Search results for: linear concentration gradient

Authors: Hassane Ouazzani Chahdi, Omar Helli, Bourzgui Nour Eddine, Hassan Maher, Ali Soltani

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The real-time knowledge of the NO, NO₂ concentration at high temperature, would allow manufacturers of automobiles to meet the upcoming stringent EURO7 anti-pollution measures for diesel engines. Knowledge of the concentration of each of these species will also enable engines to run leaner (i.e., more fuel efficient) while still meeting the anti-pollution requirements. Our proposed technology is promising in the field of automotive sensors. It consists of nanostructured semiconductors based on gallium nitride and zirconia dioxide. The development of new technologies for selective detection of NO and NO₂ gas species would be a critical enabler of superior depollution. The current response was well correlated to the NO concentration in the range of 0–2000 ppm, 0-2500 ppm NO₂, and 0-300 ppm NH₃ at a temperature of 600.

Keywords: NOₓ sensors, HEMT transistor, anti-pollution, gallium nitride, gas sensor

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, we introduce a mathematical algorithm which is used for estimating the states in the bilinear systems. This algorithm uses a special linearization of the second-order term by using the best available information about the state of the system. This technique makes our algorithm generalizes the well-known Kalman estimators. The system which is used here is of the bilinear class, the evolution of this model is linear-bilinear in the state of the system. Our algorithm can be used with linear and bilinear systems. We also here introduced a real application for the new algorithm to prove the feasibility and the efficiency for it.

Keywords: estimation algorithm, bilinear systems, Kakman filter, second order linearization

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Authors: M. François, L. Sigot, C. Vallières

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Volatile Organic Compounds (VOCs) are a real health issue, particularly in domestic indoor environments. Among these VOCs, acetaldehyde is frequently monitored in dwellings ‘air, especially due to smoking and spontaneous emissions from the new wall and soil coverings. It is responsible for respiratory complaints and is classified as possibly carcinogenic to humans. Adsorption processes are commonly used to remove VOCs from the air. Metal-Organic Frameworks (MOFs) are a promising type of material for high adsorption performance. These hybrid porous materials composed of metal inorganic clusters and organic ligands are interesting thanks to their high porosity and surface area. The HKUST-1 (also referred to as MOF-199) is a copper-based MOF with the formula [Cu₃(BTC)₂(H₂O)₃]n (BTC = benzene-1,3,5-tricarboxylate) and exhibits unsaturated metal sites that can be attractive sites for adsorption. The objective of this study is to investigate the impact of HKUST-1 pretreatment on acetaldehyde adsorption. Thus, dynamic adsorption experiments were conducted in 1 cm diameter glass column packed with 2 cm MOF bed height. MOF were sieved to 630 µm - 1 mm. The feed gas (Co = 460 ppmv ± 5 ppmv) was obtained by diluting a 1000 ppmv acetaldehyde gas cylinder in air. The gas flow rate was set to 0.7 L/min (to guarantee a suitable linear velocity). Acetaldehyde concentration was monitored online by gas chromatography coupled with a flame ionization detector (GC-FID). Breakthrough curves must allow to understand the interactions between the MOF and the pollutant as well as the impact of the HKUST-1 humidity in the adsorption process. Consequently, different MOF water content conditions were tested, from a dry material with 7 % water content (dark blue color) to water saturated state with approximately 35 % water content (turquoise color). The rough material – without any pretreatment – containing 30 % water serves as a reference. First, conclusions can be drawn from the comparison of the evolution of the ratio of the column outlet concentration (C) on the inlet concentration (Co) as a function of time for different HKUST-1 pretreatments. The shape of the breakthrough curves is significantly different. The saturation of the rough material is slower (20 h to reach saturation) than that of the dried material (2 h). However, the breakthrough time defined for C/Co = 10 % appears earlier in the case of the rough material (0.75 h) compared to the dried HKUST-1 (1.4 h). Another notable difference is the shape of the curve before the breakthrough at 10 %. An abrupt increase of the outlet concentration is observed for the material with the lower humidity in comparison to a smooth increase for the rough material. Thus, the water content plays a significant role on the breakthrough kinetics. This study aims to understand what can explain the shape of the breakthrough curves associated to the pretreatments of HKUST-1 and which mechanisms take place in the adsorption process between the MOF, the pollutant, and the water.

Keywords: acetaldehyde, dynamic adsorption, HKUST-1, pretreatment influence

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Authors: Swapna Koneru, Srinivasa Rao Allam, Vijaya Prakash Gaddem

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The different concentrations of neodymium-doped (Nd-doped) oxy fluoroborate (OFB) glasses were prepared by melt quenching method and characterized through optical absorption, emission and decay curve measurements to understand the lasing potentialities of these glasses. Optical absorption spectra were recorded and have been analyzed using Judd–Ofelt theory. The dipole strengths are parameterized in terms of three phenomenological Judd–Ofelt intensity parameters Ωλ (λ=2, 4 and 6) to elucidate the glassy matrix around Nd3+ ion as well as to determine the 4F3/2 metastable state radiative properties such as the transition probability (AR), radiative lifetime (τR), branching ratios (βR) and integrated absorption cross-section (σa) have been measured for most of the fluorescent levels of Nd3+. The emission spectra recorded for these glasses exhibit two peaks at 1085 and 1328 nm corresponding to 4F3/2 to 4I11/2 and 4I13/2 transitions have been obtained for all the glasses upon 808 nm diode laser excitation in the near infrared region. The emission intensity of the 4F3/2 to 4I11/2 transition increases with increase of Nd3+ concentration up to 1 mol% and then concentration quenching is observed for 2.0 mol% of Nd3+ concentration. The lifetimes for the 4F3/2 level are found to decrease with increase in Nd2O3 concentration in the glasses due to the concentration quenching. The decay curves of all these glasses show single exponential behavior. The spectroscopy of Nd3+ in these glasses is well understood and laser properties can be accurately determined from measured spectroscopic properties. The results obtained are compared with reports on similar glasses. The results indicate that the present glasses could be useful for 1.08 µm laser applications.

Keywords: glasses, luminescence, optical properties, photoluminescence spectroscopy

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Authors: Zahra Kouzehgari

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Since the early emergence of chaos theory in the 1970s in mathematics and physical science, it has increasingly been developed and adapted in social sciences as well. The non-linear and dynamic characteristics of the theory make it a useful conceptual framework to interpret the complex social systems behavior. Regarding chaotic approach principals, sensitivity to initial conditions, dynamic adoption, strange attractors and unpredictability this paper aims to examine whether chaos approach could interpret the ancient social changes. To do this, at first, a brief history of the chaos theory, its development and application in social science as well as the principals making the theory, then its application in archaeological since has been reviewed. The study demonstrates that although based on existing archaeological records reconstruct the whole social system of the human past, the non-linear approaches in studying social complex systems would be of a great help in finding general order of the ancient societies and would enable us to shed light on some of the social phenomena in the human history or to make sense of them.

Keywords: archaeology, non-linear approach, chaos theory, ancient social systems

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Authors: Bello Yusuf Idi

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The Gongola arm of the Upper Banue Trough, Northeastern Nigeria is predominantly covered by the outcrops of Limestone-bearing rocks in form of Sandstone with intercalation of carbonate clay, shale, basaltic, felsphatic and migmatide rocks at subpixel dimension. In this work, subpixel classification algorithm was used to classify the data acquired from landsat 7 Enhance Thematic Mapper (ETM+) satellite system with the aim of producing fractional distribution image for three most economically important solid minerals of the area: Limestone, Basalt and Migmatide. Linear Spectral Unmixing (LSU) algorithm was used to produce fractional distribution image of abundance of the three mineral resources within a 100Km2 portion of the area. The results show that the minerals occur at different proportion all over the area. The fractional map could therefore serve as a guide to the ongoing reconnaissance for the economic potentiality of the formation.

Keywords: linear spectral un-mixing, upper benue trough, gongola arm, geological engineering

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Mustapha Mahmoud Dif, Fouzia Benali-Toumi, Mohamed Benyahia, Sofiane Bouazza, Abbes Dellal, Slimane Baha

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L. multifida is applied to treat rheumatism and cold and has hypoglycemic and anti-inflammatory properties. The present study is to optimize the extraction of phenolic compounds in Algerian Lavandula multifida. The influences of parameters including temperature (decoction and maceration) and extraction time (15min to 45 min) on the flavonoids concentration are studied. The optimal conditions are determined and the quadratic response surfaces draw from the mathematical models. Total phenols were evaluated using Folin sicaltieu methods, total flavonoids were estimated using the Tri chloral aluminum method. The maximum concentration extracted, for total flavonoids, equal to 0.043 mg/g was achieved with decoction and extraction time of 41.55 min. However, for total phenol compounds highest concentration of 0.218 mg/g, is obtained with 45 min at 49.99°C.

Keywords: L multifidi, phenolic content, optimization, time, temperature

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Authors: Piyakajornkul T., Noppiboon S., Hochareon L., Kitsubun P.

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Nowadays, DNA vaccines become an interesting subject in the third vaccine generation. The platform of DNA vaccines production has been developed and its downstream process becomes challenging due to the quality of the products in terms of purity and percentage of supercoiled DNA. To overcome these challenges, tangential flow filtration (TFF), which is involved in the purification process, could be used since it provides effective separation of impurity prior to performing further purification steps. However, operating conditions of TFF is varied based on several factors such as sizes of target particle and impurities, a concentration of solution as well as a concentration polarization on the membrane surface. In this study, pVAX1/lacZ was used as a model of TFF optimization in order to prevent a concentration polarization that can lead to the membrane fouling and also minimize a diafiltration volume while maintaining the maximum permeate flux resulting in proper operating times and buffer volume. By using trans membrane pressure (TMP) excursion method, feed flow rates and TMP were varied. The results showed a correlation of permeate flux with TMP where the maximum volume concentration factor reached 2.5 times of the initial volume when feed flow rate and TMP were 7 liters/m²/min and 1 bar, respectively. It was optimal operating conditions before TFF system undergone pressure independent regime. In addition, the diafiltration volume was 14 times of the concentrated volume prior to performing a further anion chromatography process.

Keywords: concentration polarization, DNA vaccines, optimization, permeate flux, pressure dependent, tangential flow filtration (TFF), trans membrane pressure (TMP)

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Authors: Mumtaz Khan, Adeel Shahid, Waqas Khan

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Heavy metals presence in water streams is a big danger for aquatic life and ultimately effects human health. Removal of copper (Cu) by ispaghula husk, maize fibre, and maize oil cake from synthetic solution in batch conditions was studied. Different experimental parameters such as contact time, initial solution pH, agitation rate, initial Cu concentration, biosorbent concentration, and biosorbent particle size has been studied to quantify the Cu biosorption. The rate of adsorption of metal ions was very fast at the beginning and became slow after reaching the saturation point, followed by a slower active metabolic uptake of metal ions into the cells. Up to a certain point, (pH=4, concentration of Cu = ~ 640 mg/l, agitation rate = ~ 400 rpm, biosorbent concentration = ~ 0.5g, 3g, 3g for ispaghula husk, maize fiber and maize oil cake, respectively) increasing the pH, concentration of Cu, agitation rate, and biosorbent concentration, increased the biosorption rate; however the sorption capacity increased by decreasing the particle size. At optimized experimental parameters, the maximum Cu biosorption by ispaghula husk, maize fibre and maize oil cake were 86.7%, 59.6% and 71.3%, respectively. Moreover, the results of the kinetics studies demonstrated that the biosorption of copper on ispaghula husk, maize fibre, and maize oil cake followed pseudo-second order kinetics. The results of adsorption were fitted to both the Langmuir and Freundlich models. The Langmuir model represented the sorption process better than Freundlich, and R² value ~ 0.978. Optimizations of physical and environmental parameters revealed, ispaghula husk as more potent copper biosorbent than maize fibre, and maize oil cake. The sorbent is cheap and available easily, so this study can be applied to remove Cu impurities on pilot and industrial scale after certain modifications.

Keywords: biosorption, copper, ispaghula husk, maize fibre, maize oil cake, purification

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Shakti S. Acharya, V. R. R. Medicherla, Rajeev Rawat, Komal Bapna, Deepnarayan Biswas, Khadija Ali, K. Maiti

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The discovery of invar effect in 35% Ni concentration Fe1-xNix alloy has stimulated enormous experimental and theoretical research. Elemental Fe and low Ni concentration Fe1-xNix alloys which possess body centred cubic (bcc) crystal structure at ambient temperature and pressure transform to hexagonally close packed (hcp) phase at around 13 GPa. Magnetic order was found to be absent at 11K for Fe92Ni8 alloy when subjected to a high pressure of 26 GPa. The density functional theoretical calculations predicted substantial hyperfine magnetic fields, but were not observed in Mossbaur spectroscopy. The bulk modulus of fcc Fe1-xNix alloys with Ni concentration more than 35%, is found to be independent of pressure. The magnetic moment of Fe is also found be almost same in these alloys from 4 to 10 GPa pressure. Fe1-xNix alloys exhibit a complex microstructure which is formed by a series of complex phase transformations like martensitic transformation, spinodal decomposition, ordering, mono-tectoid reaction, eutectoid reaction at temperatures below 400°C. Despite the existence of several theoretical models the field is still in its infancy lacking full knowledge about the anomalous properties exhibited by these alloys. Fe1-xNix alloys have been prepared by arc melting the high purity constituent metals in argon ambient. These alloys have annealed at around 3000C in vacuum sealed quartz tube for two days to make the samples homogeneous. These alloys have been structurally characterized by x-ray diffraction and were found to exhibit a transition from bcc to fcc for x > 0.3. Ni 2p core levels of the alloys have been measured using high resolution (0.45 eV) x-ray photoelectron spectroscopy. Ni 2p core level shifts to lower binding energy with respect to that of pure Ni metal giving rise to negative core level shifts (CLSs). Measured CLSs exhibit a linear dependence in fcc region (x > 0.3) and were found to deviate slightly in bcc region (x < 0.3). ESCA potential model fails correlate CLSs with site potentials or charges in metallic alloys. CLSs in these alloys occur mainly due to shift in valence bands with composition due to intra atomic charge redistribution.

Keywords: arc melting, core level shift, ESCA potential model, valence band

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Authors: Emre Ozaslan, Bulent Acar, Mehmet Ali Guler

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Unidirectional composites are very popular structural materials used in aerospace, marine, energy and automotive industries thanks to their superior material properties. However, the mechanical behavior of composite materials is more complicated than isotropic materials because of their anisotropic nature. Also, a stress concentration availability on the structure, like a hole, makes the problem further complicated. Therefore, enormous number of tests require to understand the mechanical behavior and strength of composites which contain stress concentration. Accurate finite element analysis and analytical models enable to understand mechanical behavior and predict the strength of composites without enormous number of tests which cost serious time and money. In this study, unidirectional Carbon/Epoxy composite specimens with central circular hole were investigated in terms of stress concentration factor and strength prediction. The composite specimens which had different specimen wide (W) to hole diameter (D) ratio were tested to investigate the effect of hole size on the stress concentration and strength. Also, specimens which had same specimen wide to hole diameter ratio, but varied sizes were tested to investigate the size effect. Finite element analysis was performed to determine stress concentration factor for all specimen configurations. For quasi-isotropic laminate, it was found that the stress concentration factor increased approximately %15 with decreasing of W/D ratio from 6 to 3. Point stress criteria (PSC), inherent flaw method and progressive failure analysis were compared in terms of predicting the strength of specimens. All methods could predict the strength of specimens with maximum %8 error. PSC was better than other methods for high values of W/D ratio, however, inherent flaw method was successful for low values of W/D. Also, it is seen that increasing by 4 times of the W/D ratio rises the failure strength of composite specimen as %62.4. For constant W/D ratio specimens, all the strength prediction methods were more successful for smaller size specimens than larger ones. Increasing the specimen width and hole diameter together by 2 times reduces the specimen failure strength as %13.2.

Keywords: failure, strength, stress concentration, unidirectional composites

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Authors: Sobiya George, Anna Dora Gudmundsdottir

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The 2-hydroxychalcones form an important group of organic compounds not only because of their pharmacological properties but also because they are intermediates in the biosynthesis of flavanones. We studied the photoreactivity of 2-hydroxychalcone derivatives in aprotic solvent acetonitrile and found that their photochemistry is concentration-dependent. Irradiation of 2-hydroxychalcone derivatives with 365 nm light emitting diode (LED) in dilute concentration selectively forms flavanones, whereas, at higher concentrations, an additional photoproduct is observed. However, the application of the continuous photo-flow method resulted in the selective formation of flavanones even at higher concentrations. To understand the reaction mechanism and explain the concentration-dependent photoreactivity of 2-hydroxychalcones, we preformed trapping studies with tris(trimethylsilyl)silane, nanosecond laser flash photolysis, and time dependent-density functional theory (TD-DFT) calculations.

Keywords: flavanones, hydroxychalcones, laser flash photolysis, TD-DFT calculations

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Authors: Olaniyi Fawole, Umezuruike Opara

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Co-products obtained from pomegranate juice processing contain high levels of polyphenols with potential high added values. From value-addition viewpoint, the aim of this study was to evaluate the stability of polyphenolic concentrations in pomegranate fruit co-products in different solvent extracts and assess the effect on the total antioxidant capacity using the FRAP, DPPH˙ and ABTS˙+ assays during simulated in vitro digestion. Pomegranate juice, marc and peel were extracted in water, 50% ethanol (50%EtOH) and absolute ethanol (100%EtOH) and analysed for total phenolic concentration (TPC), total flavonoids concentration (TFC) and total antioxidant capacity in DPPH˙, ABST˙+ and FRAP assays before and after in vitro digestion. Total phenolic concentration (TPC) and total flavonoid concentration (TFC) were in the order of peel > marc > juice throughout the in vitro digestion irrespective of the extraction solvents used. However, 50% ethanol extracted 1.1 to 12-fold more polyphenols than water and ethanol solvents depending on co-products. TPC and TFC increased significantly in gastric digests. In contrast, after the duodenal, polyphenolic concentrations decreased significantly (p < 0.05) compared to those obtained in gastric digests. Undigested samples and gastric digests showed strong and positive relationships between polyphenols and the antioxidant activities measured in DPPH, ABTS and FRAP assays, with correlation coefficients (r2) ranging between 0.930 – 0.990 whereas, the correlation between polyphenols (TPC and TFC) and radical cation scavenging activity (in ABTS) were moderately positive in duodenal digests. Findings from this study also showed that the concentration of pomegranate polyphenols and antioxidant thereof during in vitro gastro-intestinal digestion may not reflect the pre-digested phenolic concentration. Thus, this study highlights the need to provide biologically relevant information on antioxidants by providing data reflecting their stability and activity after in vitro digestion.

Keywords: by-product, DPPH, polyphenols, value addition

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Authors: Yushuai Wang, Feng Xu, Junbo Tan, Xueqian Wang, Bin Liang

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In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (RMPC) and set theoretic fault detection and isolation (FDI) is extended to linear parameter varying (LPV) systems. First, a group of set-valued observers are designed for passive fault detection (FD) and the observer gains are obtained through minimizing the size of invariant set of state estimation-error dynamics. Second, an input set for fault isolation (FI) is designed offline through set theory for actively isolating faults after FD. Third, an RMPC controller based on state estimation for LPV systems is designed to control the system in the presence of disturbance and measurement noise and tolerate faults. Besides, an FTC algorithm is proposed to maintain the plant operate in the corresponding mode when the fault occurs. Finally, a numerical example is used to show the effectiveness of the proposed results.

Keywords: fault detection, linear parameter varying, model predictive control, set theory

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Authors: Salah Abdul Hameed Saleh, Ghada Hasan

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The aim of this work is to produce an empirical model for the determination of particulate matter (PM10) concentration in the atmosphere using visible bands of Landsat 8 OLI satellite image over Kirkuk city- IRAQ. The suggested algorithm is established on the aerosol optical reflectance model. The reflectance model is a function of the optical properties of the atmosphere, which can be related to its concentrations. The concentration of PM10 measurements was collected using Particle Mass Profiler and Counter in a Single Handheld Unit (Aerocet 531) meter simultaneously by the Landsat 8 OLI satellite image date. The PM10 measurement locations were defined by a handheld global positioning system (GPS). The obtained reflectance values for visible bands (Coastal aerosol, Blue, Green and blue bands) of landsat 8 OLI image were correlated with in-suite measured PM10. The feasibility of the proposed algorithms was investigated based on the correlation coefficient (R) and root-mean-square error (RMSE) compared with the PM10 ground measurement data. A choice of our proposed multispectral model was founded on the highest value correlation coefficient (R) and lowest value of the root mean square error (RMSE) with PM10 ground data. The outcomes of this research showed that visible bands of Landsat 8 OLI were capable of calculating PM10 concentration with an acceptable level of accuracy.

Keywords: air pollution, PM10 concentration, Lansat8 OLI image, reflectance, multispectral algorithms, Kirkuk area

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Authors: W. A. Gonçalves, E. P. Souza, C. R. Alcântara

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The ISCCP-Tracking database offers an opportunity to study physical and morphological characteristics of Convective Systems based on geostationary meteorological satellites. This database contains 26 years of tracking of Convective Systems for the entire globe. Then, Tropical Squall Lines which occur in Brazil are certainly within the database. In this study, we propose a methodology for identification of these systems based on the ISCCP-Tracking database. A physical and morphological characterization of these systems is also shown. The proposed methodology is firstly based on the year of 2007. The Squall Lines were subjectively identified by visually analyzing infrared images from GOES-12. Based on this identification, the same systems were identified within the ISCCP-Tracking database. It is known, and it was also observed that the Squall Lines which occur on the north coast of Brazil develop parallel to the coast, influenced by the sea breeze. In addition, it was also observed that the eccentricity of the identified systems was greater than 0.7. Then, a methodology based on the inclination (based on the coast) and eccentricity (greater than 0.7) of the Convective Systems was applied in order to identify and characterize Tropical Squall Lines in Brazil. These thresholds were applied back in the ISCCP-Tracking database for the year of 2007. It was observed that other systems, which were not Squall Lines, were also identified. Then, we decided to call all systems identified by the inclination and eccentricity thresholds as Linear Convective Systems, instead of Squall Lines. After this step, the Linear Convective Systems were identified and characterized for the entire database, from 1983 to 2008. The physical and morphological characteristics of these systems were compared to those systems which did not have the required inclination and eccentricity to be called Linear Convective Systems. The results showed that the convection associated with the Linear Convective Systems seems to be more intense and organized than in the other systems. This affirmation is based on all ISCCP-Tracking variables analyzed. This type of methodology, which explores 26 years of satellite data by an objective analysis, was not previously explored in the literature. The physical and morphological characterization of the Linear Convective Systems based on 26 years of data is of a great importance and should be used in many branches of atmospheric sciences.

Keywords: squall lines, convective systems, linear convective systems, ISCCP-Tracking

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Authors: Hande Sezgin, Senem Kursun Bahadır, Yakup Erhan Boke, Fatma Kalaoğlu

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Electronic textiles (e-textiles) are fabrics that contain electronics and interconnections with them. In this study, two types of base yarns (cotton and acrylic) and three conductive steel yarns with different linear resistance values (14Ω/m, 30Ω/m, 70Ω/m) were used to investigate the effect of base yarn type and linear resistance of conductive yarns on thermal behavior of e-textile structures. Thermal behavior of samples were examined by thermal camera.

Keywords: conductive yarn, e-textiles, smart textiles, thermal analysis

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Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

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To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

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Authors: F. Rahimi Dehgolan, S. E. Khadem, S. Bab, M. Najafee

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Nowadays, using rotating systems like shafts and disks in industrial machines have been increased constantly. Dynamic stability is one of the most important factors in designing rotating systems. In this study, linear frequencies and stability of a coupled continuous flexible rotor-disk-blades system are studied. The Euler-Bernoulli beam theory is utilized to model the blade and shaft. The equations of motion are extracted using the extended Hamilton principle. The equations of motion have been simplified using the Coleman and complex transformations method. The natural frequencies of the linear part of the system are extracted, and the effects of various system parameters on the natural frequencies and decay rates (stability condition) are clarified. It can be seen that the centrifugal stiffening effect applied to the blades is the most important parameter for stability of the considered rotating system. This result highlights the importance of considering this stiffing effect in blades equation.

Keywords: rotating shaft, flexible blades, centrifugal stiffness, stability

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Authors: Anju Joshi, C. N. Tharamani

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Diabetes is one of the leading cause of death at present and remains an important concern as the prevalence of the disease is increasing at an alarming rate. Therefore, it is crucial to diagnose the accurate levels of glucose for developing an efficient therapeutic for diabetes. Due to the availability of convenient and compact self-testing, continuous monitoring of glucose is feasible nowadays. Enzyme based electrochemical sensing of glucose is quite popular because of its high selectivity but suffers from drawbacks like complicated purification and immobilization procedures, denaturation, high cost, and low sensitivity due to indirect electron transfer. Hence, designing a robust enzyme free platform using transition metal oxides remains crucial for the efficient and sensitive determination of glucose. In the present work, manganese doped nickel oxide nanoparticles (Mn-NiO) has been synthesized onto the surface of multiwalled carbon nanotubes using a simple microwave assisted approach for non-enzymatic electrochemical sensing of glucose. The morphology and structure of the synthesized nanostructures were characterized using scanning electron microscopy (SEM) and X-Ray diffraction (XRD). We demonstrate that the synthesized nanostructures show enormous potential for electrocatalytic oxidation of glucose with high sensitivity and selectivity. Cyclic voltammetry and square wave voltammetry studies suggest superior sensitivity and selectivity of Mn-NiO decorated carbon nanotubes towards the non-enzymatic determination of glucose. A linear response between the peak current and the concentration of glucose has been found to be in the concentration range of 0.01 μM- 10000 μM which suggests the potential efficacy of Mn-NiO decorated carbon nanotubes for sensitive determination of glucose.

Keywords: diabetes, glucose, Mn-NiO decorated carbon nanotubes, non-enzymatic

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Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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Authors: Morteza Shayan Arani, Mohammadamin Esmailzadehazimi, Mohammadreza Moeini, Mohammad Toorani, Aouni A. Lakis

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This paper investigates the nonlinear response of thin, incompressible, hyperelastic cylindrical shells in the presence of a time-varying temperature field while considering initial geometric imperfections. The governing equations of motion are derived using an improved Donnell's shallow shell theory. The hyperelastic material is modeled using the Mooney-Rivlin model with two parameters, incorporating temperature-dependent terms. The Lagrangian method is applied to obtain the equation of motion. The resulting governing equation is addressed through the Lindstedt-Poincaré and Multiple Scale methods. The linear and nonlinear models presented in this study are verified against existing open literature, demonstrating the accuracy and reliability of the presented model. The study focuses on understanding the influence of temperature variations and geometrical imperfections on the natural frequency and amplitude-frequency response of the systems. Notably, the investigation reveals the coexistence of hardening and softening peaks in the amplitude-frequency response, which vary in magnitude depending on these parameters. Additionally, resonance peaks exhibit changes as a result of temperature and geometric imperfections.

Keywords: hyperelastic material, cylindrical shell, geometrical nonlinearity, material naolinearity, initial geometric imperfection, temperature gradient, hardening and softening

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Authors: H. Tai Pham, Bae Wisup, Sungmin Jung, Ivan Efriza, Ratna Widyaningsih, Byung Un Min

Abstract:

The middle-phase-microemulsion in Alkaline-Surfactant-Polymer (ASP) solution and oil play important roles in the success of an ASP flooding process. The high quality microemulsion phase has ultralow interfacial tensions and it can increase oil recovery. The research used optimal experimental design and response-surface-methodology to predict the optimum concentration of chemicals in ASP solution for maximum microemulsion quality. Secondly, this optimal ASP formulation was implemented in core flooding test to investigate the effective injection volume. As the results, the optimum concentration of surfactants in the ASP solution is 0.57 wt.% and the highest effective injection volume is 19.33% pore volume.

Keywords: optimize, ASP, response surface methodology, solubilization ratio

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Authors: Amna Khan, Zareena Kausar, Saad Malik

Abstract:

Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: H. K. Esfahani, B. Datta

Abstract:

Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Jonathan Sohn

Abstract:

Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Angelis P. Barlampas

Abstract:

Theoretical background Disorders of fixation and rotation of the large intestine, result in the existence of its parts in ectopic anatomical positions. In case of symptomatology, the clinical picture is complicated by the possible symptomatology of the neighboring anatomical structures and a differential diagnostic problem arises. Target The purpose of this work is to demonstrate the difficulty of revealing the real cause of abdominal pain, in cases of anatomical variants and the decisive contribution of imaging and especially that of computed tomography. Methods A patient came to the emergency room, because of acute pain in the right hypochondrium. Clinical examination revealed tenderness in the gallbladder area and a positive Murphy's sign. An ultrasound exam depicted a normal gallbladder and the patient was referred for a CT scan. Results Flexible, unfixed ascending colon and cecum, located in the anatomical region of the right mesentery. Opacities of the surrounding peritoneal fat and a small linear concentration of fluid can be seen. There was an appendix of normal anteroposterior diameter with the presence of air in its lumen and without clear signs of inflammation. There was an impression of possible inflammatory swelling at the base of the appendix, (DD phenomenon of partial volume; e.t.c.). Linear opacities of the peritoneal fat in the region of the second loop of the duodenum. Multiple diverticula throughout the colon. Differential Diagnosis The differential diagnosis includes the following: Inflammation of the base of the appendix, diverticulitis of the cecum-ascending colon, a rare case of second duodenal loop ulcer, tuberculosis, terminal ileitis, pancreatitis, torsion of unfixed cecum-ascending colon, embolism or thrombosis of a vascular intestinal branch. Final Diagnosis There is an unfixed cecum-ascending colon, which is exhibiting diverticulitis.

Keywords: unfixed cecum-ascending colon, abdominal pain, malrotation, abdominal CT, congenital anomalies

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Authors: V. Ibujes, A. Guevara, P. Barreto

Abstract:

Concentration of arsenic represents a serious threat to human health. It is a bioaccumulable toxic element and is transferred through the food chain. In Ecuador, values of 0.0423 mg/kg As are registered in potatoes of the skirts of the Tungurahua volcano. The increase of arsenic contamination in Ecuador is mainly due to mining activity, since the process of gold extraction generates toxic tailings with mercury. In the Province of Azuay, due to the mining activity, the soil reaches concentrations of 2,500 to 6,420 mg/kg As whereas in the province of Tungurahua it can be found arsenic concentrations of 6.9 to 198.7 mg/kg due to volcanic eruptions. Since the contamination by arsenic, the present investigation is directed to the remediation of the soils in the provinces of Azuay and Tungurahua by phytoremediation technique and the definition of a methodology of extraction by means of analysis of arsenic in the system soil-plant. The methodology consists in selection of two types of plants that have the best arsenic removal capacity in synthetic solutions 60 μM As, a lower percentage of mortality and hydroponics resistance. The arsenic concentrations in each plant were obtained from taking 10 ml aliquots and the subsequent analysis of the ICP-OES (inductively coupled plasma-optical emission spectrometry) equipment. Soils were contaminated with synthetic solutions of arsenic with the capillarity method to achieve arsenic concentration of 13 and 15 mg/kg. Subsequently, two types of plants were evaluated to reduce the concentration of arsenic in soils for 7 weeks. The global variance for soil types was obtained with the InfoStat program. To measure the changes in arsenic concentration in the soil-plant system, the Rhizo and Wenzel arsenic extraction methodology was used and subsequently analyzed with the ICP-OES (optima 8000 Pekin Elmer). As a result, the selected plants were bluegrass and llanten, due to the high percentages of arsenic removal of 55% and 67% and low mortality rates of 9% and 8% respectively. In conclusion, Azuay soil with an initial concentration of 13 mg/kg As reached the concentrations of 11.49 and 11.04 mg/kg As for bluegrass and llanten respectively, and for the initial concentration of 15 mg/kg As reached 11.79 and 11.10 mg/kg As for blue grass and llanten after 7 weeks. For the Tungurahua soil with an initial concentration of 13 mg/kg As it reached the concentrations of 11.56 and 12.16 mg/kg As for the bluegrass and llanten respectively, and for the initial concentration of 15 mg/kg As reached 11.97 and 12.27 mg/kg Ace for bluegrass and llanten after 7 weeks. The best arsenic extraction methodology of soil-plant system is Wenzel.

Keywords: blue grass, llanten, phytoremediation, soil of Azuay, soil of Tungurahua, synthetic arsenic solution

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