Search results for: signal processing for transmission carrier frequency offset

Authors: Xin Jiao, Xin Zhang, Jian Fan, Zhenwei Cai, Yiming Xu

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Tower cranes play a crucial role in the construction industry, facilitating the vertical and horizontal movement of materials and aiding in building construction, especially for high-rise structures. However, tower crane accidents can lead to severe consequences, highlighting the importance of effective safety management and inspection. This paper presents an innovative approach to tower crane inspection utilizing Unmanned Aerial Vehicles (UAVs) and an Intelligent Inspection APP System. The system leverages UAVs equipped with high-definition cameras to conduct efficient and comprehensive inspections, reducing manual labor, inspection time, and risk. By integrating advanced technologies such as Real-Time Kinematic (RTK) positioning and digital image processing, the system enables precise route planning and collection of safety hazards images. A case study conducted on a construction site demonstrates the practicality and effectiveness of the proposed method, showcasing its potential to enhance tower crane safety. On-site testing of UAV intelligent inspections reveals key findings: efficient tower crane hazard inspection within 30 minutes, with a full-identification capability coverage rates of 76.3%, 64.8%, and 76.2% for major, significant, and general hazards respectively and a preliminary-identification capability coverage rates of 18.5%, 27.2%, and 19%, respectively. Notably, UAVs effectively identify various tower crane hazards, except for those requiring auditory detection. The limitations of this study primarily involve two aspects: Firstly, during the initial inspection, manual drone piloting is required for marking tower crane points, followed by automated flight inspections and reuse based on the marked route. Secondly, images captured by the drone necessitate manual identification and review, which can be time-consuming for equipment management personnel, particularly when dealing with a large volume of images. Subsequent research efforts will focus on AI training and recognition of safety hazard images, as well as the automatic generation of inspection reports and corrective management based on recognition results. The ongoing development in this area is currently in progress, and outcomes will be released at an appropriate time.

Keywords: tower crane, inspection, unmanned aerial vehicle (UAV), intelligent inspection app system, safety management

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Basil Nkosilathi Dube, Wilson R. Nyemba, Panashe Mandevu

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In highway driving, over 50 percent of the power produced by the engine is used to overcome aerodynamic drag, which is a force that opposes a body’s motion through the air. Aerodynamic drag and thus fuel consumption increase rapidly at speeds above 90kph. It is desirable to minimize fuel consumption. Aerodynamic drag reduction in highway driving is the best approach to minimize fuel consumption and to reduce the negative impacts of greenhouse gas emissions on the natural environment. Fuel economy is the ultimate concern of automotive development. This study aims to design and analyze drag-reducing devices for a Mazda T3500 truck, namely, the cab roof and rear (trailer tail) fairings. The aerodynamic effects of adding these append devices were subsequently investigated. To accomplish this, two 3D CAD models of the Mazda truck were designed using the Design Modeler. One, with these, append devices and the other without. The models were exported to ANSYS Fluent for computational fluid dynamics analysis, no wind tunnel tests were performed. A fine mesh with more than 10 million cells was applied in the discretization of the models. The realizable k-ε turbulence model with enhanced wall treatment was used to solve the Reynold’s Averaged Navier-Stokes (RANS) equation. In order to simulate the highway driving conditions, the tests were simulated with a speed of 100 km/h. The effects of these devices were also investigated for low-speed driving. The drag coefficients for both models were obtained from the numerical calculations. By adding the cab roof and rear (trailer tail) fairings, the simulations show a significant reduction in aerodynamic drag at a higher speed. The results show that the greatest drag reduction is obtained when both devices are used. Visuals from post-processing show that the rear fairing minimized the low-pressure region at the rear of the trailer when moving at highway speed. The rear fairing achieved this by streamlining the turbulent airflow, thereby delaying airflow separation. For lower speeds, there were no significant differences in drag coefficients for both models (original and modified). The results show that these devices can be adopted for improving the aerodynamic efficiency of the Mazda T3500 truck at highway speeds.

Keywords: aerodynamic drag, computation fluid dynamics, fluent, fuel consumption

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Authors: Manel Hammami, Gabriele Grandi

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In recent years, multilevel inverters have become more attractive for single-phase photovoltaic (PV) systems, due to their known advantages over conventional H-bridge pulse width-modulated (PWM) inverters. They offer improved output waveforms, smaller filter size, lower total harmonic distortion (THD), higher output voltages and others. The most common multilevel converter topologies, presented in literature, are the neutral-point-clamped (NPC), flying capacitor (FC) and Cascaded H-Bridge (CHB) converters. In both NPC and FC configurations, the number of components drastically increases with the number of levels what leads to complexity of the control strategy, high volume, and cost. Whereas, increasing the number of levels in case of the cascaded H-bridge configuration is a flexible solution. However, it needs isolated power sources for each stage, and it can be applied to PV systems only in case of PV sub-fields. In order to improve the ratio between the number of output voltage levels and the number of components, several hybrids and asymmetric topologies of multilevel inverters have been proposed in the literature such as the FC asymmetric H-bridge (FCAH) and the NPC asymmetric H-bridge (NPCAH) topologies. Another asymmetric multilevel inverter configuration that could have interesting applications is the cascaded asymmetric H-bridge (CAH), which is based on a modular half-bridge (two switches and one capacitor, also called level doubling network, LDN) cascaded to a full H-bridge in order to double the output voltage level. This solution has the same number of switches as the above mentioned AH configurations (i.e., six), and just one capacitor (as the FCAH). CAH is becoming popular, due to its simple, modular and reliable structure, and it can be considered as a retrofit which can be added in series to an existing H-Bridge configuration in order to double the output voltage levels. In this paper, an original and effective method for the analysis of the DC-link voltage ripple is given for single-phase asymmetric H-bridge multilevel inverters based on level doubling network (LDN). Different possible configurations of the asymmetric H-Bridge multilevel inverters have been considered and the analysis of input voltage and current are analytically determined and numerically verified by Matlab/Simulink for the case of cascaded asymmetric H-bridge multilevel inverters. A comparison between FCAH and the CAH configurations is done on the basis of the analysis of the DC and voltage ripple for the DC source (i.e., the PV system). The peak-to-peak DC and voltage ripple amplitudes are analytically calculated over the fundamental period as a function of the modulation index. On the basis of the maximum peak-to-peak values of low frequency and switching ripple voltage components, the DC capacitors can be designed. Reference is made to unity output power factor, as in case of most of the grid-connected PV generation systems. Simulation results will be presented in the full paper in order to prove the effectiveness of the proposed developments in all the operating conditions.

Keywords: asymmetric inverters, dc-link voltage, level doubling network, single-phase multilevel inverter

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Authors: Gema M. Rodado, Jose M. Olavarrieta

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Hydrogen fuel cell technologies have experienced a great boost in the last decades, significantly increasing the production of these devices for both stationary and portable (mainly automotive) applications; these are influenced by two main factors: environmental pollution and energy shortage. A fuel cell is an electrochemical device that converts chemical energy directly into electricity by using hydrogen and oxygen gases as reactive components and obtaining water and heat as byproducts of the chemical reaction. Fuel cells, specifically those of Proton Exchange Membrane (PEM) technology, are considered an alternative to internal combustion engines, mainly because of the low emissions they produce (almost zero), high efficiency and low operating temperatures (< 373 K). The introduction and use of fuel cells in the automotive market requires the development of standardized and validated procedures to test and evaluate their performance in different environmental conditions including vibrations and freeze-thaw cycles. These situations of vibration and extremely low/high temperatures can affect the physical integrity or even the excellent operation or performance of the fuel cell stack placed in a vehicle in circulation or in different climatic conditions. The main objective of this work is the development and validation of vibration and freeze-thaw cycling test procedures for fuel cell stacks that can be used in a vehicle in order to consolidate their safety, performance, and durability. In this context, different experimental tests were carried out at the facilities of the National Hydrogen Centre (CNH2). The experimental equipment used was: A vibration platform (shaker) for vibration test analysis on fuel cells in three axes directions with different vibration profiles. A walk-in climatic chamber to test the starting, operating, and stopping behavior of fuel cells under defined extreme conditions. A test station designed and developed by the CNH2 to test and characterize PEM fuel cell stacks up to 10 kWe. A 5 kWe PEM fuel cell stack in off-operation mode was used to carry out two independent experimental procedures. On the one hand, the fuel cell was subjected to a sinusoidal vibration test on the shaker in the three axes directions. It was defined by acceleration and amplitudes in the frequency range of 7 to 200 Hz for a total of three hours in each direction. On the other hand, the climatic chamber was used to simulate freeze-thaw cycles by defining a temperature range between +313 K and -243 K with an average relative humidity of 50% and a recommended ramp up and rump down of 1 K/min. The polarization curve and gas leakage rate were determined before and after the vibration and freeze-thaw tests at the fuel cell stack test station to evaluate the robustness of the stack. The results were very similar, which indicates that the tests did not affect the fuel cell stack structure and performance. The proposed procedures were verified and can be used as an initial point to perform other tests with different fuel cells.

Keywords: climatic chamber, freeze-thaw cycles, PEM fuel cell, shaker, vibration tests

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Authors: Tatyane Lopes de Freitas, Antonio Diogo S. Vieira, Susana Marta Isay Saad, Maria Ines Genovese

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The fruit processing industries generate a large volume of residues to produce juices, pulps, and jams. These residues, or by-products, consisting of peels, seeds, and pulps, are routinely discarded. Fruits are rich in bioactive compounds, including polyphenols, which have positive effects on health. Dry residues from two fruits, acerola (M. emarginata D. C.) and orange (C. sinensis), were characterized in relation to contents of ascorbic acid, minerals, total dietary fibers, moisture, ash, lipids, proteins, and carbohydrates, and also high performance liquid chromatographic profile of flavonoids, total polyphenols and proanthocyanidins contents, and antioxidant capacity by three different methods (Ferric reducing antioxidant power assay-FRAP, Oxygen Radical Absorbance Capacity-ORAC, 1,1-diphenyl-2-picrylhydrazil (DPPH) radical scavenging activity). Acerola by-products presented the highest acid ascorbic content (605 mg/100 g), and better antioxidant capacity than orange by-products. The dry residues from acerola demonstrated high contents of proanthocyanidins (617 µg CE/g) and total polyphenols (2525 mg gallic acid equivalents - GAE/100 g). Both presented high total dietary fiber (above 60%) and protein contents (acerola: 10.4%; orange: 9.9%), and reduced fat content (acerola: 1.6%; orange: 2.6%). Both residues showed high levels of potassium, calcium, and magnesium, and were considered sources of these minerals. With acerola by-product, four formulations of probiotics fermented milks were produced: F0 (without the addition of acerola residue (AR)), F2 (2% AR), F5 (5% AR) and F10 (10% AR). The physicochemical characteristics of the fermented milks throughout of storage were investigated, as well as the impact of in vitro simulated gastrointestinal conditions on flavonoids and probiotics. The microorganisms analyzed maintained their populations around 8 log CFU/g during storage. After the gastric phase of the simulated digestion, the populations decreased, and after the enteric phase, no colonies were detected. On the other hand, the flavonoids increased after the gastric phase, maintaining or suffering small decrease after enteric phase. Acerola by-products powder is a valuable ingredient to be used in functional foods because is rich in vitamin C, fibers and flavonoids. These flavonoids appear to be highly resistant to the acids and salts of digestion.

Keywords: acerola, orange, by-products, fermented milk

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

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Authors: Temitayo Tosin Alawiye

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Plant disease control is important in maintaining plant vigour, grain quantity, abundance of food, feed, and fibre produced by farmers all over the world. Farmers make use of different methods in controlling these diseases but one of the commonly used method is the use of chemicals. However, the continuous and excessive usages of these agrochemicals pose a danger to the environment, man and wildlife. The more the population growth the more the food security challenge which leads to more pressure on agronomic growth. Agricultural waste also known as green waste are the residues from the growing and processing of raw agricultural products such as fruits, vegetables, rice husk, corn cob, mushroom growth medium waste, coconut husk. They are widely used in land bioremediation, crop production and protection which include disease control. These agricultural wastes help the crop by improving the soil fertility, increase soil organic matter and reduce in many cases incidence and severity of disease. The objective was to review the agricultural waste that has worked effectively against certain soil-borne diseases such as Fusarium oxysporum, Pythiumspp, Rhizoctonia spp so as to help minimize the use of chemicals. Climate change is a major problem of agriculture and vice versa. Climate change and agriculture are interrelated. Change in climatic conditions is already affecting agriculture with effects unevenly distributed across the world. It will increase the risk of food insecurity for some vulnerable groups such as the poor in Sub Saharan Africa. The food security challenge will become more difficult as the world will need to produce more food estimated to feed billions of people in the near future with Africa likely to be the biggest hit. In order to surmount this hurdle, smallholder farmers in Africa must embrace climate-smart agricultural techniques and innovations which includes the use of green waste in agriculture, conservative agriculture, pasture and manure management, mulching, intercropping, etc. Training and retraining of smallholder farmers on the use of green energy to mitigate the effect of climate change should be encouraged. Policy makers, academia, researchers, donors, and farmers should pay more attention to the use of green energy as a way of reducing incidence and severity of soilborne plant diseases to solve looming food security challenges.

Keywords: agricultural waste, climate change, green energy, soil borne plant disease

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Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

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Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

Procedia PDF Downloads 162

Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

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Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini

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Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.

Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time

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Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand

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Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.

Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing

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Authors: Ditsapelo M. McFarland

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Background: Despite the availability of the Pap smear services in urban areas in Botswana, most women in such areas do not seem to screen regular for prevention of the cervical cancer disease. Reasons for non-use of the available Pap smear services are not well understood. Beliefs about cancer may influence participation in cancer screening in these women. The purpose of this study was to develop an instrument to measure beliefs about cervical cancer and Pap smear screening among Black women in Botswana, and evaluate the psychometric properties of the instrument. Significance: Instruments that are designed to measure beliefs about cervical cancer and screening among black women in Botswana, as well as in the surrounding region, are presently not available. Valid and reliable instruments are needed for exploration of the women’s beliefs about cervical cancer. Conceptual Framework: The Health Belief Model (HBM) provided a conceptual framework for the study. Methodology: The study was done in four phases: Phase 1: item generation: 15 items were generated from literature review and qualitative data for each of four conceptually defined HBM constructs: Perceived susceptibility, severity, benefits, and barriers (Version 1). Phase 2: content validity: Four experts who were advanced practice nurses of African descent and were familiar with the content and the HBM evaluated the content. Experts rated the items on a 4-point Likert scale ranging from: 1=not relevant, 2=somewhat relevant, 3=relevant and 4=very relevant. Fifty-five items were retained for instrument development: perceived susceptibility - 11, severity - 14, benefits - 15 and barriers - 15, all measuring on a 4-point Likert scale ranging from strongly disagree (1) to strongly agree (4). (Version 2). Phase 3: pilot testing: The instrument was pilot tested on a convenient sample of 30 women in Botswana and revised as needed. Phase 4: reliability: the revised instrument (Version 3) was submitted to a larger sample of women in Botswana (n=300) for reliability testing. The sample included women who were Batswana by birth and decent, were aged 30 years and above and could complete an English questionnaire. Data were collected with the assistance of trained research assistants. Major findings: confirmatory factor analysis of the 55 items found that a number of items did not adequately load in a four-factor solution. Items that exhibited reasonable reliability and had low frequency of missing values (n=36) were retained: perceived barriers (14 items), perceived benefits (8 items), perceived severity (4 items), and perceived susceptibility (10 items). confirmatory factor analysis (principle components) for a four factor solution using varimax rotation demonstrated that these four factors explained 43% of the variation in these 36 items. Conclusion: reliability analysis using Cronbach’s Alpha gave generally satisfactory results with values from 0.53 to 0.89.

Keywords: cervical cancer, factor analysis, psychometric evaluation, varimax rotation

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Authors: Noorizal Huang, Christian Girsang, Mohamad Razi Mansoor

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Shallow gas seepage was first spotted at a central processing platform offshore Malaysia in 2010, acknowledged as Platform T in this paper. Frequent monitoring of the gas seepage was performed through remotely operated vehicle (ROV) baseline survey and a comprehensive geophysical survey was conducted to understand the characteristics of the gas seepage and to ensure that the integrity of the foundation at Platform T was not compromised. The origin of the gas back then was unknown. A soil investigation campaign was performed in 2016 to study the origin of the gas seepage. Two boreholes were drilled; a composite borehole to 150m below seabed for the purpose of soil sampling and in-situ testing and a pilot hole to 155m below the seabed, which was later converted to a fit-for-purpose relief well as an alternate migration path for the gas. During the soil investigation campaign, dissipation tests were performed at several layers which were potentially the source or migration path for the gas. Five (5) soil samples were segregated for headspace test, to identify the gas type which subsequently can be used to identify the origin of the gas. Dissipation tests performed at four depth intervals indicates pore water pressure less than 20 % of the effective vertical stress and appear to continue decreasing if the test had not been stopped. It was concluded that a low to a negligible amount of excess pore pressure exist in clayey silt layers. Results from headspace test show presence of methane corresponding to the clayey silt layers as reported in the boring logs. The gas most likely comes from biogenic sources, feeding on organic matter in situ over a large depth range. It is unlikely that there are large pockets of gas in the soil due to its homogeneous clayey nature and the lack of excess pore pressure in other permeable clayey silt layers encountered. Instead, it is more likely that when pore water at certain depth encounters a more permeable path, such as a borehole, it rises up through this path due to the temperature gradient in the soil. As the water rises the pressure decreases, which could cause gases dissolved in the water to come out of solution and form bubbles. As a result, the gas will have no impact on the integrity of the foundation at Platform T. The fit-for-purpose relief well design as well as adopting headspace testing can be used to address the shallow gas issue at Platform T in a cost effective and efficient manners.

Keywords: dissipation test, headspace test, excess pore pressure, relief well, shallow gas

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Authors: Muna Shalan

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Climate change is a systemic challenge for cities, with its impacts not happening in isolation but rather intertwined, thus increasing hazards and the vulnerability of the exposed population. The increase in the frequency and intensity of heat waves, for example, is associated with multiple repercussions on the quality of life of city inhabitants, including health discomfort, a rise in mortality and morbidity, increasing energy demand for cooling, and shrinking of green areas due to drought. To address the multi-faceted impact of urbanisation-induced warming, municipalities and local governments are challenged with devising strategies and implementing effective response measures. Municipalities are recognising the importance of guiding urban concepts to drive climate action in the urban environment. An example is climate proofing, which refers to a process of mainstreaming climate change into development strategies and programs, i.e., urban planning is viewed through a climate change lens. There is a multitude of interconnected aspects that are critical to paving the path toward climate-proofing of urban areas and avoiding poor planning of layouts and spatial arrangements. Navigating these aspects through an analysis of the overarching practices governing municipal planning processes, which is the focus of this research, will highlight entry points to improve procedures, methods, and data availability for optimising planning processes and municipal actions. By employing a case study approach, the research investigates how municipalities in different contexts, namely in the city of Sahab in Jordan, Chililabombwe in Zambia, and the city of Dortmund in Germany, are integrating guiding urban concepts to shrink the deficit in adaptation and mitigation and achieve climate proofing goals in their respective local contexts. The analysis revealed municipal strategies and measures undertaken to optimize existing building and urban design regulations by introducing key performance indicators and improving in-house capacity. Furthermore, the analysis revealed that establishing or optimising interdepartmental communication frameworks or platforms is key to strengthening the steering structures governing local climate action. The most common challenge faced by municipalities is related to their role as a regulator and implementers, particularly in budget analysis and instruments for cost recovery of climate action measures. By leading organisational changes related to improving procedures and methods, municipalities can mitigate the various challenges that may emanate from uncoordinated planning and thus promote action against urbanisation-induced warming.

Keywords: urbanisation-induced warming, response measures, municipal planning processes, key performance indicators, interdepartmental communication frameworks, cost recovery

Procedia PDF Downloads 50

Authors: Dipak Subedi, Anil Giri, Christine Whitt, Tia McDonald

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This study aims to understand the impact of the pandemic on the overall economic well-being of the agricultural sector of the United States. The two key metrics used to examine the economic well-being are the bankruptcy rate of the U.S. farm operations and the operating profit margin. One of the primary reasons for farm operations (in the U.S.) to file for bankruptcy is continuous negative profit or a significant decrease in profit. The pandemic caused significant supply and demand shocks in the domestic market. Furthermore, the ongoing trade disruptions, especially with China, also impacted the prices of agricultural commodities. The significantly reduced demand for ethanol and closure of meat processing plants affected both livestock and crop producers. This study uses data from courts to examine the bankruptcy rate over time of U.S. farm operations. Preliminary results suggest there wasn’t an increase in farm operations filing for bankruptcy in 2020. This was most likely because of record high Government payments to producers in 2020. The Federal Government made direct payments of more than $45 billion in 2020. One commonly used economic metric to measure farm profitability is the operating profit margin (OPM). Operating profit margin measures profitability as a share of the total value of production and government payments. The Economic Research Service of the United States Department of Agriculture defines a farm operation to be in a) a high-risk zone if the OPM is less than 10 percent and b) a low-risk zone if the OPM is higher than 25 percent. For this study, OPM was calculated for small, medium, and large-scale farm operations using the data from the Agriculture Resource Management Survey (OPM). Results show that except for small family farms, the share of farms in high-risk zone decreased in 2020 compared to the most recent non-pandemic year, 2019. This was most likely due to higher commodity prices at the end of 2020 and record-high government payments. Further investigation suggests a lower share of smaller farm operations receiving lower average government payments resulting in a large share (over 70 percent) being in the critical zone. This study should be of interest to multiple stakeholders, including policymakers across the globe, as it shows the resilience of the U.S. agricultural system as well as (some) impact of government payments.

Keywords: U.S. farm sector, COVID-19, operating profit margin, farm bankruptcy, ag finance, government payments to the farm sector

Procedia PDF Downloads 69

Authors: Tso Sheng-Yang, Wang Tien-Ni

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Introduction and Purpose: Previous researchers have documented children with ASD (Autism Spectrum Disorders) prefer to escaping internal privates and external privates when they face tough conditions they can’t control or they don’t like.Especially, when children with ASD need to learn challenging tasks, such us Chinese language, their inappropriate behaviors will occur apparently. Recently, researchers apply positive behavior support strategies for children with ASD to enhance their self-efficacy and therefore to reduce their adverse behaviors. Thus, the purpose of this research was to design a series of lecture based on art therapy and to evaluate its effectiveness on the child’s self-efficacy. Method: This research was the single-case design study that recruited a high school boy with ASD. Whole research can be separated into three conditions. First, baseline condition, before the class started and ended, the researcher collected participant’s competencies of self-efficacy every session. In intervention condition, the research used dramatic conventions to teach the child in Chinese language twice a week.When the data was stable across three documents, the period entered to the maintenance condition. In maintenance condition, the researcher only collected the score of self-efficacynot to do other interventions five times a month to represent the effectiveness of maintenance.The time and frequency of data collection among three conditions are identical. Concerning art therapy, the common approach, e.g., music, drama, or painting is to use art medium as independent variable. Due to visual cues of art medium, the ASD can be easily to gain joint attention with teachers. Besides, the ASD have difficulties in understanding abstract objectives Thus, using the drama convention is helpful for the ASD to construct the environment and understand the context of Classical Chinese. By real operation, it can improve the ASD to understand the context and construct prior knowledge. Result: Bassd on the 10-points Likert scale and research, we product following results. (a) In baseline condition, the average score of self-efficacyis 1.12 points, rangedfrom 1 to 2 points, and the level change is 0 point. (b)In intervention condition, the average score of self-efficacy is 7.66 points rangedfrom 7 to 9 points, and the level change is 1 point. (c)In maintenance condition, the average score of self-efficacy is 6.66 points rangedfrom 6 to 7 points, and the level change is 1 point. Concerning immediacy of change, between baseline and intervention conditions, the difference is 5 points. No overlaps were found between these two conditions. Conclusion: According to the result, we find that it is effective that using dramatic conventions a s teaching strategies to teach children with ASD. The result presents the score of self-efficacyimmediately enhances when the dramatic conventions commences. Thus, we suggest the teacher can use this approach and adjust, based on the student’s trait, to teach the ASD on difficult task.

Keywords: dramatic conventions, autism spectrum disorder, slef-efficacy, teaching strategy

Procedia PDF Downloads 66

Authors: Marsha D. Loda

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College enrollment is declining and generation Z, today’s college students, are struggling. Before the pandemic, researchers characterized this generational cohort as unique. Gen Z has been called the most achievement-oriented generation, as they enjoy greater economic status, are more racially and ethnically diverse, and better educated than any other generation. However, they are also the most likely generation to suffer from depression and anxiety. Gen Z has grown up largely with usually well-intentioned but overprotective parents who inadvertently kept them from learning life skills, likely impacting their ability to cope with and to effectively manage challenges. The unprecedented challenges resulting from the pandemic up ended their world and left them emotionally reeling. One of the ramifications of this for higher education is how to reengage current Gen Z students in the classroom. This research presents qualitative findings from 24 single-spaced pages of verbatim comments from college students. Research questions concerned what helps them learn and what they abhor, as well as how to engage them with the university outside of the classroom to aid in retention. Students leave little doubt about what they want to experience in the classroom. In order of mention, students want discussion, to engage with questions, to hear how a topic relates to real life and the real world, to feel connections with the professor and fellow students, and to have an opportunity to give their opinions. They prefer a classroom that involves conversation, with interesting topics and active learning. “professor talks instead of lecturing” “professor builds a connection with the classroom” “I am engaged because it feels like a respectful conversation” Similarly, students are direct about what they dislike in a classroom. In order of frequency, students dislike teachers unenthusiastically reading word or word from notes or presentations, repeating the text without adding examples, or addressing how to apply the information. “All lecture. I can read the book myself” “Not taught how to apply the skill or lesson” “Lectures the entire time. Lesson goes in one ear and out the other.” Pertaining to engagement outside the classroom, Gen Z challenges higher education to step outside the box. They don’t want to just hear from professionals in their field, they want to meet and interact with them. Perhaps because of their dependence on technology and pandemic isolation, they seem to reach out for assistance in forming social bonds. “I believe fun and social events are the best way to connect with students and get them involved. Cookouts, raffles, socials, or networking events would all most likely appeal to many students”. “Events… even if they aren’t directly related to learning. Maybe like movie nights… doing meet ups at restaurants”. Qualitative research suggests strategy. This research is rife with strategic implications to improve learning, increase engagement and reduce drop-out rates among Generation Z higher education students. It also compliments existing research on student engagement. With college enrollment declining by some 1.3 million students over the last two years, this research is both timely and important.

Keywords: college enrollment, generation Z, higher education, pandemic, student engagement

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Authors: Ayoola Adekunle Dada, Tolulope Omolola Fateropa

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There is no gain saying the fact that the Nigerian correctional services lack rehabilitation reformation. Owing to this, some so many inmates, including the female, become more emotionally bruised and hardened instead of coming out of the prison reformed. Although female inmates constitute only a small percentage worldwide, the challenges resulting from women falling under the provision of the penal system have prompted ficial and humanitarian bodies to consider female inmateas as vulnerable persons who need particular social work measures that meet their specific needs. Female inmates’condition may become worseinprisondue to the absence of the standard living condition. A survey of 100 female inmates will be used to determine the assessment of the living condition of the female inmates within the contexts in which they occur. Employing field methods from Medical Sociology and Law, the study seeks to make use of the collaboration of both disciplines for a comprehensive understanding of the scenario. Its specific objectives encompassed: (1) To examine access and use of health facilities among the female inmates;(2) To examine the effect of officers/warders attitude towards female inmates;(3)To investigate the perception of the female inmates towards the housing facilities in the centre and; (4) To investigate the feeding habit of the female inmates. Due to the exploratory nature of the study, the researchers will make use of mixed-method, such qualitative methods as interviews will be undertaken to complement survey research (quantitative). By adopting the above-explained inter-method triangulation, the study will not only ensure that the advantages of both methods are exploited but will also fulfil the basic purposes of research. The sampling for this study will be purposive. The study aims at sampling two correctional centres (Ado Ekiti and Akure) in order to generate representative data for the female inmates in South West Nigeria. In all, the total number of respondents will be 100. A cross-section of female inmates will be selected as respondents using a multi-stage sampling technique. 100 questionnaires will be administered. A semi structured (in-depth) interviews will be conducted among workers in the two selected correctional centres, respectively, to gain further insight on the living conditions of female inmates, which the survey may not readily elicit. These participants will be selected purposively in respect to their status in the organisation. Ethical issues in research on human subjects will be given due consideration. Such issues rest on principles of beneficence, non-maleficence, autonomy/justice and confidentiality. In the final analysis, qualitative data will be analyzed using manual content analysis. Both the descriptive and inferential statistics will be used for analytical purposes. Frequency, simple percentage, pie chart, bar chart, curve and cross-tabulations will form part of the descriptive analysis.

Keywords: assessment, health facilities, inmates, perception, living conditions

Procedia PDF Downloads 74

Authors: Maria Fonseca, Ana Branco, Joao Graca, Rui Mendes, Pedro Mimoso

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The present work is focused on the production of a carbon composite element for cycling through different techniques, namely, blow-molding and high-pressure resin transfer injection (HP-RTM). The main objective of this work is to compare both processes to produce carbon composite elements for the cycling industry. It is well known that the carbon composite components for cycling are produced mainly through blow-molding; however, this technique depends strongly on manual labour, resulting in a time-consuming production process. Comparatively, HP-RTM offers a more automated process which should lead to higher production rates. Nevertheless, a comparison of the elements produced through both techniques must be done, in order to assess if the final products comply with the required standards of the industry. The main difference between said techniques lies in the used material. Blow-moulding uses carbon prepreg (carbon fibres pre-impregnated with a resin system), and the material is laid up by hand, piece by piece, on a mould or on a hard male. After that, the material is cured at a high temperature. On the other hand, in the HP-RTM technique, dry carbon fibres are placed on a mould, and then resin is injected at high pressure. After some research regarding the best material systems (prepregs and braids) and suppliers, an element was designed (similar to a handlebar) to be constructed. The next step was to perform FEM simulations in order to determine what the best layup of the composite material was. The simulations were done for the prepreg material, and the obtained layup was transposed to the braids. The selected material was a prepreg with T700 carbon fibre (24K) and an epoxy resin system, for the blow-molding technique. For HP-RTM, carbon fibre elastic UD tubes and ± 45º braids were used, with both 3K and 6K filaments per tow, and the resin system was an epoxy as well. After the simulations for the prepreg material, the optimized layup was: [45°, -45°,45°, -45°,0°,0°]. For HP-RTM, the transposed layup was [ ± 45° (6k); 0° (6k); partial ± 45° (6k); partial ± 45° (6k); ± 45° (3k); ± 45° (3k)]. The mechanical tests showed that both elements can withstand the maximum load (in this case, 1000 N); however, the one produced through blow-molding can support higher loads (≈1300N against 1100N from HP-RTM). In what concerns to the fibre volume fraction (FVF), the HP-RTM element has a slightly higher value ( > 61% compared to 59% of the blow-molding technique). The optical microscopy has shown that both elements have a low void content. In conclusion, the elements produced using HP-RTM can compare to the ones produced through blow-molding, both in mechanical testing and in the visual aspect. Nevertheless, there is still space for improvement in the HP-RTM elements since the layup of the braids, and UD tubes could be optimized.

Keywords: HP-RTM, carbon composites, cycling, FEM

Procedia PDF Downloads 112

Authors: Yi-Tung Lin

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Researchers commonly assess implicit self-esteem with the Implicit Association Test (IAT). The IAT’s measure, often referred to as the IAT effect, indicates the strengths of automatic preferences for the self relative to others, which is often considered an index of implicit self-esteem. However, based on the Dual-process theory, the IAT does not rely entirely on the automatic process; it is also influenced by a controlled process. The present study, therefore, analyzed the IAT data with the Quad model, separating four processes on the IAT performance: the likelihood that automatic association is activated by the stimulus in the trial (AC); that a correct response is discriminated in the trial (D); that the automatic bias is overcome in favor of a deliberate response (OB); and that when the association is not activated, and the individual fails to discriminate a correct answer, there is a guessing or response bias drives the response (G). The AC and G processes are automatic, while the D and OB processes are controlled. The AC parameter is considered as the strength of the association activated by the stimulus, which reflects what implicit measures of social cognition aim to assess. The stronger the automatic association between self and positive valence, the more likely it will be activated by a relevant stimulus. Therefore, the AC parameter was used as the index of implicit self-esteem in the present study. Meanwhile, the relationship between implicit self-esteem and depression is not fully investigated. In the cognitive theory of depression, it is assumed that the negative self-schema is crucial in depression. Based on this point of view, implicit self-esteem would be negatively associated with depression. However, the results among empirical studies are inconsistent. The aims of the present study were to examine the psychometric properties of the AC (i.e., test-retest reliability and its correlations with explicit self-esteem and depression) and compare it with that of the IAT effect. The present study had 105 patients with depressive disorders completing the Rosenberg Self-Esteem Scale, Beck Depression Inventory-II and the IAT on the pretest. After at least 3 weeks, the participants completed the second IAT. The data were analyzed by the latent-trait multinomial processing tree model (latent-trait MPT) with the TreeBUGS package in R. The result showed that the latent-trait MPT had a satisfactory model fit. The effect size of test-retest reliability of the AC and the IAT effect were medium (r = .43, p < .0001) and small (r = .29, p < .01) respectively. Only the AC showed a significant correlation with explicit self-esteem (r = .19, p < .05). Neither of the two indexes was correlated with depression. Collectively, the AC parameter was a satisfactory index of implicit self-esteem compared with the IAT effect. Also, the present study supported the results that implicit self-esteem was not correlated with depression.

Keywords: cognitive modeling, implicit association test, implicit self-esteem, quad model

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

Procedia PDF Downloads 272

Authors: Imran Aziz Tunio

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Islamkot is an underdeveloped sub-district (Taluka) in the Tharparkar district Sindh province of Pakistan located between latitude 24°25'19.79"N to 24°47'59.92"N and longitude 70° 1'13.95"E to 70°32'15.11"E. The Islamkot has an arid desert climate and the region is generally devoid of perennial rivers, canals, and streams. It is highly dependent on rainfall which is not considered a reliable surface water source and groundwater is the only key source of water for many centuries. To assess groundwater’s potential, an electrical resistivity survey (ERS) was conducted in Islamkot Taluka. Groundwater investigations for 128 Vertical Electrical Sounding (VES) were collected to determine the groundwater potential and obtain qualitatively and quantitatively layered resistivity parameters. The PASI Model 16 GL-N Resistivity Meter was used by employing a Schlumberger electrode configuration, with half current electrode spacing (AB/2) ranging from 1.5 to 100 m and the potential electrode spacing (MN/2) from 0.5 to 10 m. The data was acquired with a maximum current electrode spacing of 200 m. The data processing for the delineation of dune sand aquifers involved the technique of data inversion, and the interpretation of the inversion results was aided by the use of forward modeling. The measured geo-electrical parameters were examined by Interpex IX1D software, and apparent resistivity curves and synthetic model layered parameters were mapped in the ArcGIS environment using the inverse Distance Weighting (IDW) interpolation technique. Qualitative interpretation of vertical electrical sounding (VES) data shows the number of geo-electrical layers in the area varies from three to four with different resistivity values detected. Out of 128 VES model curves, 42 nos. are 3 layered, and 86 nos. are 4 layered. The resistivity of the first subsurface layers (Loose surface sand) varied from 16.13 Ωm to 3353.3 Ωm and thickness varied from 0.046 m to 17.52m. The resistivity of the second subsurface layer (Semi-consolidated sand) varied from 1.10 Ωm to 7442.8 Ωm and thickness varied from 0.30 m to 56.27 m. The resistivity of the third subsurface layer (Consolidated sand) varied from 0.00001 Ωm to 3190.8 Ωm and thickness varied from 3.26 m to 86.66 m. The resistivity of the fourth subsurface layer (Silt and Clay) varied from 0.0013 Ωm to 16264 Ωm and thickness varied from 13.50 m to 87.68 m. The Dar Zarrouk parameters, i.e. longitudinal unit conductance S is from 0.00024 to 19.91 mho; transverse unit resistance T from 7.34 to 40080.63 Ωm2; longitudinal resistance RS is from 1.22 to 3137.10 Ωm and transverse resistivity RT from 5.84 to 3138.54 Ωm. ERS data and Dar Zarrouk parameters were mapped which revealed that the study area has groundwater potential in the subsurface.

Keywords: electrical resistivity survey, GIS & RS, groundwater potential, environmental assessment, VES

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Authors: Devon Simpson

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Recycled Manure Solids (RMS), attained via centrifugation from Canadian dairy farms, were synthesized into a non-polluting fertilizer by bonding micronutrients (Fe, Zn, and Mn) to cellulose fibers and then assessed for the effectiveness of nutrient recovery in tomatoes. Manure management technology is critical for improving the sustainability of agroecosystems and has the capacity to offer a truly circular economy. The ability to add value to manure byproducts offers an opportunity for economic benefits while generating tenable solutions to livestock waste. The dairy industry is under increasing pressure from new environmental protections such as government restrictions on manure applications, limitations on herd size as well as increased product demand from a growing population. Current systems use RMS as bedding, so there is a lack of data pertaining to RMS use as a fertilizer. This is because of nutrient distribution, where most nutrients are retained in the liquid effluent of the solid-liquid separation. A literature review on the physical and chemical properties of dairy manure further revealed more data for raw manure than centrifuged solids. This research offers an innovative perspective and a new avenue of exploration in the use of RMS. Manure solids in this study were obtained directly from dairy farms in Salmon Arm and Abbotsford, British Columbia, and underwent physical, chemical, and biological characterizations pre- and post-synthesis processing. Samples were sent to A&L labs Canada for analysis. Once characterized and bonded to micronutrients, the effect of synthesized RMS on nutrient recovery in tomatoes was studied in a greenhouse environment. The agricultural research package ‘agricolae’ for R was used for experimental design and data analysis. The growth trials consisted of a randomized complete block design (RCBD) that allowed for analysis of variance (ANOVA). The primary outcome was to measure nutrient uptake, and this was done using an Inductively Coupled Plasma Mass Spectrometer (IC-PMS) to analyze the micronutrient content of both the tissue and fruit of the tomatoes. It was found that treatments containing bonded dairy manure solids had an increased micronutrient concentration. Treatments with bonded dairy manure solids also saw an increase in yield, and a brix analysis showed higher sugar content than the untreated control and a grower standard.

Keywords: aoecosystems, dairy manure, micronutrient fertilizer, manure management, nutrient recovery, nutrient recycling, recycled manure solids, regenerative agricugrlture, sustainable farming

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Authors: Ahmad Abu-Akel, Emilie De Montpellier, Sophie Von Bentivegni, Lyn Luechinger, Alessandro Ishii, Christine Mohr

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Convergent and divergent thinking are two main components of creativity that have been viewed as complementary. While divergent thinking refers to the fluency and flexibility of generating new ideas, convergent thinking refers to the ability to systematically apply rules and knowledge to arrive at the optimal solution or idea. These creativity components have been shown to be susceptible to variation in subclinical expressions of autistic and schizotypal traits within the general population. Research, albeit inconclusively, mainly linked positive schizotypal traits with divergent thinking and autistic traits with convergent thinking. However, cumulative evidence suggests that these trait dimensions can co-occur in the same individual more than would be expected by chance and that their concurrent effect can be diametric and even interactive. The current study aimed at investigating the concurrent effect of these trait dimensions on tasks assessing convergent and divergent thinking abilities. We predicted that individuals with high positive schizotypal traits alone would perform particularly well on the divergent thinking task, whilst those with high autistic traits alone would perform particularly well on the convergent thinking task. Crucially, we also predicted that individuals who are high on both autistic and positive schizotypal traits would perform particularly well on both the divergent and convergent thinking tasks. This was investigated in a non-clinical sample of 142 individuals (Males = 45%; Mean age = 21.45, SD = 2.30), sufficient to minimally observe an effect size f² ≥ .10. Divergent thinking was evaluated using the Alternative Uses Task, and convergent thinking with the Anagrams Task. Autistic and schizotypal traits were respectively assessed with the Autism Quotient Questionnaire (AQ) and the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE). Regression analyses revealed that the positive association of autistic traits with convergent thinking scores was qualified with an interaction with positive schizotypal traits. Specifically, positive schizotypal traits were negatively associated with convergent thinking scores when AQ scores were relatively low, but this trend was reversed when AQ scores were high. Conversely, the positive effect of AQ scores on convergent thinking progressively increased with increasing positive schizotypal traits. The results of divergent thinking task are currently being analyzed and will be reported at the conference. The association of elevated autistic and positive schizotypal traits with convergent thinking may represent a unique profile of creative thinkers who are able to simultaneously draw on trait-specific advantages conferred by autistic and positively schizotypal traits such as local and global processing. This suggests that main-effect models can tell an incomplete story regarding the effect of autistic and positive schizotypal traits on creativity-related processes. Future creativity research should consider their interaction and the benefits conferred by their co-presence.

Keywords: autism, schizotypy, convergent thinking, divergent thinking, comorbidity

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Authors: S. Wiak, L. Szymanski, Z. Kolacinski, G. Raniszewski, L. Pietrzak, Z. Staniszewska

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The term ‘cancer’ is given to a collection of related diseases that may affect any part of the human body. It is a pathological behaviour of cells with the potential to undergo abnormal breakdown in the processes that control cell proliferation, differentiation, and death of particular cells. Although cancer is commonly considered as modern disease, there are beliefs that drastically growing number of new cases can be linked to the extensively prolonged life expectancy and enhanced techniques for cancer diagnosis. Magnetic hyperthermia therapy is a novel approach to cancer treatment, which may greatly contribute to higher efficiency of the therapy. Employing carbon nanotubes as nanocarriers for magnetic particles, it is possible to decrease toxicity and invasiveness of the treatment by surface functionalisation. Despite appearing in recent years, magnetic particle hyperthermia has already become of the highest interest in the scientific and medical environment. The reason why hyperthermia therapy brings so much hope for future treatment of cancer lays in the effect that it produces in malignant cells. Subjecting them to thermal shock results in activation of numerous degradation processes inside and outside the cell. The heating process initiates mechanisms of DNA destruction, protein denaturation and induction of cell apoptosis, which may lead to tumour shrinkage, and in some cases, it may even cause complete disappearance of cancer. The factors which have the major impact on the final efficiency of the treatment include temperatures generated inside the tissues, time of exposure to the heating process, and the character of an individual cancer cell type. The vast majority of cancer cells is characterised by lower pH, persistent hypoxia and lack of nutrients, which can be associated to abnormal microvasculature. Since in healthy tissues we cannot observe presence of these conditions, they should not be seriously affected by elevation of the temperature. The aim of this work is to investigate the influence of iron content in iron filled Carbon Nanotubes on the desired nanoparticles for cancer therapy. In the article, the development and demonstration of the method and the model device for hyperthermic selective destruction of cancer cells are presented. This method was based on the synthesis and functionalization of carbon nanotubes serving as ferromagnetic material nanocontainers. The methodology of the production carbon- ferromagnetic nanocontainers (FNCs) includes the synthesis of carbon nanotubes, chemical, and physical characterization, increasing the content of a ferromagnetic material and biochemical functionalization involving the attachment of the key addresses. The ferromagnetic nanocontainers were synthesised in CVD and microwave plasma system. The research work has been financed from the budget of science as a research project No. PBS2/A5/31/2013.

Keywords: hyperthermia, carbon nanotubes, cancer colon cells, radio frequency field

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Authors: Viktor D. Dubrovin, Masoud Mollaee, Jie Zong, Xiushan Zhu, Nasser Peyghambarian

Abstract:

Glasses doped with high rare-earth (RE) elements concentration attracted considerable attention since the middle of the 20th century due to their particular magneto-optical properties. Such glasses exhibit the Faraday effect in which the polarization plane of a linearly polarized light beam is rotated by the interaction between the incident light and the magneto-optical material. That effect found application in optical isolators that are useful for laser systems, which can prevent back reflection of light into lasers or optical amplifiers and reduce signal instability and noise. Glasses are of particular interest since they are cost-effective and can be formed into fibers, thus breaking the limits of traditional bulk optics requiring optical coupling for use with fiber-optic systems. The advent of high-power fiber lasers operating near 2µm revealed a necessity in the development of all fiber isolators for this region. Ce³⁺, Pr³⁺, Dy³⁺, and Tb³⁺ ions provide the biggest contribution to the Verdet constant value of optical materials among the RE. It is known that Pr³⁺ and Tb³⁺ ions have strong absorption bands near 2 µm, thus making Dy³⁺ and Ce³⁺ the only prospective candidates for fiber isolator operating in that region. Due to the high tendency of Ce³⁺ ions pass to Ce⁴⁺ during the synthesis, glasses with high cerium content usually suffers from Ce⁴⁺ ions absorption extending from visible to IR. Additionally, Dy³⁺ (₆H¹⁵/²) same as Ho³⁺ (⁵I₈) ions, have the largest effective magnetic moment (µeff = 10.6 µB) among the RE ions that starts to play the key role if the operating region is far from 4fⁿ→ 4fⁿ⁻¹5 d¹ electric-dipole transition relevant to the Faraday Effect. Considering the high effective magnetic moment value of Er³⁺ ions (µeff = 9.6 µB) that is 3rd after Dy³⁺/ Ho³⁺ and Tb³⁺, it is possible to assume that Er³⁺ doped glasses should exhibit Verdet constant value near 2µm that is comparable with one of Dy doped glasses. Thus, partial replacement of Dy³⁺ on Er³⁺ ions has been performed, keeping the overall concentration of Re₂O₃ equal to 70 wt.% (30.6 mol.%). Al₂O₃-B₂O₃-SiO₂-30.6RE₂O₃ (RE= Er, Dy) glasses had been synthesized, and their thermal, spectral, optical, structural, and magneto-optical properties had been studied. Glasses synthesis had been conducted in Pt crucibles for 3h at 1500 °C. The obtained melt was poured into preheated up to 400 °C mold and annealed from 800 oC to room temperature for 12h with 1h dwell. The mass of obtained glass samples was about 200g. Shown that the difference between crystallization and glass transition temperature is about 150 oC, even taking into account the fact that high content of RE₂O₃ leads to glass network depolymerization. Verdet constant of Al₂O₃-B₂O₃-SiO₂-30.6RE₂O₃ glasses for wavelength 1950 nm can reach more than 5.9 rad/(T*m), which is among the highest number reported for a paramagnetic glass at this wavelength. The refractive index value was found to be equal to 1.7545 at 633 nm. Our experimental results show that Al₂O₃-B₂O₃-SiO₂-30.6RE₂O₃ glasses with high Dy₂O₃ content are expected to be promising material for use as highly effective Faraday isolators and modulators of electromagnetic radiation in the 2μm region.

Keywords: oxide glass, magneto-optical, dysprosium, erbium, Faraday rotator, boron-aluminosilicate system

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Authors: Nawras Kurzom, Avi Mendelsohn

Abstract:

The effects of background music on learning and memory are inconsistent, partly due to the intrinsic complexity and variety of music and partly to individual differences in music perception and preference. A prominent musical feature that is known to elicit strong emotional responses is musical tension. Musical tension can be brought about by building anticipation of rhythm, harmony, melody, and dynamics. Delaying the resolution of dominant-to-tonic chord progressions, as well as using dissonant harmonics, can elicit feelings of tension, which can, in turn, affect memory formation of concomitant information. The aim of the presented studies was to explore how forming declarative memory is influenced by musical tension, brought about within continuous music as well as in the form of isolated chords with varying degrees of dissonance/consonance. The effects of musical tension on long-term memory of declarative information were studied in two ways: 1) by evoking tension within continuous music pieces by delaying the release of harmonic progressions from dominant to tonic chords, and 2) by using isolated single complex chords with various degrees of dissonance/roughness. Musical tension was validated through subjective reports of tension, as well as physiological measurements of skin conductance response (SCR) and pupil dilation responses to the chords. In addition, music information retrieval (MIR) was used to quantify musical properties associated with tension and its release. Each experiment included an encoding phase, wherein individuals studied stimuli (words or images) with different musical conditions. Memory for the studied stimuli was tested 24 hours later via recognition tasks. In three separate experiments, we found positive relationships between tension perception and physiological measurements of SCR and pupil dilation. As for memory performance, we found that background music, in general, led to superior memory performance as compared to silence. We detected a trade-off effect between tension perception and memory, such that individuals who perceived musical tension as such displayed reduced memory performance for images encoded during musical tension, whereas tense music benefited memory for those who were less sensitive to the perception of musical tension. Musical tension exerts complex interactions with perception, emotional responses, and cognitive performance on individuals with and without musical training. Delineating the conditions and mechanisms that underlie the interactions between musical tension and memory can benefit our understanding of musical perception at large and the diverse effects that music has on ongoing processing of declarative information.

Keywords: musical tension, declarative memory, learning and memory, musical perception

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Authors: Yi Li, Rui Lu, Lianjun Wang

Abstract:

With the rapid development of chemical industry, the consumption of volatile organic compounds (VOCs) has increased extensively. In the process of VOCs production and application, plenty of them have been transferred to environment. As a result, it has led to pollution problems not only in soil and ground water but also to human beings. Thus, it is important to develop a sensitive and cost-effective analytical method for trace VOCs detection in environment. Surface-enhanced Raman Spectroscopy (SERS), as one of the most sensitive optical analytical technique with rapid response, pinpoint accuracy and noninvasive detection, has been widely used for ultratrace analysis. Based on the plasmon resonance on the nanoscale metallic surface, SERS technology can even detect single molecule due to abundant nanogaps (i.e. 'hot spots') on the nanosubstrate. In this work, a self-supported flexible silver nitrate (AgNO3)/ethylene-propylene copolymer (EPM) hybrid nanofibers was fabricated by electrospinning. After an in-situ chemical reduction using ice-cold sodium borohydride as reduction agent, numerous silver nanoparticles were formed on the nanofiber surface. By adjusting the reduction time and AgNO3 content, the morphology and dimension of silver nanoparticles could be controlled. According to the principles of solid-phase extraction, the hydrophobic substance is more likely to partition into the hydrophobic EPM membrane in an aqueous environment while water and other polar components are excluded from the analytes. By the enrichment of EPM fibers, the number of hydrophobic molecules located on the 'hot spots' generated from criss-crossed nanofibers is greatly increased, which further enhances SERS signal intensity. The as-prepared Ag/EPM hybrid nanofibers were first employed to detect common SERS probe molecule (p-aminothiophenol) with the detection limit down to 10-12 M, which demonstrated an excellent SERS performance. To further study the application of the fabricated substrate for monitoring hydrophobic substance in water, several typical VOCs, such as benzene, toluene and p-xylene, were selected as model compounds. The results showed that the characteristic peaks of these target analytes in the mixed aqueous solution could be distinguished even at a concentration of 10-6 M after multi-peaks gaussian fitting process, including C-H bending (850 cm-1), C-C ring stretching (1581 cm-1, 1600 cm-1) of benzene, C-H bending (844 cm-1 ,1151 cm-1), C-C ring stretching (1001 cm-1), CH3 bending vibration (1377 cm-1) of toluene, C-H bending (829 cm-1), C-C stretching (1614 cm-1) of p-xylene. The SERS substrate has remarkable advantages which combine the enrichment capacity from EPM and the Raman enhancement of Ag nanoparticles. Meanwhile, the huge specific surface area resulted from electrospinning is benificial to increase the number of adsoption sites and promotes 'hot spots' formation. In summary, this work provides powerful potential in rapid, on-site and accurate detection of trace VOCs using a portable Raman.

Keywords: electrospinning, ethylene-propylene copolymer, silver nanoparticles, SERS, VOCs

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Authors: Justo Rodriguez, Daming Chen, Amador M. Guzman

Abstract:

The detection, treatment, and control of rapidly propagating, deadly viruses such as COVID-19, require the development of inexpensive, fast, and accurate devices to address the urgent needs of the population. Microfluidics-based sensors are amongst the different methods and techniques for detection that are easy to use. A micro analyzer is defined as a microfluidics-based sensor, composed of a network of microchannels with varying functions. Given their size, portability, and accuracy, they are proving to be more effective and convenient than other solutions. A micro analyzer based on the concept of “Lab on a Chip” presents advantages concerning other non-micro devices due to its smaller size, and it is having a better ratio between useful area and volume. The integration of multiple processes in a single microdevice reduces both the number of necessary samples and the analysis time, leading the next generation of analyzers for the health-sciences. In some applications, the flow of solution within the microchannels is originated by a pressure gradient, which can produce adverse effects on biological samples. A more efficient and less dangerous way of controlling the flow in a microchannel-based analyzer is applying an electric field to induce the fluid motion and either enhance or suppress the mixing process. Electrokinetic flows are characterized by no less than two non-dimensional parameters: the electric Rayleigh number and its geometrical aspect ratio. In this research, stable and unstable flows have been studied numerically (and when possible, will be experimental) in a T-shaped microchannel. Additionally, unstable electrokinetic flows for Rayleigh numbers higher than critical have been characterized. The flow mixing enhancement was quantified in relation to the stretching and folding that fluid particles undergo when they are subjected to supercritical electrokinetic flows. Computational simulations were carried out using a finite element-based program while working with the flow mixing concepts developed by Gollub and collaborators. Hundreds of seeded massless particles were tracked along the microchannel from the entrance to exit for both stable and unstable flows. After post-processing, their trajectories, the folding and stretching values for the different flows were found. Numerical results show that for supercritical electrokinetic flows, the enhancement effects of the folding and stretching processes become more apparent. Consequently, there is an improvement in the mixing process, ultimately leading to a more homogenous mixture.

Keywords: microchannel, stretching and folding, electro kinetic flow mixing, micro-analyzer

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