Search results for: optical sensors

Authors: Xiaoyong He

Abstract:

The manipulation of THz waves is still a challenging task due to lack of natural materials interacted with it strongly. Designed by tailoring the characters of unit cells (meta-molecules), the advance of metamaterials (MMs) may solve this problem. However, because of Ohmic and radiation losses, the performance of MMs devices is subjected to the dissipation and low quality factor (Q-factor). This dilemma may be circumvented by Fano resonance, which arises from the destructive interference between a bright continuum mode and dark discrete mode (or a narrow resonance). Different from symmetric Lorentz spectral curve, Fano resonance indicates a distinct asymmetric line-shape, ultrahigh quality factor, steep variations in spectrum curves. Fano resonance is usually realized through symmetry breaking. However, if concentric double rings (DR) are placed closely to each other, the near-field coupling between them gives rise to two hybridized modes (bright and narrowband dark modes) because of the local asymmetry, resulting into the characteristic Fano line shape. Furthermore, from the practical viewpoint, it is highly desirable requirement that to achieve the modulation of Fano spectral curves conveniently, which is an important and interesting research topics. For current Fano systems, the tunable spectral curves can be realized by adjusting the geometrical structural parameters or magnetic fields biased the ferrite-based structure. But due to limited dispersion properties of active materials, it is still a tough work to tailor Fano resonance conveniently with the fixed structural parameters. With the favorable properties of extreme confinement and high tunability, graphene is a strong candidate to achieve this goal. The DR-structure possesses the excitation of so-called “trapped modes,” with the merits of simple structure and high quality of resonances in thin structures. By depositing graphene circular DR on the SiO2/Si/ polymer substrate, the tunable Fano resonance has been theoretically investigated in the terahertz regime, including the effects of graphene Fermi level, structural parameters and operation frequency. The results manifest that the obvious Fano peak can be efficiently modulated because of the strong coupling between incident waves and graphene ribbons. As Fermi level increases, the peak amplitude of Fano curve increases, and the resonant peak position shifts to high frequency. The amplitude modulation depth of Fano curves is about 30% if Fermi level changes in the scope of 0.1-1.0 eV. The optimum gap distance between DR is about 8-12 μm, where the value of figure of merit shows a peak. As the graphene ribbon width increases, the Fano spectral curves become broad, and the resonant peak denotes blue shift. The results are very helpful to develop novel graphene plasmonic devices, e.g. sensors and modulators.

Keywords: graphene, metamaterials, terahertz, tunable

Procedia PDF Downloads 327

Authors: Mitali Saha, Soma Das

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The fabrication of nanoscale materials for use in chemical sensing, biosensing and biological analyses has proven a promising avenue in the last few years. Cholesterol has aroused considerable interest in recent years on account of its being an important parameter in clinical diagnosis. There is a strong positive correlation between high serum cholesterol level and arteriosclerosis, hypertension, and myocardial infarction. Enzyme-based electrochemical biosensors have shown high selectivity and excellent sensitivity, but the enzyme is easily denatured during its immobilization procedure and its activity is also affected by temperature, pH, and toxic chemicals. Besides, the reproducibility of enzyme-based sensors is not very good which further restrict the application of cholesterol biosensor. It has been demonstrated that carbon nanotubes could promote electron transfer with various redox active proteins, ranging from cytochrome c to glucose oxidase with a deeply embedded redox center. In continuation of our earlier work on the synthesis and applications of carbon and metal based nanoparticles, we have reported here the synthesis of carbon nanotubes (CCNT) by burning coconut oil under insufficient flow of air using an oil lamp. The soot was collected from the top portion of the flame, where the temperature was around 6500C which was purified, functionalized and then characterized by SEM, p-XRD and Raman spectroscopy. The SEM micrographs showed the formation of tubular structure of CCNT having diameter below 100 nm. The XRD pattern indicated the presence of two predominant peaks at 25.20 and 43.80, which corresponded to (002) and (100) planes of CCNT respectively. The Raman spectrum (514 nm excitation) showed the presence of 1600 cm-1 (G-band) related to the vibration of sp2-bonded carbon and at 1350 cm-1 (D-band) responsible for the vibrations of sp3-bonded carbon. A nonenzymatic cholesterol biosensor was then fabricated on an insulating Teflon material containing three silver wires at the surface, covered by CCNT, obtained from coconut oil. Here, CCNTs worked as working as well as counter electrodes whereas reference electrode and electric contacts were made of silver. The dimensions of the electrode was 3.5 cm×1.0 cm×0.5 cm (length× width × height) and it is ideal for working with 50 µL volume like the standard screen printed electrodes. The voltammetric behavior of cholesterol at CCNT electrode was investigated by cyclic voltammeter and differential pulse voltammeter using 0.001 M H2SO4 as electrolyte. The influence of the experimental parameters on the peak currents of cholesterol like pH, accumulation time, and scan rates were optimized. Under optimum conditions, the peak current was found to be linear in the cholesterol concentration range from 1 µM to 50 µM with a sensitivity of ~15.31 μAμM−1cm−2 with lower detection limit of 0.017 µM and response time of about 6s. The long-term storage stability of the sensor was tested for 30 days and the current response was found to be ~85% of its initial response after 30 days.

Keywords: coconut oil, CCNT, cholesterol, biosensor

Procedia PDF Downloads 266

Authors: Vadim Allheily, Rudiger Schmitt, Lionel Merlat, Gildas L'Hostis

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Inflight devices are nowadays major actors in both military and civilian landscapes. Among others, missiles, mortars, rockets or even drones this last decade are increasingly sophisticated, and it is today of prior manner to develop always more efficient defensive systems from all these potential threats. In this frame, recent High Energy Laser weapon prototypes (HEL) have demonstrated some extremely good operational abilities to shot down within seconds flying targets several kilometers off. Whereas test outcomes are promising from both experimental and cost-related perspectives, the deterioration process still needs to be explored to be able to closely predict the effects of a high-energy laser irradiation on typical structures, heading finally to an effective design of laser sources and protective countermeasures. Laser matter interaction researches have a long history of more than 40 years at the French-German Research Institute (ISL). Those studies were tied with laser sources development in the mid-60s, mainly for specific metrology of fast phenomena. Nowadays, laser matter interaction can be viewed as the terminal ballistics of conventional weapons, with the unique capability of laser beams to carry energy at light velocity over large ranges. In the last years, a strong focus was made at ISL on the interaction process of laser radiation with metal targets such as artillery shells. Due to the absorbed laser radiation and the resulting heating process, an encased explosive charge can be initiated resulting in deflagration or even detonation of the projectile in flight. Drones and Unmanned Air Vehicles (UAVs) are of outmost interests in modern warfare. Those aerial systems are usually made up of polymer-based composite materials, whose complexity involves new scientific challenges. Aside this main laser-matter interaction activity, a lot of experimental and numerical knowledge has been gathered at ISL within domains like spectrometry, thermodynamics or mechanics. Techniques and devices were developed to study separately each aspect concerned by this topic; optical characterization, thermal investigations, chemical reactions analysis or mechanical examinations are beyond carried out to neatly estimate essential key values. Results from these diverse tasks are then incorporated into analytic or FE numerical models that were elaborated, for example, to predict thermal repercussion on explosive charges or mechanical failures of structures. These simulations highlight the influence of each phenomenon during the laser irradiation and forecast experimental observations with good accuracy.

Keywords: composite materials, countermeasure, experimental work, high-energy laser, laser-matter interaction, modeling

Procedia PDF Downloads 239

Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Haytam Kasem

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The problem of quick and easy reversible attachment has become of great importance in different fields of technology. For the reason, during the last decade, a new emerging field of adhesion science has been developed. Essentially inspired by some animals and insects, which during their natural evolution have developed fantastic biological attachment systems allowing them to adhere and run on walls and ceilings of uneven surfaces. Potential applications of engineering bio-inspired solutions include climbing robots, handling systems for wafers in nanofabrication facilities, and mobile sensor platforms, to name a few. However, despite the efforts provided to apply bio-inspired patterned adhesive-surfaces to the biomedical field, they are still in the early stages compared with their conventional uses in other industries mentioned above. In fact, there are some critical issues that still need to be addressed for the wide usage of the bio-inspired patterned surfaces as advanced biomedical platforms. For example, surface durability and long-term stability of surfaces with high adhesive capacity should be improved, but also the friction and adhesion capacities of these bio-inspired microstructures when contacting rough surfaces. One of the well-known prototypes for bio-inspired attachment systems is biomimetic wall-shaped hierarchical microstructure for gecko-like attachments. Although physical background of these attachment systems is widely understood, the influence of counter-face roughness and its relationship with the friction force generated when sliding against wall-shaped hierarchical microstructure have yet to be fully analyzed and understood. To elucidate the effect of the counter-face roughness on the friction of biomimetic wall-shaped hierarchical microstructure we have replicated the isotropic topography of 12 different surfaces using replicas made of the same epoxy material. The different counter-faces were fully characterized under 3D optical profilometer to measure roughness parameters. The friction forces generated by spatula-shaped microstructure in contact with the tested counter-faces were measured on a home-made tribometer and compared with the friction forces generated by the spatulae in contact with a smooth reference. It was found that classical roughness parameters, such as average roughness Ra and others, could not be utilized to explain topography-related variation in friction force. This has led us to the development of an integrated roughness parameter obtained by combining different parameters which are the mean asperity radius of curvature (R), the asperity density (η), the deviation of asperities high (σ) and the mean asperities angle (SDQ). This new integrated parameter is capable of explaining the variation of results of friction measurements. Based on the experimental results, we developed and validated an analytical model to predict the variation of the friction force as a function of roughness parameters of the counter-face and the applied normal load, as well.

Keywords: friction, bio-mimetic micro-structure, counter-face roughness, analytical model

Procedia PDF Downloads 224

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Totsaporn Suwannaruang, Kitirote Wantala

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The purposes of this research were to synthesize titanium dioxide photocatalyst doped with nitrogen (N-doped TiO₂) by hydrothermal method and to test the photocatalytic degradation of paraquat under UV and visible light illumination. The effect of calcination treatment temperature on their physical and chemical properties and photocatalytic efficiencies were also investigated. The characterizations of calcined N-doped TiO₂ photocatalysts such as specific surface area, textural properties, bandgap energy, surface morphology, crystallinity, phase structure, elements and state of charges were investigated by Brunauer, Emmett, Teller (BET) and Barrett, Joyner, Halenda (BJH) equations, UV-Visible diffuse reflectance spectroscopy (UV-Vis-DRS) by using the Kubelka-Munk theory, Wide-angle X-ray scattering (WAXS), Focussed ion beam scanning electron microscopy (FIB-SEM), X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS), respectively. The results showed that the effect of calcination temperature was significant on surface morphology, crystallinity, specific surface area, pore size diameter, bandgap energy and nitrogen content level, but insignificant on phase structure and oxidation state of titanium (Ti) atom. The N-doped TiO₂ samples illustrated only anatase crystalline phase due to nitrogen dopant in TiO₂ restrained the phase transformation from anatase to rutile. The samples presented the nanorice-like morphology. The expansion on the particle was found at 650 and 700°C of calcination temperature, resulting in increased pore size diameter. The bandgap energy was determined by Kubelka-Munk theory to be in the range 3.07-3.18 eV, which appeared slightly lower than anatase standard (3.20 eV), resulting in the nitrogen dopant could modify the optical absorption edge of TiO₂ from UV to visible light region. The nitrogen content was observed at 100, 300 and 400°C only. Also, the nitrogen element disappeared at 500°C onwards. The nitrogen (N) atom can be incorporated in TiO₂ structure with the interstitial site. The uncalcined (100°C) sample displayed the highest percent paraquat degradation under UV and visible light irradiation due to this sample revealed both the highest specific surface area and nitrogen content level. Moreover, percent paraquat removal significantly decreased with increasing calcination treatment temperature. The nitrogen content level in TiO₂ accelerated the rate of reaction with combining the effect of the specific surface area that generated the electrons and holes during illuminated with light. Therefore, the specific surface area and nitrogen content level demonstrated the important roles in the photocatalytic activity of paraquat under UV and visible light illumination.

Keywords: restraining phase transformation, interstitial site, chemical charge state, photocatalysis, paraquat degradation

Procedia PDF Downloads 132

Authors: Alessandro Evangelista, Vito M. Manghisi, Michele Gattullo, Enricoandrea Laviola

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In this work, we propose a custom visualization technique for Out-Of-View-Objects in Virtual and Augmented Reality applications using Head Mounted Displays. In the last two decades, Augmented Reality (AR) and Virtual Reality (VR) technologies experienced a remarkable growth of applications for navigation, interaction, and collaboration in different types of environments, real or virtual. Both environments can be potentially very complex, as they can include many virtual objects located in different places. Given the natural limitation of the human Field of View (about 210° horizontal and 150° vertical), humans cannot perceive objects outside this angular range. Moreover, despite recent technological advances in AR e VR Head-Mounted Displays (HMDs), these devices still suffer from a limited Field of View, especially regarding Optical See-Through displays, thus greatly amplifying the challenge of visualizing out-of-view objects. This problem is not negligible when the user needs to be aware of the number and the position of the out-of-view objects in the environment. For instance, during a maintenance operation on a construction site where virtual objects serve to improve the dangers' awareness. Providing such information can enhance the comprehension of the scene, enable fast navigation and focused search, and improve users' safety. In our research, we investigated how to represent out-of-view-objects in HMD User Interfaces (UI). Inspired by commercial video games such as Call of Duty Modern Warfare, we designed a customized Compass. By exploiting the Unity 3D graphics engine, we implemented our custom solution that can be used both in AR and VR environments. The Compass Bar consists of a graduated bar (in degrees) at the top center of the UI. The values of the bar range from -180 (far left) to +180 (far right), the zero is placed in front of the user. Two vertical lines on the bar show the amplitude of the user's field of view. Every virtual object within the scene is represented onto the compass bar as a specific color-coded proxy icon (a circular ring with a colored dot at its center). To provide the user with information about the distance, we implemented a specific algorithm that increases the size of the inner dot as the user approaches the virtual object (i.e., when the user reaches the object, the dot fills the ring). This visualization technique for out-of-view objects has some advantages. It allows users to be quickly aware of the number and the position of the virtual objects in the environment. For instance, if the compass bar displays the proxy icon at about +90, users will immediately know that the virtual object is to their right and so on. Furthermore, by having qualitative information about the distance, users can optimize their speed, thus gaining effectiveness in their work. Given the small size and position of the Compass Bar, our solution also helps lessening the occlusion problem thus increasing user acceptance and engagement. As soon as the lockdown measures will allow, we will carry out user-tests comparing this solution with other state-of-the-art existing ones such as 3D Radar, SidebARs and EyeSee360.

Keywords: augmented reality, situation awareness, virtual reality, visualization design

Procedia PDF Downloads 108

Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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Authors: Martin Arguelles Perez, Woosoon Yim, Alexander Barzilov

Abstract:

High-fidelity radiation monitoring is an essential component in the enhancement of the situational awareness capabilities of the Department of Energy’s Office of Environmental Management (DOE-EM) personnel. In this paper, multiple units of unmanned aerial vehicles (UAVs) each equipped with a cadmium zinc telluride (CZT) gamma-ray sensor are used for radiation source localization, which can provide vital real-time data for the EM tasks. To achieve this goal, a fully autonomous system of multicopter-based UAV swarm in 3D tetrahedron formation is used for surveying the area of interest and performing radiation source localization. The CZT sensor used in this study is suitable for small-size multicopter UAVs due to its small size and ease of interfacing with the UAV’s onboard electronics for high-resolution gamma spectroscopy enabling the characterization of radiation hazards. The multicopter platform with a fully autonomous flight feature is suitable for low-altitude applications such as radiation contamination sites. The conventional approach uses a single UAV mapping in a predefined waypoint path to predict the relative location and strength of the source, which can be time-consuming for radiation localization tasks. The proposed UAV swarm-based approach can significantly improve its ability to search for and track radiation sources. In this paper, two approaches are developed using (a) 2D planar circular (3 UAVs) and (b) 3D tetrahedron formation (4 UAVs). In both approaches, accurate estimation of the gradient vector is crucial for heading angle calculation. Each UAV carries the CZT sensor; the real-time radiation data are used for the calculation of a bulk heading vector for the swarm to achieve a UAV swarm’s source-seeking behavior. Also, a spinning formation is studied for both cases to improve gradient estimation near a radiation source. In the 3D tetrahedron formation, a UAV located closest to the source is designated as a lead unit to maintain the tetrahedron formation in space. Such a formation demonstrated a collective and coordinated movement for estimating a gradient vector for the radiation source and determining an optimal heading direction of the swarm. The proposed radiation localization technique is studied by computer simulation and validated experimentally in the indoor flight testbed using gamma sources. The technology presented in this paper provides the capability to readily add/replace radiation sensors to the UAV platforms in the field conditions enabling extensive condition measurement and greatly improving situational awareness and event management. Furthermore, the proposed radiation localization approach allows long-term measurements to be efficiently performed at wide areas of interest to prevent disasters and reduce dose risks to people and infrastructure.

Keywords: radiation, unmanned aerial system(UAV), source localization, UAV swarm, tetrahedron formation

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Authors: Guilherme M. Pereira, Kimmo Teinïla, Danilo Custódio, Risto Hillamo, Célia Alves, Pérola de C. Vasconcellos

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South American large cities often present serious air pollution problems and their atmosphere composition is influenced by a variety of emissions sources. The South American Emissions Megacities, and Climate project (SAEMC) has focused on the study of emissions and its influence on climate in the South American largest cities and it also included Lima (Peru) and Medellin (Colombia), sites where few studies of the genre were done. Lima is a coastal city with more than 8 million inhabitants and the second largest city in South America. Medellin is a 2.5 million inhabitants city and second largest city in Colombia; it is situated in a valley. The samples were collected in quartz fiber filters in high volume samplers (Hi-Vol), in 24 hours of sampling. The samples were collected in intensive campaigns in both sites, in July, 2010. Several species were determined in the aerosol samples of Lima and Medellin. Organic and elemental carbon (OC and EC) in thermal-optical analysis; biomass burning tracers (levoglucosan - Lev, mannosan - Man and galactosan - Gal) in high-performance anion exchange ion chromatography with mass spectrometer detection; water soluble ions in ion chromatography. The average particulate matter was similar for both campaigns, the PM10 concentrations were above the recommended by World Health Organization (50 µg m⁻³ – daily limit) in 40% of the samples in Medellin, while in Lima it was above that value in 15% of the samples. The average total ions concentration was higher in Lima (17450 ng m⁻³ in Lima and 3816 ng m⁻³ in Medellin) and the average concentrations of sodium and chloride were higher in this site, these species also had better correlations (Pearson’s coefficient = 0,63); suggesting a higher influence of marine aerosol in the site due its location in the coast. Sulphate concentrations were also much higher at Lima site; which may be explained by a higher influence of marine originated sulphate. However, the OC, EC and monosaccharides average concentrations were higher at Medellin site; this may be due to the lower dispersion of pollutants due to the site’s location and a larger influence of biomass burning sources. The levoglucosan average concentration was 95 ng m⁻³ for Medellin and 16 ng m⁻³ and OC was well correlated with levoglucosan (Pearson’s coefficient = 0,86) in Medellin; suggesting a higher influence of biomass burning over the organic aerosol in this site. The Lev/Man ratio is often related to the type of biomass burned and was close to 18, similar to the observed in previous studies done at biomass burning impacted sites in the Amazon region; backward trajectories also suggested the transport of aerosol from that region. Biomass burning appears to have a larger influence on the air quality in Medellin, in addition the vehicular emissions; while Lima showed a larger influence of marine aerosol during the study period.

Keywords: aerosol transport, atmospheric particulate matter, biomass burning, SAEMC project

Procedia PDF Downloads 243

Authors: Bastien Sanglard, Simon Cayez, Guillaume Viau, Thomas Blon, Julian Carrey, Sébastien Lachaize

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The need to develop clean production processes is a key challenge of any industry. Steel and iron industries are particularly concerned since they emit 6.8% of global anthropogenic greenhouse gas emissions. One key step of the process is the high-temperature reduction of iron ore using coke, leading to large amounts of CO2 emissions. One route to decrease impacts is to get rid of fossil fuels by changing both the heat source and the reducer. The present work aims at investigating experimentally the possibility to use concentrated solar energy and carbon-free reducing agents. Two sets of experimentations were realized. First, in situ X-ray diffraction on pure and industrial powder of hematite was realized to study the phase evolution as a function of temperature during reduction under hydrogen and ammonia. Secondly, experiments were performed on industrial iron ore pellets, which were reduced by NH3 or H2 into a “solar furnace” composed of a controllable 1600W Xenon lamp to simulate and control the solar concentrated irradiation of a glass reactor and of a diaphragm to control light flux. Temperature and pressure were recorded during each experiment via thermocouples and pressure sensors. The percentage of iron oxide converted to iron (called thereafter “reduction ratio”) was found through Rietveld refinement. The power of the light source and the reduction time were varied. Results obtained in the diffractometer reaction chamber show that iron begins to form at 300°C with pure Fe2O3 powder and 400°C with industrial iron ore when maintained at this temperature for 60 minutes and 80 minutes, respectively. Magnetite and wuestite are detected on both powders during the reduction under hydrogen; under ammonia, iron nitride is also detected for temperatures between400°C and 600°C. All the iron oxide was converted to iron for a reaction of 60 min at 500°C, whereas a conversion ratio of 96% was reached with industrial powder for a reaction of 240 min at 600°C under hydrogen. Under ammonia, full conversion was also reached after 240 min of reduction at 600 °C. For experimentations into the solar furnace with iron ore pellets, the lamp power and the shutter opening were varied. An 83.2% conversion ratio was obtained with a light power of 67 W/cm2 without turning over the pellets. Nevertheless, under the same conditions, turning over the pellets in the middle of the experiment permits to reach a conversion ratio of 86.4%. A reduction ratio of 95% was reached with an exposure of 16 min by turning over pellets at half time with a flux of 169W/cm2. Similar or slightly better results were obtained under an ammonia reducing atmosphere. Under the same flux, the highest reduction yield of 97.3% was obtained under ammonia after 28 minutes of exposure. The chemical reaction itself, including the solar heat source, does not produce any greenhouse gases, so solar metallurgy represents a serious way to reduce greenhouse gas emission of metallurgy industry. Nevertheless, the ecological impact of the reducers must be investigated, which will be done in future work.

Keywords: solar concentration, metallurgy, ammonia, hydrogen, sustainability

Procedia PDF Downloads 115

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 21

Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

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Authors: Ayesha Anjum, Arbaz Basha

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Active Galactic Nuclei (AGN) are the actively accreting centers of the galaxies that host supermassive black holes. AGN emits radiation in all wavelengths and also shows variability across all the wavelength bands. The analysis of flux variability tells us about the morphology of the site of emission radiation. Some of the major classifications of AGN are (a) Blazars, with featureless spectra. They are subclassified as BLLacertae objects, Flat Spectrum Radio Quasars (FSRQs), and others; (b) Seyferts with prominent emission line features are classified into Broad Line, Narrow Line Seyferts of Type 1 and Type 2 (c) quasars, and other types. Sloan Digital Sky Survey (SDSS) is an optical telescope based in Mexico that has observed and classified billions of objects based on automated photometric and spectroscopic methods. A sample of blazars is obtained from the third Fermi catalog. For variability analysis, we searched for light curves for these objects in Wide-Field Infrared Survey Explorer (WISE) and Near Earth Orbit WISE (NEOWISE) in two bands: W1 (3.4 microns) and W2 (4.6 microns), reducing the final sample to 256 objects. These objects are also classified into 155 BLLacs, 99 FSRQs, and 2 Narrow Line Seyferts, namely, PMNJ0948+0022 and PKS1502+036. Mid-infrared variability studies of these objects would be a contribution to the literature. With this as motivation, the present work is focused on studying a final sample of 256 objects in general and the Seyferts in particular. Owing to the fact that the classification is automated, SDSS has miclassified these objects into quasars, galaxies, and stars. Reasons for the misclassification are explained in this work. The variability analysis of these objects is done using the method of flux amplitude variability and excess variance. The sample consists of observations in both W1 and W2 bands. PMN J0948+0022 is observed between MJD from 57154.79 to 58810.57. PKS 1502+036 is observed between MJD from 57232.42 to 58517.11, which amounts to a period of over six years. The data is divided into different epochs spanning not more than 1.2 days. In all the epochs, the sources are found to be variable in both W1 and W2 bands. This confirms that the object is variable in mid-infrared wavebands in both long and short timescales. Also, the sources are observed for color variability. Objects either show a bluer when brighter trend (BWB) or a redder when brighter trend (RWB). The possible claim for the object to be BWB (present objects) is that the longer wavelength radiation emitted by the source can be suppressed by the high-energy radiation from the central source. Another result is that the smallest radius of the emission source is one day since the epoch span used in this work is one day. The mass of the black holes at the centers of these sources is found to be less than or equal to 108 solar masses, respectively.

Keywords: active galaxies, variability, Seyfert galaxies, SDSS, WISE

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Authors: Yakup Ulusu, Faruk Ozel, Numan Eczacioglu, Abdurrahman Ozen, Sabriye Acikgoz

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GFP discovered in the mid-1970s, has been used as a marker after replicated genetic study by scientists. In biotechnology, cell, molecular biology, the GFP gene is frequently used as a reporter of expression. In modified forms, it has been used to make biosensors. Many animals have been created that express GFP as an evidence that a gene can be expressed throughout a given organism. Proteins labeled with GFP identified locations are determined. And so, cell connections can be monitored, gene expression can be reported, protein-protein interactions can be observed and signals that create events can be detected. Additionally, monitoring GFP is noninvasive; it can be detected by under UV-light because of simply generating fluorescence. Moreover, GFP is a relatively small and inert molecule, that does not seem to treat any biological processes of interest. The synthesis of GFP has some steps like, to construct the plasmid system, transformation in E. coli, production and purification of protein. GFP carrying plasmid vector pBAD–GFPuv was digested using two different restriction endonuclease enzymes (NheI and Eco RI) and DNA fragment of GFP was gel purified before cloning. The GFP-encoding DNA fragment was ligated into pET28a plasmid using NheI and Eco RI restriction sites. The final plasmid was named pETGFP and DNA sequencing of this plasmid indicated that the hexa histidine-tagged GFP was correctly inserted. Histidine-tagged GFP was expressed in an Escherichia coli BL21 DE3 (pLysE) strain. The strain was transformed with pETGFP plasmid and grown on LuiraBertoni (LB) plates with kanamycin and chloramphenicol selection. E. coli cells were grown up to an optical density (OD 600) of 0.8 and induced by the addition of a final concentration of 1mM isopropyl-thiogalactopyranoside (IPTG) and then grown for additional 4 h. The amino-terminal hexa-histidine-tag facilitated purification of the GFP by using a His Bind affinity chromatography resin (Novagen). Purity of GFP protein was analyzed by a 12 % sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). The concentration of protein was determined by UV absorption at 280 nm (Varian Cary 50 Scan UV/VIS spectrophotometer). Synthesis of GFP-Polymer composite nanofibers was produced by using GFP solution (10mg/mL) and polymer precursor Polyvinylpyrrolidone, (PVP, Mw=1300000) as starting materials and template, respectively. For the fabrication of nanofibers with the different fiber diameter; a sol–gel solution comprising of 0.40, 0.60 and 0.80 g PVP (depending upon the desired fiber diameter) and 100 mg GFP in 10 mL water: ethanol (3:2) mixtures were prepared and then the solution was covered on collecting plate via electro spinning at 10 kV with a feed-rate of 0.25 mL h-1 using Spellman electro spinning system. Results show that GFP-based nano-fiber can be used plenty of biomedical applications such as bio-imaging, bio-mechanic, bio-material and tissue engineering.

Keywords: biomaterial, GFP, nano-fibers, protein expression

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Authors: Wiolene Montanari Nordi, Debora Botequio Moretti, Mariana Caroline Pontin, Jessica Pampolini, Raul Machado-Neto

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Gills are organs responsible for respiration and osmoregulation between the fish internal environment and water. Under stress conditions, oxidative response and gill plasticity to attempt to increase gas exchange area are noteworthy, compromising the physiological processes and therefore fish health. Colostrum is a dietary source of nutrients, immunoglobulin, antioxidant and bioactive molecules, essential for immunological protection and development of the gastrointestinal epithelium. The hypothesis of this work is that antioxidant factors present in the colostrum, unprecedentedly tested in gills, can minimize or reduce the alteration of its epithelium structure of juvenile pacu (Piaractus mesopotamicus) subjected to high stocking density. The histological changes in the gills architecture were characterized by the frequency, incidence and severity of the tissue alteration and ionic status. Juvenile (50 kg fish/m3) were fed with pelleted diets containing 0, 10, 20 or 30% of lyophilized bovine colostrum (LBC) inclusion and at 30 experimental days, gill and blood samples were collected in eight fish per treatment. The study revealed differences in the type, frequency and severity (histological alterations index – HAI) of tissue alterations among the treatments, however, no distinct differences in the incidence of alteration (mean alteration value – MAV) were observed. The main histological changes in gill were elevation of the lamellar epithelium, excessive cell proliferation of the filament and lamellar epithelium causing total or partial melting of the lamella, hyperplasia and hypertrophy of lamellar and filament epithelium, uncontrolled thickening of filament and lamellar tissues, mucous and chloride cells presence in the lamella, aneurysms, vascular congestion and presence of parasites. The MAV obtained per treatment were 2.0, 2.5, 1.8 and 2.5 to fish fed diets containing 0, 10, 20 and 30% of LBC inclusion, respectively, classifying the incidence of gill alterations as slightly to moderate. The severity of alteration of individual fish of treatment 0, 10 and 20% LBC ranged values from 5 to 40 (HAI average of 20.1, 17.5 and 17.6, respectively, P > 0.05), and differs from 30% LBC, that ranged from 6 to 129 (HAI mean of 77.2, P < 0.05). The HAI value in the treatments 0, 10 and 20% LBC reveals gill tissue with injuries classified from slightly to moderate, while in 30% LBC moderate to severe, consequence of the onset of necrosis in the tissue of two fish that compromises the normal functioning of the organ. In relation to frequency of gill alterations, evaluated according to absence of alterations (0) to highly frequent (+++), histological alterations were observed in all evaluated fish, with a trend of higher frequency in 0% LBC. The concentration of Na+, Cl-, K+ and Ca2+ did not changed in all treatments (P > 0.05), indicating similar capacity of ion exchange. The concentrations of bovine colostrum used in diets of present study did not impair the alterations observed in the gills of juvenile pacu.

Keywords: histological alterations of gill tissue, ionic status, lyophilized bovine colostrum, optical microscopy

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Authors: Gizem Kayar, Ramazan Bakir, M. Ilkay Koşar, Ceren U. Gencer, Alperen Ayyildiz

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Anatomy classes are crucial for general education of medical students, whereas learning anatomy is quite challenging and requires memorization of thousands of structures. In traditional teaching methods, learning materials are still based on books, anatomy mannequins, or videos. This results in forgetting many important structures after several years. However, more interactive teaching methods like virtual reality, augmented reality, gamification, and motion sensors are becoming more popular since such methods ease the way we learn and keep the data in mind for longer terms. During our study, we designed a virtual reality based digital head anatomy platform to investigate whether a fully interactive anatomy platform is effective to learn anatomy and to understand the level of teaching and learning optimization. The Head is one of the most complicated human anatomy structures, with thousands of tiny, unique structures. This makes the head anatomy one of the most difficult parts to understand during class sessions. Therefore, we developed a fully interactive digital tool with 3D model marking, quiz structures, 2D/3D puzzle structures, and VR support so as to integrate the power of VR and gamification. The project has been developed in Unity game engine with HTC Vive Cosmos VR headset. The head anatomy 3D model has been selected with full skeletal, muscular, integumentary, head, teeth, lymph, and vein system. The biggest issue during the development was the complexity of our model and the marking of it in the 3D world system. 3D model marking requires to access to each unique structure in the counted subsystems which means hundreds of marking needs to be done. Some parts of our 3D head model were monolithic. This is why we worked on dividing such parts to subparts which is very time-consuming. In order to subdivide monolithic parts, one must use an external modeling tool. However, such tools generally come with high learning curves, and seamless division is not ensured. Second option was to integrate tiny colliders to all unique items for mouse interaction. However, outside colliders which cover inner trigger colliders cause overlapping, and these colliders repel each other. Third option is using raycasting. However, due to its own view-based nature, raycasting has some inherent problems. As the model rotate, view direction changes very frequently, and directional computations become even harder. This is why, finally, we studied on the local coordinate system. By taking the pivot point of the model into consideration (back of the nose), each sub-structure is marked with its own local coordinate with respect to the pivot. After converting the mouse position to the world position and checking its relation with the corresponding structure’s local coordinate, we were able to mark all points correctly. The advantage of this method is its applicability and accuracy for all types of monolithic anatomical structures.

Keywords: anatomy, e-learning, virtual reality, 3D model marking

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Authors: Sanjana S. Mallya, Roshan Arvind Sivakumar

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Orthotics is the branch of medicine that deals with the provision and use of artificial casts or braces to alter the biomechanical structure of the limb and provide support for the limb. Custom-made orthoses provide more comfort and can correct issues better than those available over-the-counter. However, they are expensive and require intricate modelling of the limb. Traditional methods of modelling involve creating a plaster of Paris mould of the limb. Lately, CAD/CAM and 3D printing processes have improved the accuracy and reduced the production time. Ordinarily, digital cameras are used to capture the features of the limb from different views to create a 3D model. We propose a system to model the limb using Microsoft Kinect2 sensor. The Kinect can capture RGB and depth frames simultaneously up to 30 fps with sufficient accuracy. The region of interest is captured from three views, each shifted by 90 degrees. The RGB and depth data are fused into a single RGB-D frame. The resolution of the RGB frame is 1920px x 1080px while the resolution of the Depth frame is 512px x 424px. As the resolution of the frames is not equal, RGB pixels are mapped onto the Depth pixels to make sure data is not lost even if the resolution is lower. The resulting RGB-D frames are collected and using the depth coordinates, a three dimensional point cloud is generated for each view of the Kinect sensor. A common reference system was developed to merge the individual point clouds from the Kinect sensors. The reference system consisted of 8 coloured cubes, connected by rods to form a skeleton-cube with the coloured cubes at the corners. For each Kinect, the region of interest is the square formed by the centres of the four cubes facing the Kinect. The point clouds are merged by considering one of the cubes as the origin of a reference system. Depending on the relative distance from each cube, the three dimensional coordinate points from each point cloud is aligned to the reference frame to give a complete point cloud. The RGB data is used to correct for any errors in depth data for the point cloud. A triangular mesh is generated from the point cloud by applying Delaunay triangulation which generates the rough surface of the limb. This technique forms an approximation of the surface of the limb. The mesh is smoothened to obtain a smooth outer layer to give an accurate model of the limb. The model of the limb is used as a base for designing the custom orthotic brace or cast. It is transferred to a CAD/CAM design file to design of the brace above the surface of the limb. The proposed system would be more cost effective than current systems that use MRI or CT scans for generating 3D models and would be quicker than using traditional plaster of Paris cast modelling and the overall setup time is also low. Preliminary results indicate that the accuracy of the Kinect2 is satisfactory to perform modelling.

Keywords: 3d scanning, mesh generation, Microsoft kinect, orthotics, registration

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Authors: Alexandre Daliberto Frugoli, Pedro Jose Gabriel Ferreira, Pedro Americo Frugoli, Lucio Leonardo, Thais Cavalheri Santos

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Laboratory classes in Engineering courses are essential for students to be able to integrate theory with practical reality, by handling equipment and observing experiments. In the researches of physical phenomena, students can learn about the complexities of science. Over the past years, universities in developing countries have been reducing the course load of engineering courses, in accordance with cutting cost agendas. Quality education is the object of study for researchers and requires educators and educational administrators able to demonstrate that the institutions are able to provide great learning opportunities at reasonable costs. Didactic test benches are indispensable equipment in educational activities related to turbo hydraulic pumps and pumping facilities study, which have a high cost and require long class time due to measurements and equipment adjustment time. In order to overcome the aforementioned obstacles, aligned with the professional objectives of an engineer, GruPEFE - UNIP (Research Group in Physics Education for Engineering - Universidade Paulista) has developed a multi-purpose stand for the discipline of fluid mechanics which allows the study of velocity and flow meters, loads losses and pump association. In this work, results obtained by the association in series and in parallel of hydraulic pumps will be presented and discussed, mainly analyzing the repeatability of experimental procedures and their agreement with the theory. For the association in series two identical pumps were used, consisting of the connection of the discharge of a pump to the suction of the next one, allowing the fluid to receive the power of all machines in the association. The characteristic curve of the set is obtained from the curves of each of the pumps, by adding the heads corresponding to the same flow rates. The same pumps were associated in parallel. In this association, the discharge piping is common to the two machines together. The characteristic curve of the set was obtained by adding to each value of H (head height), the flow rates of each pump. For the tests, the input and output pressure of each pump were measured. For each set there were three sets of measurements, varying the flow rate in range from 6.0 to 8.5 m 3 / h. For the two associations, the results showed an excellent repeatability with variations of less than 10% between sets of measurements and also a good agreement with the theory. This variation agrees with the instrumental uncertainty. Thus, the results validate the use of the fluids bench designed for didactic purposes. As a future work, a digital acquisition system is being developed, using differential sensors of extremely low pressures (2 to 2000 Pa approximately) for the microcontroller Arduino.

Keywords: engineering education, fluid mechanics, hydrostatic pumps association, multi-purpose stand

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Authors: Ekaterina A. Savchenko, Elena N. Velichko, Evgenii T. Aksenov

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The development of pathological processes, such as cardiovascular and oncological diseases, are accompanied by changes in molecular parameters in cells, tissues, and serum. The study of the behavior of protein molecules in solutions is of primarily importance for diagnosis of such diseases. Various physical and chemical methods are used to study molecular systems. With the advent of the laser and advances in electronics, optical methods, such as scanning electron microscopy, sedimentation analysis, nephelometry, static and dynamic light scattering, have become the most universal, informative and accurate tools for estimating the parameters of nanoscale objects. The electrophoretic light scattering is the most effective technique. It has a high potential in the study of biological solutions and their properties. This technique allows one to investigate the processes of aggregation and dissociation of different macromolecules and obtain information on their shapes, sizes and molecular weights. Electrophoretic light scattering is an analytical method for registration of the motion of microscopic particles under the influence of an electric field by means of quasi-elastic light scattering in a homogeneous solution with a subsequent registration of the spectral or correlation characteristics of the light scattered from a moving object. We modified the technique by using the regime of total internal reflection with the aim of increasing its sensitivity and reducing the volume of the sample to be investigated, which opens the prospects of automating simultaneous multiparameter measurements. In addition, the method of total internal reflection allows one to study biological fluids on the level of single molecules, which also makes it possible to increase the sensitivity and the informativeness of the results because the data obtained from an individual molecule is not averaged over an ensemble, which is important in the study of bimolecular fluids. To our best knowledge the study of electrophoretic light scattering in the regime of total internal reflection is proposed for the first time, latex microspheres 1 μm in size were used as test objects. In this study, the total internal reflection regime was realized on a quartz prism where the free electrophoresis regime was set. A semiconductor laser with a wavelength of 655 nm was used as a radiation source, and the light scattering signal was registered by a pin-diode. Then the signal from a photodetector was transmitted to a digital oscilloscope and to a computer. The autocorrelation functions and the fast Fourier transform in the regime of Brownian motion and under the action of the field were calculated to obtain the parameters of the object investigated. The main result of the study was the dependence of the autocorrelation function on the concentration of microspheres and the applied field magnitude. The effect of heating became more pronounced with increasing sample concentrations and electric field. The results obtained in our study demonstrated the applicability of the method for the examination of liquid solutions, including biological fluids.

Keywords: light scattering, electrophoretic light scattering, electrophoresis, total internal reflection

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Authors: Sigal Portnoy, Jason Friedman, Eitan Raveh

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Introduction: Sensory substitution is possible due to the capacity of our brain to adapt to information transmitted by a synthetic receptor via an alternative sensory system. Practical sensory substitution systems are being developed in order to increase the functionality of individuals with sensory loss, e.g. amputees. For upper limb prosthetic-users the loss of tactile feedback compels them to allocate visual attention to their prosthesis. The effect of adding vibrotactile feedback (VTF) to the applied force has been studied, however its effect on the allocation if visual attention during dual-tasking and the response during misleading visual feedback have not been studied. We hypothesized that VTF will improve the performance and reduce visual attention during dual-task assignments in healthy individuals using a robotic hand and improve the performance in a standardized functional test, despite the presence of misleading visual feedback. Methods: For the dual-task paradigm, twenty healthy subjects were instructed to toggle two keyboard arrow keys with the left hand to retain a moving virtual car on a road on a screen. During the game, instructions for various activities, e.g. mix the sugar in the glass with a spoon, appeared on the screen. The subject performed these tasks with a robotic hand, attached to the right hand. The robotic hand was controlled by the activity of the flexors and extensors of the right wrist, recorded using surface EMG electrodes. Pressure sensors were attached at the tips of the robotic hand and induced VTF using vibrotactile actuators attached to the right arm of the subject. An eye-tracking system tracked to visual attention of the subject during the trials. The trials were repeated twice, with and without the VTF. Additionally, the subjects performed the modified box and blocks, hidden from eyesight, in a motion laboratory. A virtual presentation of a misleading visual feedback was be presented on a screen so that twice during the trial, the virtual block fell while the physical block was still held by the subject. Results: This is an ongoing study, which current results are detailed below. We are continuing these trials with transradial myoelectric prosthesis-users. In the healthy group, the VTF did not reduce the visual attention or improve performance during dual-tasking for the tasks that were typed transfer-to-target, e.g. place the eraser on the shelf. An improvement was observed for other tasks. For example, the average±standard deviation of time to complete the sugar-mixing task was 13.7±17.2s and 19.3±9.1s with and without the VTF, respectively. Also, the number of gaze shifts from the screen to the hand during this task were 15.5±23.7 and 20.0±11.6, with and without the VTF, respectively. The response of the subjects to the misleading visual feedback did not differ between the two conditions, i.e. with and without VTF. Conclusions: Our interim results suggest that the performance of certain activities of daily living may be improved by VTF. The substitution of visual sensory input by tactile feedback might require a long training period so that brain plasticity can occur and allow adaptation to the new condition.

Keywords: prosthetics, rehabilitation, sensory substitution, upper limb amputation

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Authors: Moustafa Osman Mohammed

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This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.

Keywords: autopoiesis, nanoparticles, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system

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Authors: Zulkifli, I. W. Eltara, Anawati

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Understanding the complementary roles of surface energy and roughness on natural nonwetting surfaces has led to the development of a number of biomimetic superhydrophobic surfaces, which exhibit apparent contact angles with water greater than 150 degrees and low contact angle hysteresis. However, superoleophobic surfaces—those that display contact angles greater than 150 degrees with organic liquids having appreciably lower surface tensions than that of water—are extremely rare. In addition to chemical composition and roughened texture, a third parameter is essential to achieve superoleophobicity, namely, re-entrant surface curvature in the form of overhang structures. The overhangs can be realized as fibers. Superoleophobic surfaces are appealing for example, antifouling, since purely superhydrophobic surfaces are easily contaminated by oily substances in practical applications, which in turn will impair the liquid repellency. On the other studied have demonstrate that such aqueous nanofibrillar gels are unexpectedly robust to allow formation of highly porous aerogels by direct water removal by freeze-drying, they are flexible, unlike most aerogels that suffer from brittleness, and they allow flexible hierarchically porous templates for functionalities, e.g. for electrical conductivity. No crosslinking, solvent exchange nor supercritical drying are required to suppress the collapse during the aerogel preparation, unlike in typical aerogel preparations. The aerogel used in current work is an ultralight weight solid material composed of native cellulose nanofibers. The native cellulose nanofibers are cleaved from the self-assembled hierarchy of macroscopic cellulose fibers. They have become highly topical, as they are proposed to show extraordinary mechanical properties due to their parallel and grossly hydrogen bonded polysaccharide chains. We demonstrate that superoleophobic nanocellulose aerogels coating by sol-gel method, the aerogel is capable of supporting a weight nearly 3 orders of magnitude larger than the weight of the aerogel itself. The load support is achieved by surface tension acting at different length scales: at the macroscopic scale along the perimeter of the carrier, and at the microscopic scale along the cellulose nanofibers by preventing soaking of the aerogel thus ensuring buoyancy. Superoleophobic nanocellulose aerogels have recently been achieved using unmodified cellulose nanofibers and using carboxy methylated, negatively charged cellulose nanofibers as starting materials. In this work, the aerogels made from unmodified cellulose nanofibers were subsequently treated with fluorosilanes. To complement previous work on superoleophobic aerogels, we demonstrate their application as cargo carriers on oil, gas permeability, plastrons, and drag reduction, and we show that fluorinated nanocellulose aerogels are high-adhesive superoleophobic surfaces. We foresee applications including buoyant, gas permeable, dirt-repellent coatings for miniature sensors and other devices floating on generic liquid surfaces.

Keywords: superoleophobic, nanocellulose, aerogel, sol-gel

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

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Authors: M. Salvador, J. C. Martinez-Garcia, A. Moyano, M. C. Blanco-Lopez, M. Rivas

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Biosensors play a crucial role in the detection of molecules nowadays due to their advantages of user-friendliness, high selectivity, the analysis in real time and in-situ applications. Among them, Lateral Flow Immunoassays (LFIAs) are presented among technologies for point-of-care bioassays with outstanding characteristics such as affordability, portability and low-cost. They have been widely used for the detection of a vast range of biomarkers, which do not only include proteins but also nucleic acids and even whole cells. Although the LFIA has traditionally been a positive/negative test, tremendous efforts are being done to add to the method the quantifying capability based on the combination of suitable labels and a proper sensor. One of the most successful approaches involves the use of magnetic sensors for detection of magnetic labels. Bringing together the required characteristics mentioned before, our research group has developed a biosensor to detect biomolecules. Superparamagnetic nanoparticles (SPNPs) together with LFIAs play the fundamental roles. SPMNPs are detected by their interaction with a high-frequency current flowing on a printed micro track. By means of the instant and proportional variation of the impedance of this track provoked by the presence of the SPNPs, quantitative and rapid measurement of the number of particles can be obtained. This way of detection requires no external magnetic field application, which reduces the device complexity. On the other hand, the major limitations of LFIAs are that they are only qualitative or semiquantitative when traditional gold or latex nanoparticles are used as color labels. Moreover, the necessity of always-constant ambient conditions to get reproducible results, the exclusive detection of the nanoparticles on the surface of the membrane, and the short durability of the signal are drawbacks that can be advantageously overcome with the design of magnetically labeled LFIAs. The approach followed was to coat the SPIONs with a specific monoclonal antibody which targets the protein under consideration by chemical bonds. Then, a sandwich-type immunoassay was prepared by printing onto the nitrocellulose membrane strip a second antibody against a different epitope of the protein (test line) and an IgG antibody (control line). When the sample flows along the strip, the SPION-labeled proteins are immobilized at the test line, which provides magnetic signal as described before. Preliminary results using this practical combination for the detection and quantification of the Prostatic-Specific Antigen (PSA) shows the validity and consistency of the technique in the clinical range, where a PSA level of 4.0 ng/mL is the established upper normal limit. Moreover, a LOD of 0.25 ng/mL was calculated with a confident level of 3 according to the IUPAC Gold Book definition. Its versatility has also been proved with the detection of other biomolecules such as troponin I (cardiac injury biomarker) or histamine.

Keywords: biosensor, lateral flow immunoassays, point-of-care devices, superparamagnetic nanoparticles

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Authors: Abdelkhalek Bouchikhi, Elyes Benmokhtar, Sebastien Saletzki

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The aeronautical field is experiencing issues with RF spectrum congestion due to the constant increase in the number of flights, aircrafts and telecom systems on board. In addition, these systems are bulky in size, weight and energy consumption. The cognitive radio helps particularly solving the spectrum congestion issue by its capacity to detect idle frequency channels then, allowing an opportunistic exploitation of the RF spectrum. The present work aims to propose a new use case for aeronautical spectrum sharing and to study the performances of three different detection techniques: energy detector, matched filter and cyclostationary detector within the aeronautical use case. The spectrum in the proposed cognitive radio is allocated dynamically where each cognitive radio follows a cognitive cycle. The spectrum sensing is a crucial step. The goal of the sensing is gathering data about the surrounding environment. Cognitive radio can use different sensors: antennas, cameras, accelerometer, thermometer, etc. In IEEE 802.22 standard, for example, a primary user (PU) has always the priority to communicate. When a frequency channel witch used by the primary user is idle, the secondary user (SU) is allowed to transmit in this channel. The Distance Measuring Equipment (DME) is composed of a UHF transmitter/receiver (interrogator) in the aircraft and a UHF receiver/transmitter on the ground. While the future cognitive radio will be used jointly to alleviate the spectrum congestion issue in the aeronautical field. LDACS, for example, is a good candidate; it provides two isolated data-links: ground-to-air and air-to-ground data-links. The first contribution of the present work is a strategy allowing sharing the L-band. The adopted spectrum sharing strategy is as follow: the DME will play the role of PU which is the licensed user and the LDACS1 systems will be the SUs. The SUs could use the L-band channels opportunely as long as they do not causing harmful interference signals which affect the QoS of the DME system. Although the spectrum sensing is a key step, it helps detecting holes by determining whether the primary signal is present or not in a given frequency channel. A missing detection on primary user presence creates interference between PU and SU and will affect seriously the QoS of the legacy radio. In this study, first brief definitions, concepts and the state of the art of cognitive radio will be presented. Then, a study of three communication channel detection algorithms in a cognitive radio context is carried out. The study is made from the point of view of functions, material requirements and signal detection capability in the aeronautical field. Then, we presented a modeling of the detection problem by three different methods (energy, adapted filter, and cyclostationary) as well as an algorithmic description of these detectors is done. Then, we study and compare the performance of the algorithms. Simulations were carried out using MATLAB software. We analyzed the results based on ROCs curves for SNR between -10dB and 20dB. The three detectors have been tested with a synthetics and real world signals.

Keywords: aeronautic, communication, navigation, surveillance systems, cognitive radio, spectrum sensing, software defined radio

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Authors: Moustafa Osman Mohammed

Abstract:

This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

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Authors: Sahar Majed Asad

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Industrial structures have historically focused on functionality and efficiency, often disregarding aesthetics and human experience. However, a new approach is emerging that prioritizes humanizing industrial architecture and creating spaces that promote well-being, sustainability, and social responsibility. This study explores the motivations and design strategies behind this shift towards more human-centered industrial environments, providing practical guidance for architects, designers, and other stakeholders interested in incorporating these principles into their work. Through in-depth interviews with architects, designers, and industry experts, as well as a review of relevant literature, this study uncovers the reasons for this change in industrial design. The findings reveal that this shift is driven by a desire to create environments that prioritize the needs and experiences of the people who use them. The study identifies strategies such as incorporating natural elements, flexible design, and advanced technologies as crucial in achieving human-centric industrial design. It also emphasizes that effective communication and collaboration among stakeholders are crucial for successful human-centered design outcomes. This paper provides a comprehensive analysis of the motivations and design strategies behind the humanization of industrial architecture. It begins by examining the history of industrial architecture and highlights the focus on functionality and efficiency. The paper then explores the emergence of human-centered design principles in industrial architecture, discussing the benefits of this approach, including creating more sustainable and socially responsible environments.The paper explains specific design strategies that prioritize the human experience of industrial spaces. It outlines how incorporating natural elements like greenery and natural lighting can create more visually appealing and comfortable environments for industrial workers. Flexible design solutions, such as movable walls and modular furniture, can make spaces more adaptable to changing needs and promote a sense of ownership and creativity among workers. Advanced technologies, such as sensors and automation, can improve the efficiency and safety of industrial spaces while also enhancing the human experience. To provide practical guidance, the paper offers recommendations for incorporating human-centered design principles into industrial structures. It emphasizes the importance of understanding the needs and experiences of the people who use these spaces and provides specific examples of how natural elements, flexible design, and advanced technologies can be incorporated into industrial structures to promote human well-being. In conclusion, this study demonstrates that the humanization of industrial architecture is a growing trend that offers tremendous potential for creating more sustainable and socially responsible built environments. By prioritizing the human experience of industrial spaces, designers can create environments that promote well-being, sustainability, and social responsibility. This research study provides practical guidance for architects, designers, and other stakeholders interested in incorporating human-centered design principles into their work, demonstrating that a human-centered approach can lead to functional and aesthetically pleasing industrial spaces that promote human well-being and contribute to a better future for all.

Keywords: human-centered design, industrial architecture, sustainability, social responsibility

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Authors: Tatsuya Kasuga, Hidehisa Shimada, Kimio Oguchi

Abstract:

Recent rapid progress in ICT (Information and Communication Technology) has advanced the penetration of sensor networks (SNs) and their attractive applications. Agriculture is one of the fields well able to benefit from ICT. Plant factories control several parameters related to plant growth in closed areas such as air temperature, humidity, water, culture medium concentration, and artificial lighting by using computers and AI (Artificial Intelligence) is being researched in order to obtain stable and safe production of vegetables and medicinal plants all year anywhere, and attain self-sufficiency in food. By providing isolation from the natural environment, a plant factory can achieve higher productivity and safe products. However, the biggest issue with plant factories is the return on investment. Profits are tenuous because of the large initial investments and running costs, i.e. electric power, incurred. At present, LED (Light Emitting Diode) lights are being adopted because they are more energy-efficient and encourage photosynthesis better than the fluorescent lamps used in the past. However, further cost reduction is essential. This paper introduces experiments that reveal which color of LED lighting best enhances the growth of cultured radish sprouts. Radish sprouts were cultivated in the experimental environment formed by a hydroponics kit with three cultivation shelves (28 samples per shelf) each with an artificial lighting rack. Seven LED arrays of different color (white, blue, yellow green, green, yellow, orange, and red) were compared with a fluorescent lamp as the control. Lighting duration was set to 12 hours a day. Normal water with no fertilizer was circulated. Seven days after germination, the length, weight and area of leaf of each sample were measured. Electrical power consumption for all lighting arrangements was also measured. Results and discussions: As to average sample length, no clear difference was observed in terms of color. As regards weight, orange LED was less effective and the difference was significant (p < 0.05). As to leaf area, blue, yellow and orange LEDs were significantly less effective. However, all LEDs offered higher productivity per W consumed than the fluorescent lamp. Of the LEDs, the blue LED array attained the best results in terms of length, weight and area of leaf per W consumed. Conclusion and future works: An experiment on radish sprout cultivation under 7 different color LED arrays showed no clear difference in terms of sample size. However, if electrical power consumption is considered, LEDs offered about twice the growth rate of the fluorescent lamp. Among them, blue LEDs showed the best performance. Further cost reduction e.g. low power lighting remains a big issue for actual system deployment. An automatic plant monitoring system with sensors is another study target.

Keywords: electric power consumption, LED color, LED lighting, plant factory

Procedia PDF Downloads 167