Search results for: computational duration

Authors: Christine P. Gibson, Ramona Alex, Michael Farney, Johana Vallejo-Elias, Mitra Esfandiarei

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Aortic aneurysm is the leading cause of death in Marfan syndrome (MFS), a connective tissue disorder caused by mutations in fibrillin-1 gene (FBN1). MFS aneurysm is characterized by weakening of the aortic wall due to elastin fibers fragmentation and disorganization. The above-average height and distinct physical features make young adults with MFS desirable candidates for competitive sports; but little is known about the exercise limit at which they will be at risk for aortic rupture. On the other hand, aerobic cardiovascular exercise has been shown to have protective effects on the heart and aorta. We have previously reported that mild aerobic exercise can delay the formation of aortic aneurysm in a mouse model of MFS. In this study, we aimed to investigate the effects of various levels of exercise intensity on the progression of aortic aneurysm in the mouse model. Starting at 4 weeks of age, we subjected control and MFS mice to different levels of exercise intensity (8m/min, 10m/min, 15m/min, and 20m/min, corresponding to 55%, 65%, 75%, and 85% of VO2 max, respectively) on a treadmill for 30 minutes per day, five days a week for the duration of the study. At 24 weeks of age, aortic tissue were isolated and subjected to structural and functional studies using histology and wire myography in order to evaluate the effects of different exercise routines on elastin fragmentation and organization and aortic wall elasticity/stiffness. Our data shows that exercise training at the intensity levels between 55%-75% significantly reduces elastin fragmentation and disorganization, with less recovery observed in 85% MFS group. The reversibility of elasticity was also significantly restored in MFS mice subjected to 55%-75% intensity; however, the recovery was less pronounced in MFS mice subjected to 85% intensity. Furthermore, our data shows that smooth muscle cells (SMCs) contractilion in response to vasoconstrictor agent phenylephrine (100nM) is significantly reduced in MFS aorta (54.84 ± 1.63 mN/mm2) as compared to control (95.85 ± 3.04 mN/mm2). At 55% of intensity, exercise did not rescue SMCs contraction (63.45 ± 1.70 mN/mm2), while at higher intensity levels, SMCs contraction in response to phenylephrine was restored to levels similar to control aorta [65% (81.88 ± 4.57 mN/mm2), 75% (86.22 ± 3.84 mN/mm2), and 85% (83.91 ± 5.42 mN/mm2)]. This study provides the first time evidence that high intensity exercise (e.g. 85%) may not provide the most beneficial effects on aortic function (vasoconstriction) and structure (elastin fragmentation, aortic wall elasticity) during the progression of aortic aneurysm in MFS mice. On the other hand, based on our observations, medium intensity exercise (e.g. 65%) seems to provide the utmost protective effects on aortic structure and function in MFS mice. These findings provide new insights into the potential capacity, in which MFS patients could participate in various aerobic exercise routines, especially in young adults affected by cardiovascular complications particularly aortic aneurysm. This work was funded by Midwestern University Research Fund.

Keywords: aerobic exercise, aortic aneurysm, aortic wall elasticity, elastin fragmentation, Marfan syndrome

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Sajana Suwal, Ganesh R. Nhemafuki

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Evaluation of ground response under earthquake shaking is crucial in geotechnical earthquake engineering. Damage due to seismic excitation is mainly correlated to local geological and geotechnical conditions. It is evident from the past earthquakes (e.g. 1906 San Francisco, USA, 1923 Kanto, Japan) that the local geology has strong influence on amplitude and duration of ground motions. Since then significant studies has been conducted on ground motion amplification revealing the importance of influence of local geology on ground. Observations from the damaging earthquakes (e.g. Nigata and San Francisco, 1964; Irpinia, 1980; Mexico, 1985; Kobe, 1995; L’Aquila, 2009) divulged that non-uniform damage pattern, particularly in soft fluvio-lacustrine deposit is due to the local amplification of seismic ground motion. Non-uniform damage patterns are also observed in Kathmandu Valley during 1934 Bihar Nepal earthquake and recent 2015 Gorkha earthquake seemingly due to the modification of earthquake ground motion parameters. In this study, site effects resulting from amplification of soft soil in Kathmandu are presented. A large amount of subsoil data was collected and used for defining the appropriate subsoil model for the Kathamandu valley. A comparative study of one-dimensional total-stress equivalent linear and non-linear site response is performed using four strong ground motions for six sites of Kathmandu valley. In general, one-dimensional (1D) site-response analysis involves the excitation of a soil profile using the horizontal component and calculating the response at individual soil layers. In the present study, both equivalent linear and non-linear site response analyses were conducted using the computer program DEEPSOIL. The results show that there is no significant deviation between equivalent linear and non-linear site response models until the maximum strain reaches to 0.06-0.1%. Overall, it is clearly observed from the results that non-linear site response model perform better as compared to equivalent linear model. However, the significant deviation between two models is resulted from other influencing factors such as assumptions made in 1D site response, lack of accurate values of shear wave velocity and nonlinear properties of the soil deposit. The results are also presented in terms of amplification factors which are predicted to be around four times more in case of non-linear analysis as compared to equivalent linear analysis. Hence, the nonlinear behavior of soil prevails the urgent need of study of dynamic characteristics of the soft soil deposit that can specifically represent the site-specific design spectra for the Kathmandu valley for building resilient structures from future damaging earthquakes.

Keywords: deep soil, equivalent linear analysis, non-linear analysis, site response

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Authors: Bouabdellah Abed, Mohamed Bouzit, Lakhdar Bouarbi

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The objective of this study is to investigate numerically the effect of roof shaped on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, Pvol = 96%. A three-dimensional computational fluid dynamics (CFD) model for evaluating air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier–Stokes (RANS) equations and the k-Epsilon EARSM turbulence model as close of the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated against the wind tunnel experiment. Having established this, the wind flow and pollutant dispersion in urban street canyons of six roof shapes are simulated. The numerical simulation agrees reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated, this complexity is increased with presence of tree and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped. The results also indicated that the corners eddies provide additional ventilation and lead to lower traffic pollutant concentrations at the street canyon ends.

Keywords: street canyon, pollutant dispersion, trees, building configuration, numerical simulation, k-Epsilon EARSM

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

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This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

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Authors: C. Villamizar, M. Serrato

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In the pursuit of athletic performance, the role of physical training which is determined by a number of charges or taxes on physiological stress and musculoskeletal systems of the human body generated by the intensity and duration is fundamental. Given the physical demands of these activities both training and competitive must take into account the optimal relationship with a straining process recovery post favoring the process of overcompensation which aims to facilitate the return and rising energy potential and protein synthesis also of different tissues. Allowing muscle function returns to baseline or pre-exercise states. If this recovery process is not performed or is not allowed in a proper way, will result in an increased state of fatigue. Active recovery, is one of the strategies implemented in the sport for a return to pre-exercise physiological states. However, there are some adverse assumptions regarding the negative effects, as is the possibility of increasing the degradation of muscle glycogen and thus delaying the synthesis thereof. For them, it is necessary to investigate what would be the effects generated application made at different times after the effort. The aim of this study was to determine the effects of active recovery post effort made at three different times: immediately, at 12 and 24 hours on biochemical markers creatine kinase in youth soccer player’s categories. A randomized controlled trial with allocation to three groups was performed: A. active recovery immediately after the effort; B. active recovery performed at 12 hours after the effort; C. active recovery made at 24 hours after the effort. This study included 27 subjects belonging to a Colombian soccer team of the second division. Vital signs, weight, height, BMI, the percentage of muscle mass, fat mass percentage, personal medical history, and family were valued. The velocity, explosive force and Creatin Kinase (CK) in blood were tested before and after interventions. SAFT 90 protocol (Soccer Field specific Aerobic Test) was applied to participants for generating fatigue. CK samples were taken one hour before the application of the fatigue test, one hour after the fatigue protocol and 48 of the initial CK sample. Mean age was 18.5 ± 1.1 years old. Improvements in jumping and speed recovery the 3 groups (p < 0.05), but no statistically significant differences between groups was observed after recuperation. In all participants, there was a significant increment of CK when applied SAFT 90 in all the groups (median 103.1-111.1). The CK measurement after 48 hours reflects a recovery in all groups, however the group C, a decline below baseline levels of -55.5 (-96.3 /-20.4) which is a significant find. Other research has shown that CK does not return quickly to their baseline, but our study shows that active recovery favors the clearance of CK and also to perform recovery 24 hours after the effort generates higher clearance of this biomarker.

Keywords: active recuperation, creatine phosphokinase, post training, young soccer players

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Authors: Alexandru-Ion Marinescu

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

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

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Authors: Boda Sreenivas, Lyathakula Ravindranath, Kanugula Srishailam, Byru Venkatram Reddy

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Extensive research into the optimized structure and molecular properties of 3-Flouro-2-methylbenzoicacid(FMB), 3-Chloro-2-methoxybenzoicacid (CMB), and 3-Bromo-2-methylbenzoicacid (BMB) was carried out using FT-IR, FT-Raman and UV-Visible spectra, as well as theoretically using the DFT approach with B3LYPfunctional in conjunction with 6-311++G(d,p) basis set. The optimized structure was determined by evaluating torsional scans about free rotation bonds. Structure parameters, harmonic vibrational frequencies, potential energy distribution(PED), and infrared and Raman intensities were computed. The computational results from the DFT approach, such asFT-IR, FT-Raman, and UV-Visible spectra, were compared with the experimental results and found good agreement. Observed and calculated frequencies agreed with an rms error of 8.42, 6.60, and 6.95 cm-1 for FMB, CMB, and BMB, respectively. Unambiguous vibrational assignments were made for all fundamentals using PED and eigenvectors. The electronic HOMO-LUMO, H-bonding, and strong conjugative interactions across different molecular entities are discussed using experimental and simulated Ultraviolet-Visible spectra. The title molecules' molecular properties such as dipole moment, mean polarizability, and first-order hyperpolarizability, were calculated to study their non-linear optical (NLO) behavior. The chemical reactivity descriptors and mapped electrostatic surface potential (MESP) were also evaluated. Natural bond orbital (NBO) analysis was used to examine the stability of molecules resulting from hyperconjugative interactions and charge delocalization.

Keywords: ftir/raman spectra, DFT, NLO, homo-lumo, NBO, halogenated benzoic acids

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

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

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

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Authors: Tatiana S. Ogneva

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Aluminum and nickel-based intermetallic compounds have attracted the attention of scientific community as promising materials for heat-resistant and wear-resistant coatings in such manufacturing areas as microelectronics, aircraft and rocket building and chemical industries. Magnetron sputtering makes possible to coat materials without formation of liquid phase and improves the mechanical and functional properties of nickel aluminides due to the possibility of nanoscale structure formation. The purpose of the study is the investigation of structure and properties of intermetallic coatings produced by magnetron sputtering technique. The feature of this work is the using of composite targets for sputtering, which were consisted of two semicircular sectors of cp-Ni and cp-Al. Plates of alumina, silicon, titanium and steel alloys were used as substrates. To estimate sputtering conditions on structure of intermetallic coatings, a series of samples were produced and studied in detail using scanning and transition electron microcopy and X-Ray diffraction. Besides, nanohardness and scratching tests were carried out. The varying parameters were the distance from the substrate to the target, the duration and the power of the sputtering. The thickness of the obtained intermetallic coatings varied from 0.05 to 0.5 mm depending on the sputtering conditions. The X-ray diffraction data indicated that the formation of intermetallic compounds occurred after sputtering without additional heat treatment. Sputtering at a distance not closer than 120 mm led to the formation of NiAl phase. Increase in the power of magnetron from 300 to 900 W promoted the increase of heterogeneity of the phase composition and the appearance of intermetallic phases NiAl, Ni₂Al₃, NiAl₃, and Al under the aluminum side, and NiAl, Ni₃Al, and Ni under the nickel side of the target. A similar trend is observed with increasing the distance of sputtering from 100 to 60 mm. The change in the phase composition correlates with the changing of the atomic composition of the coatings. Scanning electron microscopy revealed that the coatings have a nanoscale grain structure. In this case, the substrate material and the distance from the substrate to the magnetron have a significant effect on the structure formation process. The size of nanograins differs from 10 to 83 nm and depends not only on the sputtering modes but also on material of a substrate. Nanostructure of the material influences the level of mechanical properties. The highest level of nanohardness of the coatings deposited during 30 minutes on metallic substrates at a distance of 100 mm reached 12 GPa. It was shown that nanohardness depends on the grain size of the intermetallic compound. Scratching tests of the coatings showed a high level of adhesion of the coating to substrate without any delamination and cracking. The results of the study showed that magnetron sputtering of composite targets consisting of nickel and aluminum semicircles makes it possible to form intermetallic coatings with good mechanical properties directly in the process of sputtering without additional heat treatment.

Keywords: intermetallic coatings, magnetron sputtering, mechanical properties, structure

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Authors: A. Pallavi, N. Vijay Mohan

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A nation can be economically progressive only when the citizens have sufficient capacity to work efficiently to increase the productivity. So, good health must be regarded as a primary need of the community. This helps the growth and development of the body and the mind, which in turn leads to progress and prosperity of the nation. An optimum growth is a necessity for an efficient existence in a biologically adverse and economically competitive world. It is also necessary for the execution of daily routine work. Yoga is a method or a system for the complete development of the personality in a human being. It can be further elaborated as an all-around and complete development of the body, mind, morality, intellect and soul of a being. Sri Aurobindo defines yoga as 'a methodical effort towards self-perfection by the development of the potentialities in the individual.' Aerobic exercise as any activity that uses large muscle groups, can be maintained continuously, and is rhythmic I nature. It is a type of exercise that overloads the heart and lungs and causes them to work harder than at rest. The important idea behind aerobic exercise today, is to get up and get moving. There are more activities that ever to choose from, whether it is a new activity or an old one. Find something you enjoy doing that keeps our heart rate elevated for a continuous time period and get moving to a healthier life. Middle aged selected and served as the subjects for the purpose of this study. The selected subjects were in the age group of 30 to 40 years. By going through the literature and after consulting the experts in yoga and aerobic training, the investigator had chosen the variables which are specifically related to the middle-aged men. The selected physiological variables are pulse rate, diastolic blood pressure, systolic blood pressure; percent body fat and vital capacity. The selected psychological variables are job anxiety, occupational stress. The study was formulated as a random group design consisting of aerobic exercise and yogic exercises groups. The subjects (N=60) were at random divided into three equal groups of twenty middle-aged men each. The groups were assigned the names as follows: 1. Experimental group I- aerobic exercises group, 2. Experimental group II- yogic exercises, 3. Control group. All the groups were subjected to pre-test prior to the experimental treatment. The experimental groups participated in their respective duration of twenty-four weeks, six days in a week throughout the study. The various tests administered were: prior to training (pre-test), after twelfth week (second test) and twenty-fourth weeks (post-test) of the training schedule.

Keywords: pulse rate, diastolic blood pressure, systolic blood pressure; percent body fat and vital capacity, psychological variables, job anxiety, occupational stress, aerobic exercise, yogic exercise

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Authors: Richard L. Summers

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The advanced computational analysis of biological systems is becoming increasingly dependent upon an understanding of the information-theoretic structure of the materials, energy and interactive processes that comprise those systems. The stability and survival of these living systems are fundamentally contingent upon their ability to acquire and process the meaning of information concerning the physical state of its biological continuum (biocontinuum). The drive for adaptive system reconciliation of a divergence from steady-state within this biocontinuum can be described by an information metric-based formulation of the process for actionable knowledge acquisition that incorporates the axiomatic inference of Kullback-Leibler information minimization driven by survival replicator dynamics. If the mathematical expression of this process is the Lagrangian integrand for any change within the biocontinuum then it can also be considered as an action functional for the living system. In the direct method of Lyapunov, such a summarizing mathematical formulation of global system behavior based on the driving forces of energy currents and constraints within the system can serve as a platform for the analysis of stability. As the system evolves in time in response to biocontinuum perturbations, the summarizing function then conveys information about its overall stability. This stability information portends survival and therefore has absolute existential meaning for the living system. The first derivative of the Lyapunov energy information function will have a negative trajectory toward a system's steady state if the driving force is dissipating. By contrast, system instability leading to system dissolution will have a positive trajectory. The direction and magnitude of the vector for the trajectory then serves as a quantifiable signature of the meaning associated with the living system’s stability information, homeostasis and survival potential.

Keywords: meaning, information, Lyapunov, living systems

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Authors: Palash Kumar Mollick, Leire Olazar, Laura Santamaria, Pablo Comendador, Gartzen Lopez, Martin Olazar

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Average calorific value of a mixure of waste plastic is approximately 38 MJ/kg. Present work aims to extract maximum possible energy from a mixure of waste plastic using a DC thermal plasma in a spouted bed reactor. Plasma pyrolysis and steam reforming process has shown a potential to generate hydrogen from plastic with much below of legal limit of producing dioxins and furans as the carcinogenic gases. A spouted bed pyrolysis rector can continuously process plastic beads to produce organic volatiles, which later react with steam in presence of catalyst to results in syngas. lasma being the fourth state of matter, can carry high impact electrons to favour the activation energy of any chemical reactions. Computational Fluid Dynamic (CFD) simulation using COMSOL Multiphysics software has been performed to evaluate performance of a plasma spouted bed reactor in producing contamination free hydrogen as a green energy from waste plastic beads. The simulation results will showcase a design of a plasma spouted bed reactor for converting plastic waste into green hydrogen in a single step process. The high temperature hydrodynamics of spouted bed with plastic beads and the corresponding temperature distribution inside the reaction chamber will be critically examined for it’s near future installation of demonstration plant.

Keywords: green hydrogen, plastic waste, synthetic gas, pyrolysis, steam reforming, spouted bed, reactor design, plasma, dc palsma, cfd simulation

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Authors: Rosa S. Wong, Keith T. S. Tung, Frederick K. Ho, Winnie W. Y. Tso, King-wa Fu, Nirmala Rao, Patrick Ip

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As technology advances, exposures in early childhood are no longer confined to stimulations in the surrounding physical environments. Children nowadays are also subject to influences from the digital world. In particular, early access to game consoles can cause risks to child development, especially when the game is not developmentally appropriate for young children. Overstimulation is possible and could impair brain development. On the other hand, recreational parent-child activities, including outdoor activities and visits to museums, require child interaction with parents, which is beneficial for developing adaptive emotion regulation and social skills. Given the differences between these two types of exposures, this study investigated and compared the independent effects of early exposure to a game console and early play-based parent-child activities on children’s long-term psychosocial outcomes. This study used data from a subset of children (n=304, 142 male and 162 female) in the longitudinal cohort study, which studied the long-term impact of family socioeconomic status on child development. In 2012/13, we recruited a group of children at Kindergarten 3 (K3) randomly from Hong Kong local kindergartens and collected data regarding their duration of exposure to game console and recreational parent-child activities at that time. In 2018/19, we re-surveyed the parents of these children who were matriculated as Form 1 (F1) students (ages ranging from 11 to 13 years) in secondary schools and asked the parents to rate their children’s psychosocial problems in F1. Linear regressions were conducted to examine the associations between early exposures and adolescent psychosocial problems with and without adjustment for child gender and K3 family socioeconomic status. On average, K3 children spent about 42 minutes on a game console every day and had 2-3 recreational activities with their parents every week. Univariate analyses showed that more time spent on game consoles at K3 was associated with more psychosocial difficulties in F1 particularly more externalizing problems. The effect of early exposure to game console on externalizing behavior remained significant (B=0.59, 95%CI: 0.15 to 1.03, p=0.009) after adjusting for recreational parent-child activities and child gender. For recreational parent-child activities at K3, its effect on overall psychosocial difficulties became insignificant after adjusting for early exposure to game consoles and child gender. However, it was found to have significant protective effect on externalizing problems (B=-0.65, 95%CI: -1.23 to -0.07, p=0.028) even after adjusting for the confounders. Early exposure to game consoles has negative impact on children’s psychosocial health, whereas play-based parent-child activities can foster positive psychosocial outcomes. More efforts should be directed to propagate the risks and benefits of these activities and urge the parents and caregivers to replace child-alone screen time with parent-child play time in daily routine.

Keywords: early childhood, electronic device, parenting, psychosocial wellbeing

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Authors: Hui-Chieh Li

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Circular economy promotes greater resource productivity and avoids pollution through greater recycling and re-use which bring benefits for both the environment and the economy. The concept is contrast to a linear economy which is ‘take, make, dispose’ model of production. A well-design reverse logistics service strategy could enhance the willingness of recycling of the users and reduce the related logistics cost as well as carbon emissions. Moreover, the recycle brings the manufacturers most advantages as it targets components for closed-loop reuse, essentially converting materials and components from worn-out product into inputs for new ones at right time and right place. This study considers demand-supply interaction, time-dependent recycle demand, time-dependent surplus value of recycled product and constructs models on recycle service strategy for the recyclable waste collector. A crucial factor in optimizing a recycle service strategy is consumer demand. The study considers the relationships between consumer demand towards recycle and product characteristics, surplus value and user behavior. The study proposes a recycle service strategy which differs significantly from the conventional and typical uniform service strategy. Periods with considerable demand and large surplus product value suggest frequent and short service cycle. The study explores how to determine a recycle service strategy for recyclable waste collector in terms of service cycle frequency and duration and vehicle type for all service cycles by considering surplus value of recycled product, time-dependent demand, transportation economies and demand-supply interaction. The recyclable waste collector is responsible for the collection of waste product for the manufacturer. The study also examines the impacts of utilization rate on the cost and profit in the context of different sizes of vehicles. The model applies mathematical programming methods and attempts to maximize the total profit of the distributor during the study period. This study applies the binary logit model, analytical model and mathematical programming methods to the problem. The model specifically explores how to determine a recycle service strategy for the recycler by considering product surplus value, time-dependent recycle demand, transportation economies and demand-supply interaction. The model applies mathematical programming methods and attempts to minimize the total logistics cost of the recycler and maximize the recycle benefits of the manufacturer during the study period. The study relaxes the constant demand assumption and examines how service strategy affects consumer demand towards waste recycling. Results of the study not only help understanding how the user demand for recycle service and product surplus value affects the logistics cost and manufacturer’s benefits, but also provide guidance such as award bonus and carbon emission regulations for the government.

Keywords: circular economy, consumer demand, product surplus value, recycle service strategy

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Authors: Oluibukun G. Ajayi, Joseph O. Odumosu, Oladimeji T. Babafemi, Azeez Z. Opeyemi, Asaleye O. Samuel

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The need for the complete automation of every procedure of surveying and most especially, its engineering applications cannot be overemphasized due to the many demerits of the conventional manual or analogue approach. This paper presents the summarized details of the development of a Route Information Management (RIM) software. The software, codenamed ‘AutoROUTE’, was encoded using Microsoft visual studio-visual basic package, and it offers complete automation of the computational procedures and plan production involved in route surveying. It was experimented using a route survey data (longitudinal profile and cross sections) of a 2.7 km road which stretches from Dama to Lunko village in Minna, Niger State, acquired with the aid of a Hi-Target DGPS receiver. The developed software (AutoROUTE) is capable of computing the various simple curve parameters, horizontal curve, and vertical curve, and it can also plot road alignment, longitudinal profile, and cross-section with a capability to store this on the SQL incorporated into the Microsoft visual basic software. The plotted plans with AutoROUTE were compared with the plans produced with the conventional AutoCAD Civil 3D software, and AutoROUTE proved to be more user-friendly and accurate because it plots in three decimal places whereas AutoCAD plots in two decimal places. Also, it was discovered that AutoROUTE software is faster in plotting and the stages involved is less cumbersome compared to AutoCAD Civil 3D software.

Keywords: automated systems, cross sections, curves, engineering construction, longitudinal profile, route surveying

Procedia PDF Downloads 141

Authors: Mohammad Fereidoonnezhad, Seán Leen, Stephen Nash, Patrick McGarry

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From the perspective of research innovation, the tidal energy industry is still in its early stages. While a very small number of turbines have progressed to utility-scale deployment, blade breakage is commonly reported due to the enormous hydrodynamic loading applied to devices. The aim of this study is the development of computer simulation technologies for the design of next-generation fibre-reinforced composite tidal turbines. This will require significant technical advances in the areas of tidal turbine testing and multi-scale computational modelling. The complex turbine blade profiles are designed to incorporate non-linear distributions of airfoil sections to optimize power output and self-starting capability while reducing power fluctuations. A number of candidate blade geometries are investigated, ranging from spiral geometries to parabolic geometries, with blades arranged in both cylindrical and spherical configurations on a vertical axis turbine. A combined blade element theory (BET-start-up model) is developed in MATLAB to perform computationally efficient parametric design optimisation for a range of turbine blade geometries. Finite element models are developed to identify optimal fibre-reinforced composite designs to increase blade strength and fatigue life. Advanced fluid-structure-interaction models are also carried out to compute blade deflections following design optimisation.

Keywords: tidal turbine, composite materials, fluid-structure-interaction, start-up capability

Procedia PDF Downloads 117

Authors: Javier Varillas, Jorge Alcalá

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We investigate dislocation avalanche phenomena in face-centered cubic (FCC) and body-centered cubic (BCC) crystals using massive, large-scale molecular dynamics (MD) simulations. The analysis is focused on the intermittent development of dense dislocation arrangements subjected to uniaxial tensile straining under displacement control. We employ a novel computational scheme that allows us to inject an entangled dislocation structure in periodic MD domains. We assess the emission of plastic bursts (or dislocation avalanches) in terms of the sharp stress drops detected in the stress-strain curve. The plastic activity corresponds to the sporadic operation of specific dislocation glide processes exhibiting quiescent periods between successive avalanche events. We find that the plastic intermittences in our simulations do not overlap in time under sufficiently low strain rates as dissipation operates faster than driving, where the dense dislocation networks evolve through the emission of dislocation avalanche events whose carried slip adheres to self-organized power-law distributions. These findings enable the extension of the slip distributions obtained from strict displacement-controlled micropillar compression experiments towards smaller values of slip size. Our results furnish further understanding upon the development of entangled dislocation networks in metal plasticity, including specific mechanisms of dislocation propagation and annihilation, along with the evolution of specific dislocation populations through dislocation density analyses.

Keywords: dislocations, intermittent plasticity, molecular dynamics, slip distributions

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Authors: Maher Aburrous, Adel Khelifi, Manar Abu Talib

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Transactions performed by financial institutions on daily basis require XML encryption on large scale. Encrypting large volume of message fully will result both performance and resource issues. In this paper a novel approach is presented for securing financial XML transactions using classification data mining (DM) algorithms. Our strategy defines the complete process of classifying XML transactions by using set of classification algorithms, classified XML documents processed at later stage using element-wise encryption. Classification algorithms were used to identify the XML transaction rules and factors in order to classify the message content fetching important elements within. We have implemented four classification algorithms to fetch the importance level value within each XML document. Classified content is processed using element-wise encryption for selected parts with "High", "Medium" or “Low” importance level values. Element-wise encryption is performed using AES symmetric encryption algorithm and proposed modified algorithm for AES to overcome the problem of computational overhead, in which substitute byte, shift row will remain as in the original AES while mix column operation is replaced by 128 permutation operation followed by add round key operation. An implementation has been conducted using data set fetched from e-banking service to present system functionality and efficiency. Results from our implementation showed a clear improvement in processing time encrypting XML documents.

Keywords: XML transaction, encryption, Advanced Encryption Standard (AES), XML classification, e-banking security, fuzzy classification, cryptography, intelligent encryption

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Authors: Huang Wei-Yi

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Objective: This article explores the intensive care nursing experience of a terminal lung cancer patient who received palliative care after tracheal intubation. The patient was nearing death, and the family experienced sadness and grief as they faced the patient’s deteriorating condition and impending death. Methods: The patient was diagnosed with lung cancer in 2018 and received chemotherapy and radiation therapy with regular outpatient follow-ups. Due to brain metastasis and recent poor pain control and treatment outcomes, the patient was admitted to the intensive care unit (ICU), where the tracheal tube was removed, and palliative care was initiated. During the care period, a holistic assessment was conducted, addressing the physical, psychological, social, and spiritual aspects of care. Medical records were reviewed, interviews and family meetings were held, and a comprehensive assessment was carried out by the critical care team in collaboration with the palliative care team. The primary nursing issues identified included pain, ineffective breathing patterns, fear of death, and altered tissue perfusion. Results: Throughout the care process, the palliative care nurse, along with the family, utilized listening, caring, companionship, pain management, essential oil massage, distraction, and comfortable positioning to alleviate the patient’s pain and breathing difficulties. The use of Morphine 6mg in 0.9% N/S 50ml IV drip q6h reduced the FLACC pain score from 6 to 3. The patient’s respiratory rate improved from 28 breaths/min to 18-22 breaths/min, and sleep duration increased from 4 to 7 uninterrupted hours. The holistic palliative care approach, coupled with the involvement of the palliative care team, facilitated expressions of gratitude, apologies, and love between the patient and family. Visiting hours were extended, and with the nurse’s assistance, these moments were recorded and shared with the patient’s consent, providing cherished memories for the family. The patient’s end-of-life experience was thus improved, and the family was able to find peace. This case also served to promote the concept of palliative care, ensuring that more patients and families receive high-quality nursing care. Conclusion: When caring for terminal patients, collaboration with the palliative care team, including social workers, clergy, psychologists, and nutritionists, is essential. Involving the family in decision-making and providing opportunities for closeness and expressions of gratitude improve personalized care and enhance the patient's quality of life. Upon transferring to the ward, the patient’s hemodynamic stability was maintained, including SBP 110-130 mmHg, respiratory rate 20-22 breaths/min, and pain score <3. The patient was later discharged and transitioned to home hospice care for ongoing support.

Keywords: intensive care, lung cancer, palliative care, ICU

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Authors: Ang Chia Hong, Julian Khoo Xubin, Burra Venkata Durga Kumar

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Distributed systems offer many benefits to the healthcare industry. From big data analysis to business intelligence, the increased computational power and efficiency from distributed systems serve as an invaluable resource in the healthcare sector to utilize. However, as the usage of these distributed systems increases, many issues arise. The main focus of this paper will be on security issues. Many security issues stem from distributed systems in the healthcare industry, particularly information security. The data of people is especially sensitive in the healthcare industry. If important information gets leaked (Eg. IC, credit card number, address, etc.), a person’s identity, financial status, and safety might get compromised. This results in the responsible organization losing a lot of money in compensating these people and even more resources expended trying to fix the fault. Therefore, a framework for a blockchain-based healthcare data management system for healthcare was proposed. In this framework, the usage of a blockchain network is explored to store the encryption key of the patient’s data. As for the actual data, it is encrypted and its encrypted data, called ciphertext, is stored in a cloud storage platform. Furthermore, there are some issues that have to be emphasized and tackled for future improvements, such as a multi-user scheme that could be proposed, authentication issues that have to be tackled or migrating the backend processes into the blockchain network. Due to the nature of blockchain technology, the data will be tamper-proof, and its read-only function can only be accessed by authorized users such as doctors and nurses. This guarantees the confidentiality and immutability of the patient’s data.

Keywords: distributed, healthcare, efficiency, security, blockchain, confidentiality and immutability

Procedia PDF Downloads 176

Authors: Kaihong Yu, Tetsui Yamashita, Shigeaki Shingyochi, Kazuo Matsumoto, Makoto Ohta

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During cardiac ablation, high power delivery for deeper lesion formation is limited by electrode-tissue interface overheating which can cause serious complications such as thrombus. To prevent this overheating, temperature control and open irrigation are often used. In temperature control, radiofrequency generator is adjusted to deliver the maximum output power, which maintains the electrode temperature at a target temperature (commonly 55°C or 60°C). Then the electrode-tissue interface temperature is also limited. The electrode temperature is a result of heating from the contacted tissue and cooling from the surrounding blood. Because the cooling from blood is decreased under conditions of low blood flow, the generator needs to decrease the output power. Thus, temperature control cannot deliver high power under conditions of low blood flow. In open irrigation, saline in room temperature is flushed through the holes arranged in the electrode. The electrode-tissue interface is cooled by the sufficient environmental cooling. And high power delivery can also be done under conditions of low blood flow. However, a large amount of saline infusions (approximately 1500 ml) during irrigation can cause other serious complication. When open irrigation cannot be used under conditions of low blood flow, a new overheating prevention may be required. The authors have proposed a new electrode cooling method by making the catheter vibrating. The previous work has introduced that the vibration can make a cooling effect on electrode, which may result form that the vibration could increase the flow velocity around the catheter. The previous work has also proved that increasing vibration frequency can increase the cooling by vibration. However, the effect of the vibration amplitude is still unknown. Thus, the present study investigated the effect of vibration amplitude on tissue temperature and lesion size. An agar phantom model was used as a tissue-equivalent material for measuring tissue temperature. Thermocouples were inserted into the agar to measure the internal temperature. Porcine myocardium was used for lesion size measurement. A normal ablation catheter was set perpendicular to the tissue (agar or porcine myocardium) with 10 gf contact force in 37°C saline without flow. Vibration amplitude of ± 0.5, ± 0.75, and ± 1.0 mm with a constant frequency (31 Hz or 63) was used. A temperature control protocol (45°C for agar phantom, 60°C for porcine myocardium) was used for the radiofrequency applications. The larger amplitude shows the larger lesion sizes. And the higher tissue temperatures in agar phantom are also shown with the higher amplitude. With a same frequency, the larger amplitude has the higher vibrating speed. And the higher vibrating speed will increase the flow velocity around the electrode more, which leads to a larger electrode temperature decrease. To maintain the electrode at the target temperature, ablator has to increase the output power. With the higher output power in the same duration, the released energy also increases. Consequently, the tissue temperature will be increased and lead to larger lesion sizes.

Keywords: cardiac ablation, electrode cooling, lesion size, tissue temperature

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Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

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Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

Procedia PDF Downloads 100

Authors: Vittorio Linfante

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Utopìa is a term that, since its first appearance in 1516, in Tommaso Moro’s work, has taken on different meanings and forms in various fields: social studies, politics, art, creativity, and design. The utopias, although of short duration and in their apparent impossibility, have been able to give a shape to the future, laying the foundations for our present and the future of the next generations. The Twentieth century was the historical period crossed by many changes, and it saw the most significant number of utopias not only social, political, and scientific but also artistic, architectural, in design, communication, and, last but not least, in fashion. Over the years, fashion has been able to interpret various utopistic impulses giving form to the most futuristic visions. From the Manifesto del Vestito by Giacomo Balla, through the functional experiments that led to the Tuta by Thayath and the Varst by Aleksandr Rodčenko and Varvara Stepanova, through the Space Age visions of Rudi Gernreich, Paco Rabanne and Pierre Cardin, and the Archizoom’s political actions and their fashion project Vestirsi è facile. Experiments that have continued to the present days through the (sometimes) excessive visions of Hussein Chalayan, Alexander McQueen, and Gareth Pugh or those that are more anchored to the market (but no fewer innovative and visionaries) by Prada, Chanel, and Raf Simmons. If, as Bauman states, it is true that we have entered in a phase of Retrotopia characterized by the inability to think about new forms of the future; it is necessary, more than ever, to redefine the role of history, of its narration and its mise en scène, within the contemporary creative process. A process that increasingly requires an in-depth knowledge of the past for the definition of a renewed discourse about design processes. A discourse in which words like archive, exhibition, curating, revival, vintage, and costume take on new meanings. The paper aims to investigate–through case studies, research, and professional projects–the renewed role of curating and preserving fashion artefacts. A renewed role that–in an era of Retrotopia–museums, exhibitions, and archives can (and must) assume, to contribute to the definition of new design paradigms, capable of overcoming the traditional categories of revival or costume in favour of a more contemporary “mash-up” approach. Mash-up in which past and present, craftsmanship and new technologies, revival and experimentation merge seamlessly. In this perspective, dresses (as well as fashion accessories) should be considered not only as finished products but as artefacts capable of talking about the past and of producing unpublished new stories at the same time. Archives, exhibitions (academic and not), and museums thus become powerful sources of inspiration for fashion: places and projects capable of generating innovation, becoming active protagonists of the contemporary fashion design processes.

Keywords: heritage, history, costume and fashion interface, performance, language, design research

Procedia PDF Downloads 113

Authors: Lian Kösters, Wendy Smits, Raymond Montizaan

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The number of solo self-employed in the Netherlands has been increasing for years. The relative increase is among the largest in the EU. To explain this increase, most studies have focused on the supply side, workers who offer themselves as solo self-employed. The number of studies that focus on the demand side, the employer who hires the solo self-employed, is still scarce. Studies into employer behaviour conducted until now show that employers mainly choose self-employed workers when they have a temporary need for specialist knowledge, but also during projects or production peaks. These studies do not provide insight into the employers’ considerations for different contract types. In this study, interviews with employers were conducted, and available literature was consulted to provide an overview of the several factors employers use to compare different contract types. That input was used to set up a vignette study. This was carried out at the end of 2021 among almost 1000 business owners, HR managers, and business leaders of Dutch companies. Each respondent was given two sets of five fictitious candidates for two possible positions in their organization. They were asked to rank these candidates. The positions varied with regard to the type of tasks (core tasks or support tasks) and the time it took to train new people for the position. The respondents were asked additional questions about the positions, such as the required level of education, the duration, and the degree of predictability of tasks. The fictitious candidates varied, among other things, in the type of contract on which they would come to work for the organization. The results were analyzed using a rank-ordered logit analysis. This vignette setup makes it possible to see which factors are most important for employers when choosing to hire a solo self-employed person compared to other contracts. The results show that there are no indications that employers would want to hire solo self-employed workers en masse. They prefer regular employee contracts. The probability of being chosen with a solo self-employed contract over someone who comes to work as a temporary employee is 32 percent. This probability is even lower than for on-call and temporary agency workers. For a permanent contract, this probability is 46 percent. The results provide indications that employers consider knowledge and skills more important than the solo self-employed contract and that this can compensate. A solo self-employed candidate with 10 years of work experience has a 63 percent probability of being found attractive by an employer compared to a temporary employee without work experience. This suggests that employers are willing to give someone a less attractive contract for the employer if the worker so wishes. The results also show that the probability that a solo self-employed person is preferred over a candidate with a temporary employee contract is somewhat higher in business economics, administrative and technical professions. No significant results were found for factors where it was expected that solo self-employed workers are preferred more often, such as for unpredictable or temporary work.

Keywords: employer behaviour, rank-ordered logit analysis, solo self-employment, temporary contract, vignette study

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Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

Procedia PDF Downloads 128

Authors: Susan Evans, Janna Gordon-Elliott, Katarzyna Wyka, Virginia Mutch

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During the rise of the COVID-19 pandemic, healthcare workers needed an intervention that could address their profound acute stress. Mindfulness-based stress reduction (MBSR) is a program that has long established effectiveness for mental and physical health outcomes. In recent years, MBSR has been modified such that the duration of both class time and number of sessions has been abbreviated, and its delivery has been adapted for online dissemination, thus increasing the likelihood that individuals who could most benefit from the program would do so. We sought to investigate whether a brief, online version of MBSR could be feasible and acceptable for health care workers (HCW) in acute stress in response to the COVID-19 pandemic. Participants were recruited via an email sent to all hospital employees, which spans residents, physicians, nurses, housekeeping, lab technicians, administrators, and others. Participating HCW were asked about their previous experience with mindfulness and asked to commit to a minimum of 3 sessions. They were then provided with four weekly 1-hour sessions online that included the major mindfulness exercises taught during traditional MBSR programs (i.e., body scan, sitting meditation, mindful eating, and yoga). Participants were provided with supporting slides, videos, demonstrations and asked to track their practice. Hospital staff enrolled in the program; by the end of the first day of recruitment, 40 had applied; by the start date, about 100 were enrolled, and n attended a minimum of 3 sessions, supporting feasibility. Hospital staff also participated and practiced the mindfulness exercises (n=42), thus supporting acceptability. Participants reported that the program was logical, successful, and worth recommending both before starting the program and after completing it (M= 22.02 and M=21.76, respectively, possible range 0-27). There was a slight decline in the belief in improvement in health and well-being due to the program (ES=.37, p=.021). Secondary hypotheses regarding participants’ self-reported stress and levels of mindfulness were also supported, such that participants reported improvements in perceived stress (ES=.45, p=.006), compassion satisfaction, burnout, and secondary traumatic stress (ES=.41, ES=.31, ES=.35, respectively, p<.05). Participants reported significant improvements in the describing facet of mindfulness (ES=.49, p=.004), while all other facets (observing, acting with awareness, nonjudging of inner experience, nonreactivity to inner experience) remained unchanged pre- to post-program. Results from this study suggest that an abridged, online version of MBSR is feasible and accessible to health care workers in acute stress and provides benefits expected from traditional MBSR programs. The lack of a randomized control group limits generalizability. We intend to provide a structure, framework, and lessons learned to hospital administrators and clinical staff seeking to support their employees in acute stress.

Keywords: acute stress, health care workers, mindfulness, online interventions

Procedia PDF Downloads 121

Authors: A. Saravanan, B. R. Huang, C. J. Yeh, K. C. Leou, I. N. Lin

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A new class of ultra-nano diamond-graphite nano-hybrid (DGH) composite materials containing nano-sized diamond needles was developed at low temperature process. Such kind of diamond- graphite nano-hybrid composite nanowires exhibit high electrical conductivity and excellent electron field emission (EFE) properties. Few earlier reports mention that addition of N2 gas to the growth plasma requires high growth temperature (800°C) to trigger the dopants to generate the conductivity in the films. High growth temperature is not familiar with the Si-based device fabrications. We have used a novel process such as bias-enhanced-grown (beg) MPECVD process to grow diamond films at low substrate temperature (450°C). We observed that the beg-N/UNCD films thus obtained possess high conductivity of σ=987 S/cm, ever reported for diamond films with excellent Electron field emission (EFE) properties. TEM investigation indicated that these films contain needle-like diamond grains about 5 nm in diameter and hundreds of nanometers in length. Each of the grains was encased in graphitic layers about tens of nano-meters in thickness. These materials properties suitable for more specific applications, such as high conductivity for electron field emitters, high robustness for microplasma cathodes and high electrochemical activity for electro-chemical sensing. Subsequently, other hand, the highly conducting DGH films were coated on vertically aligned ZnO nanorods, there is no prior nucleation or seeding process needed due to the use of BEG method. Such a composite structure provides significant enhancement in the field emission characteristics of the cold cathode was observed with ultralow turn on voltage 1.78 V/μm with high EFE current density of 3.68 mA/ cm2 (at 4.06V/μm) due to decoration of DGH material on ZnO nanorods. The DGH/ZNRs based device get stable emission for longer duration of 562min than bare ZNRs (104min) without any current degradation because the diamond coating protects the ZNRs from ion bombardment when they are used as the cathode for microplasma devices. The potential application of these materials is demonstrated by the plasma illumination measurements that ignited the plasma at the minimum voltage by 290 V. The photoresponse (Iphoto/Idark) behavior of the DGH/ZNRs based photodetectors exhibits a much higher photoresponse (1202) than bare ZNRs (229). During the process the electron transport is easy from ZNRs to DGH through graphitic layers, the EFE properties of these materials comparable to other primarily used field emitters like carbon nanotubes, graphene. The DGH/ZNRs composite also providing a possibility of their use in flat panel, microplasma and vacuum microelectronic devices.

Keywords: bias-enhanced nucleation and growth, ZnO nanorods, electrical conductivity, electron field emission, photo-detectors

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Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

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The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

Procedia PDF Downloads 326