of the immune system. It is thus necessary to explore the impact of long–term or chronic stress upon the prevalence and risk of cancer. To what extent can the dysregulation of immune function caused by long–term exposure to stress be controlled or minimized? This study focuses explicitly upon immunosuppression due to its ability to increase disease susceptibility, including cancer itself. Based upon an analysis of the literature relating to the fundamental structure of the immune system alongside the prospective linkage of chronic stress and the development of cancer, immunosuppression may not necessarily correlate directly to the acquisition of cancer—although it remains a contributing factor. A cross-sectional analysis of the survey data from the University of Tennessee Medical Center (UTMC) and Harvard Medical School (HMS) will provide additional supporting evidence (or otherwise) for the hypothesis of the study about whether immunosuppression (caused by the chronic stress response) notably impacts the prevalence of cancer. Finally, a multidimensional framework related to education on chronic stress and its effects is proposed.

Keywords: immune system, immunosuppression, long–term (chronic) stress, risk of cancer

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Authors: Ranjith Maniyeri, Ahamed C. Saleel

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Two-dimensional fluid flow over a stationary circular cylinder is one of the bench mark problem in the field of fluid-structure interaction in computational fluid dynamics (CFD). Motivated by this, in the present work, a two-dimensional computational model is developed using an improved version of immersed boundary method which combines the feedback forcing scheme of the virtual boundary method with Peskin’s regularized delta function approach. Lagrangian coordinates are used to represent the cylinder and Eulerian coordinates are used to describe the fluid flow. A two-dimensional Dirac delta function is used to transfer the quantities between the sold to fluid domain. Further, continuity and momentum equations governing the fluid flow are solved using fractional step based finite volume method on a staggered Cartesian grid system. The developed code is validated by comparing the values of drag coefficient obtained for different Reynolds numbers with that of other researcher’s results. Also, through numerical simulations for different Reynolds numbers flow behavior is well captured. The stability analysis of the improved version of immersed boundary method is tested for different values of feedback forcing coefficients.

Keywords: Feedback Forcing Scheme, Finite Volume Method, Immersed Boundary Method, Navier-Stokes Equations

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Authors: Zahra Azizi, Ashkan Karbasi, Farzin Firouzian, Sara Soleimani Asl, Akram Ranjbar

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Background: One of the most often used herbicides in agriculture is paraquat (PQ), which is very harmful to both people and animals. Chitosan is a well-known, non-toxic polymer commonly used in preparing particles via ionotropic gelation facilitated by negatively charged agents such as sodium alginate. This study aimed to compare the effects of PQ and nanoparaquat (PQNPs) on liver function in male rats. Materials & Methods: Rats were exposed to PQ & PQNPs (4 mg/kg/day, intraperitoneally) for seven days. Then, rats were anesthetized, and serum and liver samples were collected. Later, enzymatic activities such as alanine transaminase (ALT), aspartate transaminase (AST), and alkaline phosphatase (ALP) in serum and oxidative stress biomarkers such as lipid peroxidation (LPO), total antioxidant capacity (TAC) and total thiol groups (TTG) levels in liver tissue were measured by colorimetric methods. Also, histological changes in the liver were evaluated. Results: PQ altered the levels of ALT, AST, and ALP while inducing oxidative stress in the liver. Additionally, liver homogenates with PQ exposure had challenged LPO, TAC, and TTG levels. The severe liver damage is indicated by a significant increase in the enzyme activity of AST, ALT, and ALP in serum. According to the results of the current study, PQNPs, as compared to PQ and the control group, lowered ALT, AST, ALP, and LPO levels while increasing TAC and TTG levels. Conclusion: According to biochemical and histological investigations, PQ loaded in chitosan-alginate particles is more efficient than free PQ at reducing liver toxicity.

Keywords: paraquat, paraquat nanoparticles, liver, oxidative stress

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Authors: Kinnsley Travis, Camerron M. Crowder

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Mapk8ip3 (Mitogen-Activated Protein Kinase 8 Interacting Protein 3) is a gene that codes for the JIP3 protein, which is a part of the JIP scaffolding protein family. This protein is involved in axonal vesicle transport, elongation and regeneration. Variants in the Mapk8ip3 gene are associated with a rare-genetic condition that results in a neurodevelopmental disorder that can cause a range of phenotypes including global developmental delay and intellectual disability. Currently, there are 18 known individuals diagnosed to have sequenced confirmed Mapk8ip3 genetic disorders. This project focuses on examining the impact of a subset of missense patient variants on the Jip3 protein function by overexpressing the mRNA of these variants in a zebrafish knockout model for Jip3. Plasmids containing cDNA with individual missense variants were reverse transcribed, purified, and injected into single-cell zebrafish embryos (Wild Type, Jip3 -/+, and Jip3 -/-). At 6-days post mRNA microinjection, morphological, behavioral, and microscopic phenotypes were examined in zebrafish larvae. Morphologically, we compared the size and shape of the zebrafish during their development over a 5-day period. Total locomotive activity was assessed using the Microtracker assay and patterns of movement over time were examined using the DanioVision assay. Lastly, we used confocal microscopy to examine sensory axons for swelling and shortened length, which are phenotypes observed in the loss-of-function knockout Jip3 zebrafish model. Using these assays during embryonic development, we determined the impact of various missense variants on Jip3 protein function, compared to knockout and wild-type zebrafish embryo models. Variants in the gene Mapk8ip3 cause rare-neurodevelopmental disorders due to an essential role in axonal vesicle transport, elongation and regeneration. A subset of missense variants was examined by overexpressing the mRNA of these variants in a Jip3 knock-out zebrafish. Morphological, behavioral, and microscopic phenotypes were examined in zebrafish larvae. Using these assays, the spectrum of disorders can be phenotypically determined and the impact of variant location can be compared to knockout and wild-type zebrafish embryo models.

Keywords: rare disease, neurodevelopmental disorders, mrna overexpression, zebrafish research

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Authors: Anisul Islam

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The U.S. has a very strong trade relationship with China but with a large and persistent trade deficit. Some has argued that the undervalued Chinese Yuan is to be blamed for the persistent trade deficit. The empirical results are mixed at best. This paper empirically estimates the U.S. export function along with the U.S. import function with its trade with China with the purpose of testing for the existence of the Marshall-Lerner (ML) condition as well for the possible existence of the J-curve hypothesis. Annual export and import data will be utilized for as long as the time series data exists. The export and import functions will be estimated using advanced econometric techniques, along with appropriate diagnostic tests performed to examine the validity and reliability of the estimated results. The annual time-series data covers from 1975 to 2022 with a sample size of 48 years, the longest period ever utilized before in any previous study. The data is collected from several sources, such as the World Bank’s World Development Indicators, IMF Financial Statistics, IMF Direction of Trade Statistics, and several other sources. The paper is expected to shed important light on the ongoing debate regarding the persistent U.S. trade deficit with China and the policies that may be useful to reduce such deficits over time. As such, the paper will be of great interest for the academics, researchers, think tanks, global organizations, and policy makers in both China and the U.S.

Keywords: exports, imports, marshall-lerner condition, j-curve hypothesis, united states, china

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

Procedia PDF Downloads 297

Authors: Guo Jinhong

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The purpose of this study is to explore the association between board member functions and information disclosure levels. Based on the literature variables, such as the characteristics of the board of directors in the past, a single comprehensive indicator is established as a substitute variable for board functions, and the information disclosure evaluation results published by the Securities and Foundation are used to measure the information disclosure level of the company. This study focuses on companies listed on the Taiwan Stock Exchange from 2006 to 2010 and uses descriptive statistical analysis, univariate analysis, correlation analysis and ordered normal probability (Ordered Probit) regression for empirical analysis. The empirical results show that there is a significant positive correlation between the function of board members and the level of information disclosure. This study also conducts a sensitivity test and draws similar conclusions, showing that boards with better board member functions have higher levels of information disclosure. In addition, this study also found that higher board independence, lower director shareholding pledge ratio, higher director shareholding ratio, and directors with rich professional knowledge and practical experience can help improve the level of information disclosure. The empirical results of this study provide strong support for the "relative regulations to improve the level of information disclosure" formulated by the competent authorities in recent years.

Keywords: function of board members, information disclosure, securities, foundation

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Authors: Filip Stojcevski, Tim Hilditch, Luke Henderson

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Although carbon fibre composites are becoming ever more prominent in the engineering industry, interfacial failure still remains one of the most common limitations to material performance. Carbon fiber surface treatments have played a major role in advancing composite properties however research into the influence of manufacturing variables on a fiber manufacturing line is lacking. This project investigates the impact of altering carbon fiber manufacturing conditions on a production line (specifically electrochemical oxidization and sizing variables) to assess fiber-matrix adhesion. Pristine virgin fibers were manufactured and interfacial adhesion systematically assessed from a microscale (single fiber) to a mesoscale (12k tow), and ultimately a macroscale (laminate). Correlations between interfacial shear strength (IFSS) at each level is explored as a function of known interfacial bonding mechanisms; namely mechanical interlocking, chemical adhesion and fiber wetting. Impact of these bonding mechanisms is assessed through extensive mechanical, topological and chemical characterisation. They are correlated to performance as a function of IFSS. Ultimately this study provides a bottoms up approach to improving composite laminates. By understanding the scaling effects from a singular fiber to a composite laminate and linking this knowledge to specific bonding mechanisms, material scientists can make an informed decision on the manufacturing conditions most beneficial for interfacial adhesion.

Keywords: carbon fibers, interfacial adhesion, surface treatment, sizing

Procedia PDF Downloads 265

Authors: Meziane Rachid, Boufala Seddik, Hamzi Amar, Amara Mohamed

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Today’s energy industry seeks maximum benefit with maximum reliability. In order to achieve this goal, design engineers depend on reliability optimization techniques. This work uses a harmony search algorithm (HS) meta-heuristic optimization method to solve the problem of wind-Solar-Gas power systems design optimization. We consider the case where redundant electrical components are chosen to achieve a desirable level of reliability. The electrical power components of the system are characterized by their cost, capacity and reliability. The reliability is considered in this work as the ability to satisfy the consumer demand which is represented as a piecewise cumulative load curve. This definition of the reliability index is widely used for power systems. The proposed meta-heuristic seeks for the optimal design of series-parallel power systems in which a multiple choice of wind generators, transformers and lines are allowed from a list of product available in the market. Our approach has the advantage to allow electrical power components with different parameters to be allocated in electrical power systems. To allow fast reliability estimation, a universal moment generating function (UMGF) method is applied. A computer program has been developed to implement the UMGF and the HS algorithm. An illustrative example is presented.

Keywords: reliability optimization, harmony search optimization (HSA), universal generating function (UMGF)

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Authors: Akeel Noori Almulla Hwaish

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Architectural design is influenced by the actual thermal behaviour of building components, and this in turn depends not only on their steady and periodic thermal characteristics, but also on exposure effects, orientation, surface colour, and climatic fluctuations at the given location. Design data and environmental parameters should be produced in an accurate way for specified locations, so that architects and engineers can confidently apply them in their design calculations that enable precise evaluation of the influence of various parameters relating to each component of the envelope, which indicates overall thermal performance of building. The present paper will be carried out with an objective of thermal behaviour assessment and characteristics of the opaque and transparent parts of one of the very unique components used as a symbolic distinguished element of building envelope, its thermal behaviour under the impact of solar temperatures, and its role in heat exchange related to a specific U-value of specified construction materials alternatives. The research method will consider the specified Hot-Dry weather and new mosque in Baghdad, Iraq as a case study. Also, data will be presented in light of the criteria of indoor thermal comfort in terms of design parameters and thermal assessment for a“model dome”. Design alternatives and considerations of energy conservation, will be discussed as well using comparative computer simulations. Findings will be incorporated to outline the conclusions clarifying the important role of the dome in heat exchange of the whole building envelope for approaching an indoor thermal comfort level and further research in the future.

Keywords: building envelope, sustainable design, dome impact, hot-climates, heat exchange

Procedia PDF Downloads 475

Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

Procedia PDF Downloads 311