Search results for: impedance band-width

Authors: Boriana Karamanova, Svetlana Veleva, Luybomir Soserov, Ana Arenillas, Francesco Lufrano, Antonia Stoyanova

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Supercapacitors have received a lot of research attention and are promising energy storage devices due to their high power and long cycle life. In order to developed an advanced device with significant capacity for storing charge and cheap carbon materials, efforts must focus not only on improving synthesis by controlling the morphology and pore size but also on improving electrode-electrolyte compatibility of the resulting systems. The present study examines the relationship between the surface chemistry of two activated carbon xerogels, the electrolyte type, and the electrochemical properties of supercapacitors. Activated carbon xerogels were prepared by varying the initial pH of the resorcinol-formaldehyde aqueous solution. The materials produced are physicochemical characterized by DTA/TGA, porous characterization, and SEM analysis. The carbon xerogel based electrodes were prepared by spreading over glass plate a slurry containing the carbon gel, graphite, and poly vinylidene difluoride (PVDF) binder. The layer formed was dried consecutively at different temperatures and then detached by water. After, the layer was dried again to improve its mechanical stability. The developed electrode materials and the Aquivion® E87-05S membrane (Solvay Specialty Polymers), socked in Na2SO4 as a polymer electrolyte, were used to assembly the solid-state supercapacitor. Symmetric supercapacitor cells composed by same electrodes and 1 M KOH electrolytes are also assembled and tested for comparison. The supercapacitor performances are verified by different electrochemical methods - cyclic voltammetry, galvanostatic charge/discharge measurements, electrochemical impedance spectroscopy, and long-term durability tests in neutral and alkaline electrolytes. Specific capacitances, energy, and power density, energy efficiencies, and durability were compared into studied supercapacitors. Ex-situ physicochemical analyses on the synthesized materials have also been performed, which provide information about chemical and structural changes in the electrode morphology during charge / discharge durability tests. They are discussed on the basis of electrode-electrolyte interaction. The obtained correlations could be of significance in order to design sustainable solid-state supercapacitors with high power and energy density. Acknowledgement: This research is funded by the Ministry of Education and Science of Bulgaria under the National Program "European Scientific Networks" (Agreement D01-286 / 07.10.2020, D01-78/30.03.2021). Authors gratefully acknowledge.

Keywords: carbon xerogel, electrochemical tests, neutral and alkaline electrolytes, supercapacitors

Procedia PDF Downloads 137

Authors: Mustafa M. Donma, Orkide Donma

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The examination of both serum lipid fractions and body’s lipid composition are quite informative during the evaluation of obesity stages. Within this context, alterations in lipid parameters are commonly observed. The variations in the fat distribution of the body are also noteworthy. Total cholesterol (TC), triglycerides (TRG), low density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol (HDL-C) are considered as the basic lipid fractions. Fat deposited in trunk and extremities may give considerable amount of information and different messages during discrete health states. Ratios are also derived from distinct fat distribution in these areas. Trunk-to-leg fat ratio (TLFR) and trunk-to-appendicular fat ratio (TAFR) are the most recently introduced ratios. In this study, lipid fractions and TLFR, as well as TAFR, were evaluated, and the distinctions among healthy, obese (OB), and morbid obese (MO) groups were investigated. Three groups [normal body mass index (N-BMI), OB, MO] were constituted from a population aged 6 to 18 years. Ages and sexes of the groups were matched. The study protocol was approved by the Non-interventional Ethics Committee of Tekirdag Namik Kemal University. Written informed consent forms were obtained from the parents of the participants. Anthropometric measurements (height, weight, waist circumference, hip circumference, head circumference, neck circumference) were obtained and recorded during the physical examination. Body mass index values were calculated. Total, trunk, leg, and arm fat mass values were obtained by TANITA Bioelectrical Impedance Analysis. These values were used to calculate TLFR and TAFR. Systolic (SBP) and diastolic blood pressures (DBP) were measured. Routine biochemical tests including TC, TRG, LDL-C, HDL-C, and insulin were performed. Data were evaluated using SPSS software. p value smaller than 0.05 was accepted as statistically significant. There was no difference among the age values and gender ratios of the groups. Any statistically significant difference was not observed in terms of DBP, TLFR as well as serum lipid fractions. Higher SBP values were measured both in OB and MO children than those with N-BMI. TAFR showed a significant difference between N-BMI and OB groups. Statistically significant increases were detected between insulin values of N-BMI group and OB as well as MO groups. There were bivariate correlations between LDL and TLFR (r=0.396; p=0.037) as well as TAFR values (r=0.413; p=0.029) in MO group. When adjusted for SBP and DBP, partial correlations were calculated as (r=0.421; p=0.032) and (r=0.438; p=0.025) for LDL-TLFR as well as LDL-TAFR, respectively. Much stronger partial correlations were obtained for the same couples (r=0.475; p=0.019 and r=0.473; p=0.020, respectively) upon controlling for TRG and HDL-C. Much stronger partial correlations observed in MO children emphasize the potential transition from morbid obesity to metabolic syndrome. These findings have concluded that LDL-C may be suggested as a discriminating parameter between OB and MO children.

Keywords: children, lipid parameters, obesity, trunk-to-leg fat ratio, trunk-to-appendicular fat ratio

Procedia PDF Downloads 112

Authors: Hilal Köse, Şeyma Dombaycıoğlu, Ali Osman Aydın, Hatem Akbulut

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Rechargeable lithium-ion batteries (LIBs) have become promising power sources for a wide range of applications, such as mobile communication devices, portable electronic devices and electrical/hybrid vehicles due to their long cycle life, high voltage and high energy density. Graphite, as anode material, has been widely used owing to its extraordinary electronic transport properties, large surface area, and high electrocatalytic activities although its limited specific capacity (372 mAh g-1) cannot fulfil the increasing demand for lithium-ion batteries with higher energy density. To settle this problem, many studies have been taken into consideration to investigate new electrode materials and metal oxide/graphene composites are selected as a kind of promising material for lithium ion batteries as their specific capacities are much higher than graphene. Among them, SnO₂, an n-type and wide band gap semiconductor, has attracted much attention as an anode material for the new-generation lithium-ion batteries with its high theoretical capacity (790 mAh g-1). However, it suffers from large volume changes and agglomeration associated with the Li-ion insertion and extraction processes, which brings about failure and loss of electrical contact of the anode. In addition, there is also a huge irreversible capacity during the first cycle due to the formation of amorphous Li₂O matrix. To obtain high capacity anode materials, we studied on the synthesis and characterization of SnO₂-Graphene nanocomposites and investigated the capacity of this free-standing anode material in this work. For this aim, firstly, graphite oxide was obtained from graphite powder using the method described by Hummers method. To prepare the nanocomposites as free-standing anode, graphite oxide particles were ultrasonicated in distilled water with SnO2 nanoparticles (1:1, w/w). After vacuum filtration, the GO-SnO₂ paper was peeled off from the PVDF membrane to obtain a flexible, free-standing GO paper. Then, GO structure was reduced in hydrazine solution. Produced SnO2- graphene nanocomposites were characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectrometer (EDS), and X-ray diffraction (XRD) analyses. CR2016 cells were assembled in a glove box (MBraun-Labstar). The cells were charged and discharged at 25°C between fixed voltage limits (2.5 V to 0.2 V) at a constant current density on a BST8-MA MTI model battery tester with 0.2C charge-discharge rate. Cyclic voltammetry (CV) was performed at the scan rate of 0.1 mVs-1 and electrochemical impedance spectroscopy (EIS) measurements were carried out using Gamry Instrument applying a sine wave of 10 mV amplitude over a frequency range of 1000 kHz-0.01 Hz.

Keywords: SnO₂-graphene, nanocomposite, anode, Li-ion battery

Procedia PDF Downloads 228

Authors: Adamantini Loukodimou, David Weston, Shiladitya Paul

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Offshore structures are subjected to harsh environments. It is documented that carbon steel needs protection from corrosion. The combined effect of UV radiation, seawater splash, and fluctuating temperatures diminish the integrity of these structures. In addition, the possibility of damage caused by floating ice, seaborne debris, and maintenance boats make them even more vulnerable. Their inspection and maintenance when far out in the sea are difficult, risky, and expensive. The most known method of mitigating corrosion of offshore structures is the use of cathodic protection. There are several zones in an offshore wind turbine. In the atmospheric zone, due to the lack of a continuous electrolyte (seawater) layer between the structure and the anode at all times, this method proves inefficient. Thus, the use of protective coatings becomes indispensable. This research focuses on the atmospheric zone. The conversion of commercially available and conventional paint (epoxy) system to an autonomous self-healing paint system via the addition of suitable encapsulated healing agents and catalyst is investigated in this work. These coating systems, which can self-heal when damaged, can provide a cost-effective engineering solution to corrosion and related problems. When the damage of the paint coating occurs, the microcapsules are designed to rupture and release the self-healing liquid (monomer), which then will react in the presence of the catalyst and solidify (polymerization), resulting in healing. The catalyst should be compatible with the system because otherwise, the self-healing process will not occur. The carbon steel substrate will be exposed to a corrosive environment, so the use of a sacrificial layer of Zn is also investigated. More specifically, the first layer of this new coating system will be TSZA (Thermally Sprayed Zn85/Al15) and will be applied on carbon steel samples with dimensions 100 x 150 mm after being blasted with alumina (size F24) as part of the surface preparation. Based on the literature, it corrodes readily, so one additional paint layer enriched with microcapsules will be added. Also, the reaction and the curing time are of high importance in order for this bilayer system of coating to work successfully. For the first experiments, polystyrene microcapsules loaded with 3-octanoyltio-1-propyltriethoxysilane were conducted. Electrochemical experiments such as Electrochemical Impedance Spectroscopy (EIS) confirmed the corrosion inhibiting properties of the silane. The diameter of the microcapsules was about 150-200 microns. Further experiments were conducted with different reagents and methods in order to obtain diameters of about 50 microns, and their self-healing properties were tested in synthetic seawater using electrochemical techniques. The use of combined paint/electrodeposited coatings allows for further novel development of composite coating systems. The potential for the application of these coatings in offshore structures will be discussed.

Keywords: corrosion mitigation, microcapsules, offshore wind turbines, self-healing

Procedia PDF Downloads 115

Authors: Peter Kus, Anna Ostroverkh, Yurii Yakovlev, Yevheniia Lobko, Roman Fiala, Ivan Khalakhan, Vladimir Matolin

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Hydrogen economy is a concept of low-emission society which harvests most of its energy from renewable sources (e.g., wind and solar) and in case of overproduction, electrochemically turns the excess amount into hydrogen, which serves as an energy carrier. Proton exchange membrane water electrolyzers (PEMWE) are the backbone of this concept. By fast-response electricity to hydrogen conversion, the PEMWEs will not only stabilize the electrical grid but also provide high-purity hydrogen for variety of fuel cell powered devices, ranging from consumer electronics to vehicles. Wider commercialization of PEMWE technology is however hindered by high prices of noble metals which are necessary for catalyzing the redox reactions within the cell. Namely, platinum for hydrogen evolution reaction (HER), running on cathode, and iridium for oxygen evolution reaction (OER) on anode. Possible way of how to lower the loading of Pt and Ir is by using conductive high-surface nanostructures as catalyst supports in conjunction with thin-film catalyst deposition. The presented study discusses unconventional technique of membrane electron assembly (MEA) preparation. Noble metal catalysts (Pt and Ir) were magnetron sputtered in very low loadings onto the surface of porous sublayers (located on gas diffusion layer or directly on membrane), forming so to say localized three-phase boundary. Ultrasonically sprayed corrosion resistant TiC-based sublayer was used as a support material on anode, whereas magnetron sputtered nanostructured etched nitrogenated carbon (CNx) served the same role on cathode. By using this configuration, we were able to significantly decrease the amount of noble metals (to thickness of just tens of nanometers), while keeping the performance comparable to that of average state-of-the-art catalysts. Complex characterization of prepared supported catalysts includes in-cell performance and durability tests, electrochemical impedance spectroscopy (EIS) as well as scanning electron microscopy (SEM) imaging and X-ray photoelectron spectroscopy (XPS) analysis. Our research proves that magnetron sputtering is a suitable method for thin-film deposition of electrocatalysts. Tested set-up of thin-film supported anode and cathode catalysts with combined loading of just 120 ug.cm⁻² yields remarkable values of specific current. Described approach of thin-film low-loading catalyst deposition might be relevant when noble metal reduction is the topmost priority.

Keywords: hydrogen economy, low-loading catalyst, magnetron sputtering, proton exchange membrane water electrolyzer

Procedia PDF Downloads 163

Authors: Preethi Kumari P., Shetty Prakasha, Rao Suma A.

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Mild steel has been widely employed as construction materials for pipe work in the oil and gas production such as down hole tubular, flow lines and transmission pipelines, in chemical and allied industries for handling acids, alkalis and salt solutions due to its excellent mechanical property and low cost. Acid solutions are widely used for removal of undesirable scale and rust in many industrial processes. Among the commercially available acids hydrochloric acid is widely used for pickling, cleaning, de-scaling and acidization of oil process. Mild steel exhibits poor corrosion resistance in presence of hydrochloric acid. The high reactivity of mild steel in presence of hydrochloric acid is due to the soluble nature of ferrous chloride formed and the cementite phase (Fe3C) normally present in the steel is also readily soluble in hydrochloric acid. Pitting attack is also reported to be a major form of corrosion in mild steel in the presence of high concentrations of acids and thereby causing the complete destruction of metal. Hydrogen from acid reacts with the metal surface and makes it brittle and causes cracks, which leads to pitting type of corrosion. The use of chemical inhibitor to minimize the rate of corrosion has been considered to be the first line of defense against corrosion. In spite of long history of corrosion inhibition, a highly efficient and durable inhibitor that can completely protect mild steel in aggressive environment is yet to be realized. It is clear from the literature review that there is ample scope for the development of new organic inhibitors, which can be conveniently synthesized from relatively cheap raw materials and provide good inhibition efficiency with least risk of environmental pollution. The aim of the present work is to evaluate the electrochemical parameters for the corrosion inhibition behavior of an aromatic hydrazide derivative, 4-hydroxy- N '-[(E)-1H-indole-2-ylmethylidene)] benzohydrazide (HIBH) on mild steel in 2M hydrochloric acid using Tafel polarization and electrochemical impedance spectroscopy (EIS) techniques at 30-60 °C. The results showed that inhibition efficiency increased with increase in inhibitor concentration and decreased marginally with increase in temperature. HIBH showed a maximum inhibition efficiency of 95 % at 8×10-4 M concentration at 30 °C. Polarization curves showed that HIBH act as a mixed-type inhibitor. The adsorption of HIBH on mild steel surface obeys the Langmuir adsorption isotherm. The adsorption process of HIBH at the mild steel/hydrochloric acid solution interface followed mixed adsorption with predominantly physisorption at lower temperature and chemisorption at higher temperature. Thermodynamic parameters for the adsorption process and kinetic parameters for the metal dissolution reaction were determined.

Keywords: electrochemical parameters, EIS, mild steel, tafel polarization

Procedia PDF Downloads 337

Authors: Solanki Ravirajsinh

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In the software testing life cycle, failing to conduct thorough performance testing can result in significant losses for an organization due to application crashes and improper behavior under high user loads in production. Simulating large volumes of requests, such as 5 million within 5-10 minutes, is challenging without a scalable performance testing framework. Leveraging cloud services to implement a performance testing framework makes it feasible to handle 5-10 million requests in just 5-10 minutes, helping organizations ensure their applications perform reliably under peak conditions. Implementing a scalable performance testing framework using cloud services and tools like JMeter, EC2 instances (Virtual machine), cloud logs (Monitor errors and logs), EFS (File storage system), and security groups offers several key benefits for organizations. Creating performance test framework using this approach helps optimize resource utilization, effective benchmarking, increased reliability, cost savings by resolving performance issues before the application is released. In performance testing, a master-slave framework facilitates distributed testing across multiple EC2 instances to emulate many concurrent users and efficiently handle high loads. The master node orchestrates the test execution by coordinating with multiple slave nodes to distribute the workload. Slave nodes execute the test scripts provided by the master node, with each node handling a portion of the overall user load and generating requests to the target application or service. By leveraging JMeter's master-slave framework in conjunction with cloud services like EC2 instances, EFS, CloudWatch logs, security groups, and command-line tools, organizations can achieve superior scalability and flexibility in their performance testing efforts. In this master-slave framework, JMeter must be installed on both the master and each slave EC2 instance. The master EC2 instance functions as the "brain," while the slave instances operate as the "body parts." The master directs each slave to execute a specified number of requests. Upon completion of the execution, the slave instances transmit their results back to the master. The master then consolidates these results into a comprehensive report detailing metrics such as the number of requests sent, encountered errors, network latency, response times, server capacity, throughput, and bandwidth. Leveraging cloud services, the framework benefits from automatic scaling based on the volume of requests. Notably, integrating cloud services allows organizations to handle more than 5-10 million requests within 5 minutes, depending on the server capacity of the hosted website or application.

Keywords: identify crashes of application under heavy load, JMeter with cloud Services, Scalable performance testing, JMeter master and slave using cloud Services

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Authors: Tiffany Baetens, Sophie Halliez, Luc Buée, Emiliano Pallecchi, Vincent Thomy, Steve Arscott

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We demonstrate here a viable stretchable bio-microelectromechanical systems (BioMEMS) technology for use with biological studies concerned with the effect of high mechanical strains on living cells. An example of this is traumatic brain injury (TBI) where neurons are damaged with physical force to the brain during, e.g., accidents and sports. Robust, miniaturized integrated systems are needed by biologists to be able to study the effect of TBI on neuron cells in vitro. The major challenges in this area are (i) to develop micro, and nanofabrication processes which are based on stretchable substrates and to (ii) create systems which are robust and performant at very high mechanical strain values—sometimes as high as 100%. At the time of writing, such processes and systems were rapidly evolving subject of research and development. The BioMEMS which we present here is composed of an elastomer substrate (low Young’s modulus ~1 MPa) onto which is patterned robust electrodes and insulators. The patterning of the thin films is achieved using standard photolithography techniques directly on the elastomer substrate—thus making the process generic and applicable to many materials’ in based systems. The chosen elastomer used is commercial ‘Sylgard 184’ polydimethylsiloxane (PDMS). It is spin-coated onto a silicon wafer. Multistep ultra-violet based photolithography involving commercial photoresists are then used to pattern robust thin film metallic electrodes (chromium/gold) and insulating layers (parylene) on the top of the PDMS substrate. The thin film metals are deposited using thermal evaporation and shaped using lift-off techniques The BioMEMS has been characterized mechanically using an in-house strain-applicator tool. The system is composed of 12 electrodes with one reference electrode transversally-orientated to the uniaxial longitudinal straining of the system. The electrical resistance of the electrodes is observed to remain very stable with applied strain—with a resistivity approaching that of evaporated gold—up to an interline strain of ~50%. The mechanical characterization revealed some interesting original properties of such stretchable BioMEMS. For example, a Poisson effect induced electrical ‘self-healing’ of cracking was identified. Biocompatibility of the commercial photoresist has been studied and is conclusive. We will present the results of the BioMEMS, which has also characterized living cells with a commercial Multi Electrode Array (MEA) characterization tool (Multi Channel Systems, USA). The BioMEMS enables the cells to be strained up to 50% and then characterized electrically and optically.

Keywords: BioMEMS, elastomer, electrical impedance measurements of living cells, high mechanical strain, microfabrication, stretchable systems, thin films, traumatic brain injury

Procedia PDF Downloads 146

Authors: Mustafa M. Donma, Orkide Donma, Murat Aydin, Muhammet Demirkol, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

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Childhood obesity is an ever increasing global health problem, affecting both developed and developing countries. Accurate evaluation of obesity in children requires difficult and detailed investigation. In our study, obesity in children was evaluated using new body fat ratios and indices. Assessment of anthropometric measurements, as well as some ratios, is important because of the evaluation of gender differences particularly during the late periods of obesity. A total of 239 children; 168 morbid obese (MO) (81 girls and 87 boys) and 71 normal weight (NW) (40 girls and 31 boys) children, participated in the study. Informed consent forms signed by the parents were obtained. Ethics Committee approved the study protocol. Mean ages (years)±SD calculated for MO group were 10.8±2.9 years in girls and 10.1±2.4 years in boys. The corresponding values for NW group were 9.0±2.0 years in girls and 9.2±2.1 years in boys. Mean body mass index (BMI)±SD values for MO group were 29.1±5.4 kg/m² and 27.2±3.9 kg/m² in girls and boys, respectively. These values for NW group were calculated as 15.5±1.0 kg/m² in girls and 15.9±1.1 kg/m² in boys. Groups were constituted based upon BMI percentiles for age-and-sex values recommended by WHO. Children with percentiles >99 were grouped as MO and children with percentiles between 85 and 15 were considered NW. The anthropometric measurements were recorded and evaluated along with the new ratios such as trunk-to-appendicular fat ratio, as well as indices such as Index-I and Index-II. The body fat percent values were obtained by bio-electrical impedance analysis. Data were entered into a database for analysis using SPSS/PASW 18 Statistics for Windows statistical software. Increased waist-to-hip circumference (C) ratios, decreased head-to-neck C, height ‘to’ ‘two’-‘to’-waist C and height ‘to’ ‘two’-‘to’-hip C ratios were observed in parallel with the development of obesity (p≤0.001). Reference value for height ‘to’ ‘two’-‘to’-hip ratio was detected as approximately 1.0. Index-II, based upon total body fat mass, showed much more significant differences between the groups than Index-I based upon weight. There was not any difference between trunk-to-appendicular fat ratios of NW girls and NW boys (p≥0.05). However, significantly increased values for MO girls in comparison with MO boys were observed (p≤0.05). This parameter showed no difference between NW and MO states in boys (p≥0.05). However, statistically significant increase was noted in MO girls compared to their NW states (p≤0.001). Trunk-to-appendicular fat ratio was the only fat-based parameter, which showed gender difference between NW and MO groups. This study has revealed that body ratios and formula based upon body fat tissue are more valuable parameters than those based on weight and height values for the evaluation of morbid obesity in children.

Keywords: anthropometry, childhood obesity, gender, morbid obesity

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Authors: Mattias Bergstrom

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Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

Procedia PDF Downloads 107

Authors: Adinew Gebremeskel Tizazu

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The effect of soil-structure interaction on the dynamic response of reinforced concrete buildings of regular and symmetrical geometry are considered in this study. The structures are presumed to be generally embedded in a homogenous soil formation underlain by very stiff material or bedrock. The structure-foundation–soil system is excited at the base by an earthquake ground motion. The superstructure is idealized as a system with lumped masses concentrated at the floor levels, and coupled with the substructure. The substructure system, which comprises of the foundation and soil, is represented, and replaced by springs and dashpots. Frequency-dependent impedances of the foundation system are incorporated in the discrete model in terms of the springs and dashpots coefficients. The excitation applied to the model is field ground motions of actual earthquake records. Modal superposition principle is employed to transform the equations of motion in geometrical coordinates to modal coordinates. However, the modal equations remain coupled with respect to damping terms due to the difference in damping mechanisms of the superstructure and the soil. Hence, proportional damping for the coupled structural system may not be assumed. An iterative approach is adopted and programmed to solve the system of coupled equations of motion in modal coordinates to obtain the displacement responses of the system. Parametric studies for responses of building structures with regular and symmetric plans of different structural properties and heights are made for fixed and flexible base conditions, for different soil conditions encountered in Addis Ababa. The displacement, base shear and base overturning moments are used in the comparison of different types of structures for various foundation embedment depths, site conditions and height of structures. These values are compared against those of fixed base structure. The study shows that the flexible base structures, generally exhibit different responses from those structures with fixed base. Basically, the natural circular frequencies, the base shears and the inter-story displacements for the flexible base are less than those of the fixed base structures. This trend is particularly evident when the flexible soil has large thickness. In contrast, the trend becomes less predictable, when the thickness of the flexible soil decreases. Moreover, in the latter case, the iteration undulates significantly making the prediction difficult. This is attributed to the highly jagged nature of the impedance functions of frequencies for such formations. In this case, it is difficult to conclude whether the conventional fixed-base approach yields conservative design forces, as is the case for soil formations of large thickness.

Keywords: effect of soil structure, dynamic response corroborated, the modal superposition principle, parametric studies

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Authors: Mustafa M. Donma, Orkide Donma

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Metabolisms of macrominerals, those of calcium, phosphorus and magnesium, are closely associated with the metabolism of vitamin D. Particularly magnesium, the second most abundant intracellular cation, is related to biochemical and metabolic processes in the body, such as those of carbohydrates, proteins and lipids. The status of each mineral was investigated in obesity to some extent. Their products and ratios may possibly give much more detailed information about the matter. The aim of this study is to investigate possible relations between each macromineral and some obesity-related parameters. This study was performed on 235 children, whose ages were between 06-18 years. Aside from anthropometric measurements, hematological analyses were performed. TANITA body composition monitor using bioelectrical impedance analysis technology was used to establish some obesity-related parameters including basal metabolic rate (BMR), total fat, mineral and muscle masses. World Health Organization body mass index (BMI) percentiles for age and sex were used to constitute the groups. The values above 99^th percentile were defined as morbid obesity. Those between 95^th and 99^th percentiles were included into the obese group. The overweight group comprised of children whose percentiles were between 95 and 85. Children between the 85^th and 15^th percentiles were defined as normal. Metabolic syndrome (MetS) components (waist circumference, fasting blood glucose, triacylglycerol, high density lipoprotein cholesterol, systolic pressure, diastolic pressure) were determined. High performance liquid chromatography was used to determine Vitamin D status by measuring 25-hydroxy cholecalciferol (25-hydroxy vitamin D₃, 25(OH)D). Vitamin D values above 30.0 ng/ml were accepted as sufficient. SPSS statistical package program was used for the evaluation of data. The statistical significance degree was accepted as p < 0.05. The important points were the correlations found between vitamin D and magnesium as well as phosphorus (p < 0.05) that existed in the group with normal BMI values. These correlations were lost in the other groups. The ratio of phosphorus to magnesium was even much more highly correlated with vitamin D (p < 0.001). The negative correlation between magnesium and total fat mass (p < 0.01) was confined to the MetS group showing the inverse relationship between magnesium levels and obesity degree. In this group, calcium*magnesium product exhibited the highest correlation with total fat mass (p < 0.001) among all groups. Only in the MetS group was a negative correlation found between BMR and calcium*magnesium product (p < 0.05). In conclusion, magnesium is located at the center of attraction concerning its relationships with vitamin D, fat mass and MetS. The ratios and products derived from macrominerals including magnesium have pointed out stronger associations other than each element alone. Final considerations have shown that unique correlations of magnesium as well as calcium*magnesium product with total fat mass have drawn attention particularly in the MetS group, possibly due to the derangements in some basic elements of carbohydrate as well as lipid metabolism.

Keywords: macrominerals, metabolic syndrome, pediatric obesity, vitamin D

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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: Soumyadeep Bhaduri, Rahul Ghosh, Rahul Shukla, Manaswini Behera

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The textile industry consumes a substantial amount of water throughout the processing and production of textile fabrics. The water eventually turns into wastewater, where it acts as an immense damaging nuisance due to its dye content. Wastewater streams contain a percentage ranging from 2.0% to 50.0% of the total weight of dye used, depending on the dye class. The management of dye effluent in textile industries presents a formidable challenge to global sustainability. The current focus is on implementing wastewater treatment technology that enable the recycling of wastewater, reduce energy usage and offset carbon emissions. Microbial fuel cell (MFC) is a device that utilizes microorganisms as a bio-catalyst to effectively treat wastewater while also producing electricity. The MFC harnesses the chemical energy present in wastewater by oxidizing organic compounds in the anodic chamber and reducing an electron acceptor in the cathodic chamber, thereby generating electricity. This research investigates the potential of MFCs to tackle this challenge of azo dye removal with simultaneously generating electricity. Although MFCs are well-established for wastewater treatment, their application in dye decolorization with concurrent electricity generation remains relatively unexplored. This study aims to address this gap by assessing the effectiveness of MFCs as a sustainable solution for treating wastewater containing azo dyes. By harnessing microorganisms as biocatalysts, MFCs offer a promising avenue for environmentally friendly dye effluent management. The performance of MFCs in treating azo dyes and generating electricity was evaluated by optimizing the Chemical Oxygen Demand (COD) and Hydraulic Retention Time (HRT) of influent. COD and HRT values ranged from 1600 mg/L to 2400 mg/L and 5 to 9 days, respectively. Results showed that the maximum open circuit voltage (OCV) reached 648 mV at a COD of 2400 mg/L and HRT of 5 days. Additionally, maximum COD removal of 98% and maximum color removal of 98.91% were achieved at a COD of 1600 mg/L and HRT of 9 days. Furthermore, the study observed a maximum power density of 19.95 W/m3 at a COD of 2400 mg/L and HRT of 5 days. Electrochemical analysis, including linear sweep voltammetry (LSV), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were done to find out the response current and internal resistance of the system. To optimize pH and dye concentration, pH values were varied from 4 to 10, and dye concentrations ranged from 25 mg/L to 175 mg/L. The highest voltage output of 704 mV was recorded at pH 7, while a dye concentration of 100 mg/L yielded the maximum output of 672 mV. This study demonstrates that MFCs offer an efficient and sustainable solution for treating azo dyes in textile industry wastewater, while concurrently generating electricity. These findings suggest the potential of MFCs to contribute to environmental remediation and sustainable development efforts on a global scale.

Keywords: textile wastewater treatment, microbial fuel cell, renewable energy, sustainable wastewater treatment

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Authors: Neoclis Hadjigeorgiou, Spyridon Angelopoulos, Evangelos V. Hristoforou, Paul P. Sotiriadis

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The increasing demand for accurate and reliable magnetic measurements over the past decades has paved the way for the development of different types of magnetic sensing systems as well as of more advanced measurement techniques. Anisotropic Magneto Resistance (AMR) sensors have emerged as a promising solution for applications requiring high resolution, providing an ideal balance between performance and cost. However, certain issues of AMR sensors such as non-linear response and measurement noise are rarely discussed in the relevant literature. In this work, an analog closed loop compensation system is proposed, developed and tested as a means to eliminate the non-linearity of AMR response, reduce the 1/f noise and enhance the sensitivity of magnetic sensor. Additional performance aspects, such as cross-axis and hysteresis effects are also examined. This system was analyzed using an analytical model and a P-Spice model, considering both the sensor itself as well as the accompanying electronic circuitry. In addition, a commercial closed loop architecture Flux-Gate sensor (calibrated and certified), has been used for comparison purposes. Three different experimental setups have been constructed for the purposes of this work, each one utilized for DC magnetic field measurements, AC magnetic field measurements and Noise density measurements respectively. The DC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to calibrate and characterize the system under consideration. A high-accuracy DC power supply has been used for providing the operating current to the Helmholtz coils. The results were recorded by a multichannel voltmeter The AC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to examine the effective bandwidth not only of the proposed system but also for the Flux-Gate sensor. A voltage controlled current source driven by a function generator has been utilized for the Helmholtz coil excitation. The result was observed by the oscilloscope. The third experimental apparatus incorporated an AC magnetic shielding construction composed of several layers of electric steel that had been demagnetized prior to the experimental process. Each sensor was placed alone and the response was captured by the oscilloscope. The preliminary experimental results indicate that closed loop AMR response presented a maximum deviation of 0.36% with respect to the ideal linear response, while the corresponding values for the open loop AMR system and the Fluxgate sensor reached 2% and 0.01% respectively. Moreover, the noise density of the proposed close loop AMR sensor system remained almost as low as the noise density of the AMR sensor itself, yet considerably higher than that of the Flux-Gate sensor. All relevant numerical data are presented in the paper.

Keywords: AMR sensor, chopper, closed loop, electronic noise, magnetic noise, memory effects, flux-gate sensor, linearity improvement, sensitivity improvement

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Authors: Stephen Kyakulumbye, Vivian Kobusingye

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Generally, World over, COVID-19 has had adverse effects on all sectors but with more debilitating effects on the education sector. After reactive lockdowns, education institutions that could continue teaching and learning had to go a distance mediated by digital technological tools. In Uganda, the Ministry of Education thereby issued COVID-19 Online Distance E-learning (ODeL) emergent guidelines. Despite such guidelines, academic institutions in Uganda and similar developing contexts with academically constrained resource environments were caught off-guard and ill-prepared to transform from face-to-face learning to online distance learning mode. Most academic institutions that migrated spontaneously did so with no deliberate tools, systems, strategies, or software to cause active, meaningful, and engaging learning for students. By experience, most of these academic institutions shifted to Zoom and WhatsApp and instead conducted online teaching in real-time than blended synchronous and asynchronous tools. This paper provides students’ experiences while blending synchronous and asynchronous content-creating and learning tools within a technological resource-constrained environment to navigate in such a challenging Uganda context. These conceptual case-based findings, using experience from Uganda Christian University (UCU), point at the design of learning activities with two certain characteristics, the enhancement of synchronous learning technologies with asynchronous ones to mitigate the challenge of system breakdown, passive learning to active learning, and enhances the types of presence (social, cognitive and facilitatory). The paper, both empirical and experiential in nature, uses online experiences from third-year students in Bachelor of Business Administration student lectured using asynchronous text, audio, and video created with Open Broadcaster Studio software and compressed with Handbrake, all open-source software to mitigate disk space and bandwidth usage challenges. The synchronous online engagements with students were a blend of zoom or BigBlueButton, to ensure that students had an alternative just in case one failed due to excessive real-time traffic. Generally, students report that compared to their previous face-to-face lectures, the pre-recorded lectures via Youtube provided them an opportunity to reflect on content in a self-paced manner, which later on enabled them to engage actively during the live zoom and/or BigBlueButton real-time discussions and presentations. The major recommendation is that lecturers and teachers in a resource-constrained environment with limited digital resources like the internet and digital devices should harness this approach to offer students access to learning content in a self-paced manner and thereby enabling reflective active learning through reflective and high-order thinking.

Keywords: synchronous learning, asynchronous learning, active learning, reflective learning, resource-constrained environment

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Authors: Mustafa Metin Donma

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Metabolic syndrome (MetS) is characterized by a series of biochemical, physiological and anthropometric indicators and is a life-threatening health problem due to its close association with chronic diseases such as diabetes mellitus, hypertension, cancer and cardiovascular diseases. The syndrome deserves great interest both in adults and children. Central obesity is the indispensable component of MetS. Particularly, children, who are morbidly obese have a great tendency to develop the disease, because they are under the threat in their future lives. Preventive measures at this stage should be considered. For this, investigators seek for an informative scale or an index for the purpose. So far, several, but not many suggestions come into the stage. However, the diagnostic decision is not so easy and may not be complete particularly in the pediatric population. The aim of the study was to develop a MetS index capable of predicting MetS, while children are at the morbid obesity stage. This study was performed on morbid obese (MO) children, which were divided into two groups. Morbid obese children, who do not possess MetS criteria comprised the first group (n=44). The second group was composed of children (n=42) with MetS diagnosis. Parents were informed about the signed consent forms, which are required for the participation of their children in the study. The approval of the study protocol was taken from the institutional ethics committee of Tekirdag Namik Kemal University. Helsinki Declaration was accepted prior to and during the study. Anthropometric measurements including weight, height, waist circumference (WC), hip C, head C, neck C, biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein cholesterol (HDL-C) and blood pressure measurements (systolic (SBP) and diastolic (DBP)) were performed. Body fat percentage (BFP) values were determined by TANITA’s Bioelectrical Impedance Analysis technology. Body mass index and MetS indices were calculated. The equations for MetS index (MetSI) and advanced Donma MetS index (ADMI) were [(INS/FBG)/(HDL-C/TRG)]*100 and MetSI*[(SBP+DBP/Height)], respectively. Descriptive statistics including median values, compare means tests, correlation-regression analysis were performed within the scope of data evaluation using the statistical package program, SPSS. Statistically significant mean differences were determined by a p value smaller than 0.05. Median values for MetSI and ADMI in MO (MetS-) and MO (MetS+) groups were calculated as (25.9 and 36.5) and (74.0 and 106.1), respectively. Corresponding mean±SD values for BFPs were 35.9±7.1 and 38.2±7.7 in groups. Correlation analysis of these two indices with corresponding general BFP values exhibited significant association with ADMI, close to significance with MetSI in MO group. Any significant correlation was found with neither of the indices in MetS group. In conclusion, important associations observed with MetS indices in MO group were quite meaningful. The presence of these associations in MO group was important for showing the tendency towards the development of MetS in MO (MetS-) participants. The other index, ADMI, was more helpful for predictive purpose.

Keywords: body fat percentage, child, index, metabolic syndrome, obesity

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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: Cyril O. Ehi-Eromosele, Ajayi Kayode

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The Li-rich layered metal oxides (LLO) are the most promising candidates for promising electrodes of high energy Li-ion battery (LIB). In literature, these electrode system has either been designed as a hetero-structure of the primary components (composite) or as a core-shell structure with improved electrochemistry reported for both configurations when compared with its primary components. With the on-going efforts to improve on the electrochemical performance of the LIB, it is important to investigate comparatively the structural and electrochemical characteristics of the core-shell like and ‘composite’ forms of these materials with the same compositions and synthesis conditions which could influence future engineering of these materials. Therefore, this study concerns the structural and electrochemical properties of the ‘composite’ and core-shell like LLO cathode materials with the same nominal composition of 0.5Li₂MnO₃-0.5LiNi₀.₅Mn₀.₃Co₀.₂O₂ (LiNi₀.₅Mn₀.₃Co₀.₂O₂ as core and Li₂MnO₃ as the shell). The results show that the core-shell sample (–CS) gave better electrochemical performance than the ‘composite’ sample (–C). Both samples gave the same initial charge capacity of ~300 mAh/g when cycled at 10 mA/g and comparable charge capacity (246 mAh/g for the –CS sample and 240 mAh/g for the –C sample) when cycled at 200 mA/g. However, the –CS sample gave a higher initial discharge capacity at both current densities. The discharge capacity of the –CS sample was 232 mAh/g and 164 mAh/g while the –C sample is 208 mAh/g and 143 mAh/g at the current densities of 10 mA/g and 200 mA/g, respectively. Electrochemical impedance spectroscopy (EIS) results show that the –CS sample generally exhibited a smaller resistance than the –C sample both for the uncycled and after 50th cycle. Detailed structural analysis is on-going, but preliminary results show that the –CS sample had bigger unit cell volume and a higher degree of cation mixing. The thermal stability of the –CS sample was higher than the –C sample. XPS investigation also showed that the pristine –C sample gave a more reactive surface (showing formation of carbonate species to a greater degree) which could result in the greater resistance seen in the EIS result. To reinforce the results obtained for the 0.5Li₂MnO₃-0.5LiNi₀.₅Mn₀.₃Co₀.₃O₂ composition, the same investigations were extended to another ‘composite’ and core-shell like LLO cathode materials also with the same nominal composition of 0.5Li₂MnO₃-0.5LiNi₀.₃Mn₀.₃Co₀.₃O₂. In this case, the aim was to determine the electrochemical performance of the material using a low Ni content (LiNi₀.₃Mn₀.₃Co₀.₃O₂) as the core to clarify the contributions of the core-shell configuration to the electrochemical performance of these materials. Ni-rich layered oxides show active catalytic surface leading to electrolyte oxidation resulting in poor thermal stability and cycle life. Here, the core-shell sample also gave better electrochemical performance than the ‘composite’ sample with 0.5Li₂MnO₃-0.5LiNi₀.₃Mn₀.₃Co₀.₃O₂ composition. Furthermore, superior electrochemical performance was also recorded for the core-shell like spinel modified LLO (0.5Li₂MnO₃-0.45LiNi₀.₅Mn₀.₃Co₀.₂O₂-0.05LiNi₀.₅Mn₁.₅O₄) when compared to the composite system. These results show that the core-shell configuration can generally be used to improve the structural and electrochemical properties of the LLO and spinel modified LLO materials.

Keywords: lithium-ion battery, lithium rich oxide cathode, core-shell structure, composite structure

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Authors: Orkide Donma, Mustafa M. Donma, Muhammet Demirkol, Murat Aydin, Tuba Gokkus, Burcin Nalbantoglu, Aysin Nalbantoglu, Birol Topcu

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Obesity in childhood establishes a ground for adulthood obesity. Especially morbid obesity is an important problem for the children because of the associated diseases such as diabetes mellitus, cancer and cardiovascular diseases. In this study, body mass index (BMI), body fat ratios, anthropometric measurements and ratios were evaluated together with different laboratory indices upon evaluation of obesity in morbidly obese (MO) children. Children with nutritional problems participated in the study. Written informed consent was obtained from the parents. Study protocol was approved by the Ethics Committee. Sixty-two MO girls aged 129.5±35.8 months and 75 MO boys aged 120.1±26.6 months were included into the scope of the study. WHO-BMI percentiles for age-and-sex were used to assess the children with those higher than 99^th as morbid obesity. Anthropometric measurements of the children were recorded after their physical examination. Bio-electrical impedance analysis was performed to measure fat distribution. Anthropometric ratios, body fat ratios, Index-I and Index-II as well as insulin sensitivity indices (ISIs) were calculated. Girls as well as boys were binary grouped according to homeostasis model assessment-insulin resistance (HOMA-IR) index of <2.5 and >2.5, fasting glucose to insulin ratio (FGIR) of <6 and >6 and quantitative insulin sensitivity check index (QUICKI) of <0.33 and >0.33 as the frequently used cut-off points. They were evaluated based upon their BMIs, arms, legs, trunk, whole body fat percentages, body fat ratios such as fat mass index (FMI), trunk-to-appendicular fat ratio (TAFR), whole body fat ratio (WBFR), anthropometric measures and ratios [waist-to-hip, head-to-neck, thigh-to-arm, thigh-to-ankle, height/2-to-waist, height/2-to-hip circumference (C)]. SPSS/PASW 18 program was used for statistical analyses. p≤0.05 was accepted as statistically significance level. All of the fat percentages showed differences between below and above the specified cut-off points in girls when evaluated with HOMA-IR and QUICKI. Differences were observed only in arms fat percent for HOMA-IR and legs fat percent for QUICKI in boys (p≤ 0.05). FGIR was unable to detect any differences for the fat percentages of boys. Head-to-neck C was the only anthropometric ratio recommended to be used for all ISIs (p≤0.001 for both girls and boys in HOMA-IR, p≤0.001 for girls and p≤0.05 for boys in FGIR and QUICKI). Indices which are recommended for use in both genders were Index-I, Index-II, HOMA/BMI and log HOMA (p≤0.001). FMI was also a valuable index when evaluated with HOMA-IR and QUICKI (p≤0.001). The important point was the detection of the severe significance for HOMA/BMI and log HOMA while they were evaluated also with the other indices, FGIR and QUICKI (p≤0.001). These parameters along with Index-I were unique at this level of significance for all children. In conclusion, well-accepted ratios or indices may not be valid for the evaluation of both genders. This study has emphasized the limiting properties for boys. This is particularly important for the selection process of some ratios and/or indices during the clinical studies. Gender difference should be taken into consideration for the evaluation of the ratios or indices, which will be recommended to be used particularly within the scope of obesity studies.

Keywords: anthropometry, childhood obesity, gender, insulin sensitivity index

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Prescilla Lambert, Christophe Roos, Mounim Lebrini

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For several years, the Caribbean islands and West Africa have had to deal with the massive arrival of the brown seaweed Sargassum. Overall, this macroalgae, which constitutes a habitat for a great diversity of marine organisms, is also an additional stress factor for the marine environment (e.g., coral reefs). In addition, the accumulation followed by the significant decomposition of the Sargassum spp. biomass on the coast leads to the release of toxic gases (H₂S and NH₃), which calls into question the functioning of the economic, health and tourist life of the island and the other interested territories. Originally, these algae are formed by the eutrophication of the oceans accentuated by global warming. Unfortunately, scientists predict a significant recurrence of these Sargassum strandings for years to come. It is therefore more than necessary to find solutions by putting in place a sustainable management plan for this phenomenon. Martinique, a small island in the Caribbean arc, is one of the many areas impacted by Sargassum seaweed strandings. Since 2011, there has been a constant increase in the degradation of the materials present in this region, largely due to toxic/corrosive gases released by the algae decomposition. In order to protect the structures and the vulnerable building materials while limiting the use of synthetic/petroleum based molecules as much as possible, research is being conducted on molecules of natural origin. Thus, thanks to the chemical composition, which comprise molecules with interesting properties, algae such as Sargassum could potentially help to solve many issues. Therefore, this study focuses on the green extraction and characterization of molecules from the species Sargassum fluitans and Sargassum natans present in Martinique. The secondary metabolites found in these extracts showed variability in yield rates due to local climatic conditions. The tests carried out shed light on the anticorrosive and antibacterial potential of the algae. These extracts can thus be described as natural inhibitors. The effect of variation in inhibitor concentrations was tested in electrochemistry using electrochemical impedance spectroscopy and polarization curves. The analysis of electrochemical results obtained by direct immersion in the extracts and self-assembled molecular layers (SAMs) for Sargassum fluitans III, Sargassum natans I and VIII species was conclusive in acid and alkaline environments. The excellent results obtained reveal an inhibitory efficacy of 88% at 50mg/L for the crude extract of Sargassum fluitans III and efficacies greater than 97% for the chemical families of Sargassum fluitans III. Similarly, microbiological tests also suggest a bactericidal character. Results for Sargassum fluitans III crude extract show a minimum inhibitory concentration (MIC) of 0.005 mg/mL on Gram-negative bacteria and a MIC greater than 0.6 mg/mL on Gram-positive bacteria. These results make it possible to consider the management of local and international issues while valuing a biomass rich in biodegradable molecules. The next step in this study will therefore be the evaluation of the toxicity of Sargassum spp..

Keywords: Sargassum, secondary metabolites, anticorrosive, antibacterial, natural inhibitors

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Authors: Piotr Kacejko, Mariusz Duk, Miroslaw Wendeker

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This paper presents an adaptive controller to track the maximum power point of a photovoltaic modules (PV) under fast irradiation change on the city-bus roof. Photovoltaic systems have been a prominent option as an additional energy source for vehicles. The Municipal Transport Company (MPK) in Lublin has installed photovoltaic panels on its buses roofs. The solar panels turn solar energy into electric energy and are used to load the buses electric equipment. This decreases the buses alternators load, leading to lower fuel consumption and bringing both economic and ecological profits. A DC–DC boost converter is selected as the power conditioning unit to coordinate the operating point of the system. In addition to the conversion efficiency of a photovoltaic panel, the maximum power point tracking (MPPT) method also plays a main role to harvest most energy out of the sun. The MPPT unit on a moving vehicle must keep tracking accuracy high in order to compensate rapid change of irradiation change due to dynamic motion of the vehicle. Maximum power point track controllers should be used to increase efficiency and power output of solar panels under changing environmental factors. There are several different control algorithms in the literature developed for maximum power point tracking. However, energy performances of MPPT algorithms are not clarified for vehicle applications that cause rapid changes of environmental factors. In this study, an adaptive MPPT algorithm is examined at real ambient conditions. PV modules are mounted on a moving city bus designed to test the solar systems on a moving vehicle. Some problems of a PV system associated with a moving vehicle are addressed. The proposed algorithm uses a scanning technique to determine the maximum power delivering capacity of the panel at a given operating condition and controls the PV panel. The aim of control algorithm was matching the impedance of the PV modules by controlling the duty cycle of the internal switch, regardless of changes of the parameters of the object of control and its outer environment. Presented algorithm was capable of reaching the aim of control. The structure of an adaptive controller was simplified on purpose. Since such a simple controller, armed only with an ability to learn, a more complex structure of an algorithm can only improve the result. The presented adaptive control system of the PV system is a general solution and can be used for other types of PV systems of both high and low power. Experimental results obtained from comparison of algorithms by a motion loop are presented and discussed. Experimental results are presented for fast change in irradiation and partial shading conditions. The results obtained clearly show that the proposed method is simple to implement with minimum tracking time and high tracking efficiency proving superior to the proposed method. This work has been financed by the Polish National Centre for Research and Development, PBS, under Grant Agreement No. PBS 2/A6/16/2013.

Keywords: adaptive control, photovoltaic energy, city bus electric load, DC-DC converter

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Authors: Rajashekar Badam, Vedarajan Raman, Noriyoshi Matsumi

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Efficiency of energy converting and storage systems like fuel cells and Li-Air battery principally depended on oxygen reduction reaction (ORR) which occurs at cathode. As the kinetics of the ORR is very slow, it becomes the rate determining step. Exploring carbon substrates for enhancing the dispersion and activity of the metal catalyst and commercially viable simple preparation method is a very crucial area of research in the field of energy materials. Hence, many researchers made large number of carbon-based ORR materials today. But, there are hardly few studies on the effect of interaction between Pt-carbon and carbon-electrolyte on activity. In this work, we have prepared functionalized carbon-based Pt catalyst (Pt-FAB) with enhanced interfacial properties that lead to efficient ORR catalysis. The present work deals with a single-pot method to exfoliate and functionalized acetylene black with enhanced interaction with Pt as well as electrolyte. Acetylene black was functionalized and exfoliated using a facile single pot acid treatment method. The resulted FAB was further decorated with Pt-nano particles (Pt-np). The TEM images of Pt-FAB with uniformly decorated Pt-np of ~3 nm. Further, XPS studies of Pt 4f peak revealed that Pt0 peak was shifted by 0.4 eV in Pt-FAB compared to binding energy of typical Pt⁰ found in Pt/C. The shift can be ascribed to the modulation of electronic state and strong electronic interaction of Pt with carbon. Modulated electronic structure of Pt and strong electronic interaction of Pt with FAB enhances the catalytic activity and durability respectively. To understand the electrode electrolyte interface, electrochemical impedance spectroscopy was carried out. These measurements revealed that the charge transfer resistance of electrode to electrolyte for Pt-FAB is 10 times smaller than that of conventional Pt/C. The interaction with electrolyte helps reduce the interface boundaries, which in turn affects the overall catalytic performance of the electrode. Cyclic voltammetric measurements in 0.1M HClO₄ aq. at a potential scan rate of 50 mVs-1 was employed to evaluate electrochemical surface area (ECSA) of Pt. ECSA of Pt-FAB was found to be as high as 67.2 m²g⁻¹. The three-electrode system showed very high ORR catalytic activity. Mass activity at 0.9 V vs. RHE showed 460 A/g which is much higher than the DOE target values for the year 2020. Further, it showed enhanced performance by showing 723 mW/cm² of highest power density and 1006 mA/cm² of current density at 0.6 V in fuel cell single cell type configuration and 1030 mAhg⁻¹ of rechargeable capacity in Li air battery application. The higher catalytic activity can be ascribed to the improved interaction of FAB with Pt and electrolyte. The aforementioned results evince that Pt-FAB will be a promising cathode material for efficient ORR with significant cyclability for its application in fuel cells and Li-Air batteries. In conclusion, a disordered material was prepared from AB and was systematically characterized. The extremely high ORR activity and ease of preparation make it competent for replacing commercially available ORR materials.

Keywords: functionalized acetylene black, oxygen reduction reaction, fuel cells, Functionalized battery

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Authors: Sarah Pasala, Elizabeth Zacharias

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Vital sign monitoring is crucial for both everyday health and medical diagnosis. A significant factor in assessing a human's health is their vital signs, which include heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings. Vital sign monitoring has been the focus of many system and method innovations recently. Piezoelectrics are materials that convert mechanical energy into electrical energy and can be used for vital sign monitoring. Piezoelectric energy harvesters that are stretchable and flexible can detect very low frequencies like airflow, heartbeat, etc. Current advancements in piezoelectric materials and flexible sensors have made it possible to create wearable and implantable medical devices that can continuously monitor physiological signals in humans. But because of their non-biocompatible nature, they also produce a large amount of e-waste and require another surgery to remove the implant. This paper presents a biocompatible and flexible piezoelectric composite material for wearable and implantable devices that offers a high-performance platform for seamless and continuous monitoring of human physiological signals and tactile stimuli. It also addresses the issue of e-waste and secondary surgery. A Lead-free piezoelectric, SrBi4Ti4O15, is found to be suitable for this application because the properties can be tailored by suitable substitutions and also by varying the synthesis temperature protocols. In the present work, SrBi4Ti4O15 modified by rare-earth has been synthesized and studied. Coupling factors are calculated from resonant (fr) and anti-resonant frequencies (fa). It is observed that Samarium substitution in SBT has increased the Curie temperature, dielectric and piezoelectric properties. From impedance spectroscopy studies, relaxation, and non-Debye type behaviour are observed. The composite of bioresorbable poly(l-lactide) and Lead-free rare earth modified Bismuth Layered Ferroelectrics leads to a flexible piezoelectric device for non-invasive measurement of vital signs, such as heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings and also artery pulse signals in near-surface arteries. These composites are suitable to detect slight movement of the muscles and joints. This Lead-free rare earth modified Bismuth Layered Ferroelectrics – polymer composite is synthesized using a ball mill and the solid-state double sintering method. XRD studies indicated the two phases in the composite. SEM studies revealed the grain size to be uniform and in the range of 100 nm. The electromechanical coupling factor is improved. The elastic constants are calculated and the mechanical flexibility is found to be improved as compared to the single-phase rare earth modified Bismuth Latered piezoelectric. The results indicate that this composite is suitable for the non-invasive detection of multiple vital signs of humans.

Keywords: composites, flexible, non-invasive, piezoelectric

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Authors: Carlos M. Parra, Matthew Sutherland, Ranjita Poudel

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Reduced mental-bandwidth related to low socioeconomic status (low-SES) might lead to impulsivity and risk-taking behavior, which poses as a major hurdle towards asset building (savings) behavior. Understanding the relationship between risk-related personality metrics as well as laboratory risk behavior and real-life savings behavior can help facilitate the development of effective asset building programs, which are vital for mitigating financial vulnerability and income inequality. As such, this study explored the relationship between personality metrics, laboratory behavior in a risky decision-making task and real-life asset building (savings) behaviors among individuals with low-SES from Miami, Florida (FL). Study participants (12 male, 15 female) included racially and ethnically diverse adults (mean age 41.22 ± 12.65 years), with incomplete higher education (18% had High School Diploma, 30% Associates, and 52% Some College), and low annual income (mean $13,872 ± $8020.43). Participants completed eight self-report surveys and played a widely used risky decision-making paradigm called the Balloon Analogue Risk Task (BART). Specifically, participants played three runs of BART (20 trials in each run; total 60 trials). In addition, asset building behavior data was collected for 24 participants who opened and used savings accounts and completed a 6-month savings program that involved monthly matches, and a final reward for completing the savings program without any interim withdrawals. Each participant’s total savings at the end of this program was the main asset building indicator considered. In addition, a new effective use of average pump bet (EUAPB) indicator was developed to characterize each participant’s ability to place winning bets. This indicator takes the ratio of each participant’s total BART earnings to average pump bet (APB) in all 60 trials. Our findings indicated that EUAPB explained more than a third of the variation in total savings among participants. Moreover, participants who managed to obtain BART earnings of at least 30 cents out of their APB, also tended to exhibit better asset building (savings) behavior. In particular, using this criterion to separate participants into high and low EUAPB groups, the nine participants with high EUAPB (mean BART earnings of 35.64 cents per APB) ended up with higher mean total savings ($255.11), while the 15 participants with low EUAPB (mean BART earnings of 22.50 cents per APB) obtained lower mean total savings ($40.01). All mean differences are statistically significant (2-tailed p  .0001) indicating that the relation between higher EUAPB and higher total savings is robust. Overall, these findings can help refine asset building interventions implemented by policy makers and practitioners interested in reducing financial vulnerability among low-SES population. Specifically, by helping identify individuals who are likely to readily take advantage of savings opportunities (such as matched savings programs) and avoiding the stipulation of unnecessary and expensive financial coaching programs to these individuals. This study was funded by J.P. Morgan Chase (JPMC) and carried out by scientists from Florida International University (FIU) in partnership with Catalyst Miami.

Keywords: balloon analogue risk task (BART), matched savings programs, asset building capability, low-SES participants

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Authors: Rohit T. P., Sahil Athrij, Sasi Gopalan

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Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards Augmented/Virtual Reality applications the computational demands on these devices are increasing exponentially and we are already reaching the limits of hardware optimizations. This paper proposes a software solution to this problem. By leveraging the capabilities of cloud computing we can offload the work from mobile devices to dedicated rendering servers that are way more powerful. But this introduces the problem of latency. This paper introduces a protocol that can achieve high-performance low latency Augmented/Virtual Reality experience. There are two parts to the protocol, 1) In-flight compression The main cause of latency in the system is the time required to transmit the camera frame from client to server. The round trip time is directly proportional to the amount of data transmitted. This can therefore be reduced by compressing the frames before sending. Using some standard compression algorithms like JPEG can result in minor size reduction only. Since the images to be compressed are consecutive camera frames there won't be a lot of changes between two consecutive images. So inter-frame compression is preferred. Inter-frame compression can be implemented efficiently using WebGL but the implementation of WebGL limits the precision of floating point numbers to 16bit in most devices. This can introduce noise to the image due to rounding errors, which will add up eventually. This can be solved using an improved interframe compression algorithm. The algorithm detects changes between frames and reuses unchanged pixels from the previous frame. This eliminates the need for floating point subtraction thereby cutting down on noise. The change detection is also improved drastically by taking the weighted average difference of pixels instead of the absolute difference. The kernel weights for this comparison can be fine-tuned to match the type of image to be compressed. 2) Dynamic Load distribution Conventional cloud computing architectures work by offloading as much work as possible to the servers, but this approach can cause a hit on bandwidth and server costs. The most optimal solution is obtained when the device utilizes 100% of its resources and the rest is done by the server. The protocol balances the load between the server and the client by doing a fraction of the computing on the device depending on the power of the device and network conditions. The protocol will be responsible for dynamically partitioning the tasks. Special flags will be used to communicate the workload fraction between the client and the server and will be updated in a constant interval of time ( or frames ). The whole of the protocol is designed so that it can be client agnostic. Flags are available to the client for resetting the frame, indicating latency, switching mode, etc. The server can react to client-side changes on the fly and adapt accordingly by switching to different pipelines. The server is designed to effectively spread the load and thereby scale horizontally. This is achieved by isolating client connections into different processes.

Keywords: 2D kernelling, augmented reality, cloud computing, dynamic load distribution, immersive experience, mobile computing, motion tracking, protocols, real-time systems, web-based augmented reality application

Procedia PDF Downloads 76

Authors: Keita Nishio, Takashi Kaburagi, Yosuke Kurihara

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Recent advances in medical technology have served to enhance average life expectancy. However, the total time for which the patients are prescribed complete bedrest has also increased. With patients being required to maintain a constant lying posture- also called bedsore- development of a system to detect patient roll-over becomes imperative. For this purpose, extant studies have proposed the use of cameras, and favorable results have been reported. Continuous on-camera monitoring, however, tends to violate patient privacy. We have proposed unconstrained bio-signal measurement system that could detect body-motion during sleep and does not violate patient’s privacy. Therefore, in this study, we propose a roll-over detection method by the date obtained from the bi-signal measurement system. Signals recorded by the sensor were assumed to comprise respiration, pulse, body motion, and noise components. Compared the body-motion and respiration, pulse component, the body-motion, during roll-over, generate large vibration. Thus, analysis of the body-motion component facilitates detection of the roll-over tendency. The large vibration associated with the roll-over motion has a great effect on the Root Mean Square (RMS) value of time series of the body motion component calculated during short 10 s segments. After calculation, the RMS value during each segment was compared to a threshold value set in advance. If RMS value in any segment exceeded the threshold, corresponding data were considered to indicate occurrence of a roll-over. In order to validate the proposed method, we conducted experiment. A bi-directional microphone was adopted as a high-sensitivity pressure sensor and was placed between the mattress and bedframe. Recorded signals passed through an analog Band-pass Filter (BPF) operating over the 0.16-16 Hz bandwidth. BPF allowed the respiration, pulse, and body-motion to pass whilst removing the noise component. Output from BPF was A/D converted with the sampling frequency 100Hz, and the measurement time was 480 seconds. The number of subjects and data corresponded to 5 and 10, respectively. Subjects laid on a mattress in the supine position. During data measurement, subjects—upon the investigator's instruction—were asked to roll over into four different positions—supine to left lateral, left lateral to prone, prone to right lateral, and right lateral to supine. Recorded data was divided into 48 segments with 10 s intervals, and the corresponding RMS value for each segment was calculated. The system was evaluated by the accuracy between the investigator’s instruction and the detected segment. As the result, an accuracy of 100% was achieved. While reviewing the time series of recorded data, segments indicating roll-over tendencies were observed to demonstrate a large amplitude. However, clear differences between decubitus and the roll-over motion could not be confirmed. Extant researches possessed a disadvantage in terms of patient privacy. The proposed study, however, demonstrates more precise detection of patient roll-over tendencies without violating their privacy. As a future prospect, decubitus estimation before and after roll-over could be attempted. Since in this paper, we could not confirm the clear differences between decubitus and the roll-over motion, future studies could be based on utilization of the respiration and pulse components.

Keywords: bedsore, high-sensitivity pressure sensor, roll-over, unconstrained bio-signal measurement

Procedia PDF Downloads 121

Authors: Utpal Das, Sona Das

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InAs/GaSb type-II superlattice (T2SL) Mid-wave infrared (MWIR) focal plane arrays (FPAs) have recently seen rapid development. However, in small pixel size large format FPAs, the occurrence of high mesa sidewall surface leakage current is a major constraint necessitating proper surface passivation. A simple pixel isolation technique in InAs/GaSb T2SL detector arrays without the conventional mesa etching has been proposed to isolate the pixels by forming a more resistive higher band gap material from the SL, in the inter-pixel region. Here, a single step femtosecond (fs) laser anneal of the T2SL structure of the inter-pixel T2SL regions, have been used to increase the band gap between the pixels by QW-intermixing and hence increase isolation between the pixels. The p-i-n photodiode structure used here consists of a 506nm, (10 monolayer {ML}) InAs:Si (1x10¹⁸cm⁻³)/(10ML) GaSb SL as the bottom n-contact layer grown on an n-type GaSb substrate. The undoped absorber layer consists of 1.3µm, (10ML)InAs/(10ML)GaSb SL. The top p-contact layer is a 63nm, (10ML)InAs:Be(1x10¹⁸cm⁻³)/(10ML)GaSb T2SL. In order to improve the carrier transport, a 126nm of graded doped (10ML)InAs/(10ML)GaSb SL layer was added between the absorber and each contact layers. A 775nm 150fs-laser at a fluence of ~6mJ/cm² is used to expose the array where the pixel regions are masked by a Ti(200nm)-Au(300nm) cap. Here, in the inter-pixel regions, the p+ layer have been reactive ion etched (RIE) using CH₄+H₂ chemistry and removed before fs-laser exposure. The fs-laser anneal isolation improvement in 200-400μm pixels due to spatially selective quantum well intermixing for a blue shift of ~70meV in the inter-pixel regions is confirmed by FTIR measurements. Dark currents are measured between two adjacent pixels with the Ti(200nm)-Au(300nm) caps used as contacts. The T2SL quality in the active photodiode regions masked by the Ti-Au cap is hardly affected and retains the original quality of the detector. Although, fs-laser anneal of p+ only etched p-i-n T2SL diodes show a reduction in the reverse dark current, no significant improvement in the full RIE-etched mesa structures is noticeable. Hence for a 128x128 array fabrication of 8μm square pixels and 10µm pitch, SU8 polymer isolation after RIE pixel delineation has been used. X-n+ row contacts and Y-p+ column contacts have been used to measure the optical response of the individual pixels. The photo-response of these 8μm and other 200μm pixels under a 2ns optical pulse excitation from an Optical-Parametric-Oscillator (OPO), shows a peak responsivity of ~0.03A/W and 0.2mA/W, respectively, at λ~3.7μm. Temporal response of this detector array is seen to have a fast response ~10ns followed typical slow decay with ringing, attributed to impedance mismatch of the connecting co-axial cables. In conclusion, response times of a few ns have been measured in 8µm pixels of a 128x128 array. Although fs-laser anneal has been found to be useful in increasing the inter-pixel isolation in InAs/GaSb T2SL arrays by QW inter-mixing, it has not been found to be suitable for passivation of full RIE etched mesa structures with vertical walls on InAs/GaSb T2SL.

Keywords: band-gap blue-shift, fs-laser-anneal, InAs/GaSb T2SL, Inter-pixel isolation, ns-Response, photodiode array

Procedia PDF Downloads 153

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

Procedia PDF Downloads 178