Search results for: shape curves

Authors: Ali Aghahosseini Dehaghani

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Every year in this globalized world, thousands of migrants leave their countries hoping to find a better situation of life in other parts of the world. In this regard, many questions, from a human rights point of view, have been raised about how this phenomenon should be managed in the host countries. Although legal approaches such as legislation and litigation are inevitable in the way to respect the human rights of migrants, there is an increasing consensus about the fact that a strict juridical approach is inadequate to protect as well as to prevent violations of migrants’ rights. Indeed, given the multiplicity of factors that affect and shape the application of these rights and considering the fact that law is a social phenomenon, what is needed is an interdisciplinary approach, which combines both juridical approaches and perspectives from other disciplines. In this respect, a sociological approach is important because it shows the social processes through which human rights of migrants have been constructed or violated in particular social situations. Sociologists who study international migration ask the questions such as how many people migrate, who migrates, why people migrate, what happens to them once they arrive in the host country, how migration affects sending and receiving communities, the extent to which migrants help the economy, the effects of migration on crimes, and how migrants change the local communities. This paper is an attempt to show how sociology can promote human rights of migrants. To this end, the article first explores the usefulness and value of an interdisciplinary approach to realize how and to what extent sociology may improve and promote the human rights of migrants in the destination country. It then examines mechanisms which help to reach to a systematic integration of law and sociological discipline to advance migrants’ rights as well as to encourage legal scholars to consider the implications of societal structures in their works.

Keywords: human rights, migrants, sociological approach, interdisciplinary study

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Authors: Anissa Mary Thomas Thattil, Nancy Angeline Gnanaselvam, B. Ramakrishna Goud

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Faecal sludge management (FSM) is an unorganized sector, and in India, there is an absence of regulations regarding the collection, transport, treatment, and disposal of faecal sludge. FSM has a high degree of occupational hazards that need to be thoroughly understood in order to shape effective solutions. On-field observations of five FSM operations were conducted in Anekal Taluk of southern Karnataka. All five of the FSM operations were privately owned and snowball method of sampling was employed. Two types of FS operations observed were: mechanical emptying involving direct human contact with faecal sludge and mechanical emptying without direct human contact with faecal sludge. Each operation was manned by 3-4 faecal sludge operators (FSOs). None of the observed FSOs used personal protective equipment. According to the WHO semi-quantitative risk assessment, the very high risk occupational hazards identified were dermal contact with faecal sludge, inhalation of toxic gases, and social stigma. The high risk hazards identified were trips and falls, injuries, ergonomic hazards, substance abuse, and mental health problems. In all five FSM operations, the collected faecal sludge was discharged untreated onto abandoned land. FSM in India is fraught with occupational and environmental hazards which need to be urgently addressed. This includes formalizing the institution of FSM, contextualized behaviour change communication, capacity building of local bodies, awareness programmes among agriculturists and FSOs, and designation of sites for the safe harnessing of faecal sludge as soil nutrient.

Keywords: faecal sludge, faecal sludge management, FSM, occupational hazards, sanitation

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Authors: Omar Alhamd, Peter A. Thomas, Trevor J. Greenhough, Annette K. Shrive

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The Pseudomonas syringae species complex includes many plant pathogenic strains with highly specific interactions with varied host species and cultivars. The rapid spread of these bacteria over the last ten years has become a cause for concern. Nanoparticles have previously shown promise in microbiological action. We have therefore investigated in vitro and in vivo the effects of different types and sizes of nanoparticles in order to provide quantitative information about their effect on the bacteria. The effects of several different nanoparticles against several bacteria strains were investigated. The effect of NP on bacterial growth was studied by measuring the optical density, biochemical and nutritional tests, and transmission electron microscopy (TEM) to determine the shape and size of NP. Our results indicate that their effects varied, with either a negative or a positive impact on both bacterial and plant growth. Additionally, the methods of exposure to nanoparticles have a crucial role in accumulation, translocation, growth response and bacterial growth. The results of our studies on the behaviour and effects of nanoparticles in model plants showed. Cerium oxide (CeO₂) and silver (Ag) NP showed significant antibacterial activity against several pathogenic bacteria. It was found that titanium nanoparticles (TiO₂) can have either a negative or a positive impact, according to concentration and size. It is also thought that environmental conditions can have a major influence on bacterial growth. Studies were therefore also carried out under some environmental stress conditions to test bacterial survival and to assess bacterial virulence. All results will be presented including information about the effects of different nanoparticles on Pseudomonas syringae bacteria.

Keywords: plant microbiome, nanoparticles, 16S rRNA gene sequencing, bacterial survival

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Authors: Siriporn Okonogi, Pimpak Phumat, Sakornrat Khongkhunthian

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Piper betle has been extensively reported for various pharmacological effects including antimicrobial activity. 4-Allylpyrocatechol (AC) is a principle active compound found in P. betle. However, AC has a problem of solubility in water. The aims of the present study were to prepare AC loaded polymeric micelles for enhancing its water solubility and to evaluate its anti-biofilm activity against oral phathogenic bacteria. AC was loaded in polymeric micelles (PM) of Pluronic F127 by using thin film hydration method to obtain AC loaded PM (PMAC). The results revealed that AC in the form of PMAC possessed high water solubility. PMAC particles were characterized using a transmission electron microscope and photon correlation spectroscopy. Determination of entrapment efficiency (EE) and loading capacity (LC) of PMAC was done by using high-performance liquid chromatography. The highest EE (86.33 ± 14.27 %) and LC (19.25 ± 3.18 %) of PMAC were found when the weight ratio of polymer to AC was 4 to 1. At this ratio, the particles showed spherical in shape with the size of 38.83 ± 1.36 nm and polydispersity index of 0.28 ± 0.10. Zeta potential of the particles is negative with the value of 16.43 ± 0.55 mV. Crystal violet assay and confocal microscopy were applied to evaluate the effects of PMAC on Streptococcus mutans biofilms using chlorhexidine (CHX) as a positive control. PMAC contained 1.5 mg/mL AC could potentially inhibit (102.01 ± 9.18%) and significantly eradicate (85.05 ± 2.03 %) these biofilms (p < 0.05). Comparison with CHX, PMAC showed slightly similar biofilm inhibition but significantly stronger biofilm eradication (p < 0.05) than CHX. It is concluded that PMAC can enhance water solubility and anti-biofilm activity of AC.

Keywords: pluronic, polymeric micelles, solubility, 4-allylpyrocathecol, Streptococcus mutans, anti-biofilm

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Authors: Zohreh Soleimani, Sally Salome Shahzad, Stamatis Zoras

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As a result of current energy and environmental issues, the human body is known as one of the promising candidate for converting wasted heat to electricity (Seebeck effect). Thermoelectric generator (TEG) is one of the most prevalent means of harvesting body heat and converting that to eco-friendly electrical power. However, the uneven distribution of the body heat and its curvature geometry restrict harvesting adequate amount of energy. To perfectly transform the heat radiated by the body into power, the most direct solution is conforming the thermoelectric generators (TEG) with the arbitrary surface of the body and increase the temperature difference across the thermoelectric legs. Due to this, a computational survey through COMSOL Multiphysics is presented in this paper with the main focus on the impact of integrating a flexible wearable TEG with a corrugated shaped heat sink on the module power output. To eliminate external parameters (temperature, air flow, humidity), the simulations are conducted within indoor thermal level and when the wearer is stationary. The full thermoelectric characterization of the proposed TEG fabricated by a wavy shape heat sink has been computed leading to a maximum power output of 25µW/cm2 at a temperature gradient nearly 13°C. It is noteworthy that for the flexibility of the proposed TEG and heat sink, the applicability and efficiency of the module stay high even on the curved surfaces of the body. As a consequence, the results demonstrate the superiority of such a TEG to the most state of the art counterparts fabricated with no heat sink and offer a new train of thought for the development of self-sustained and unobtrusive wearable power suppliers which generate energy from low grade dissipated heat from the body.

Keywords: device simulation, flexible thermoelectric module, heat sink, human body heat

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Authors: R. Gounina-Allouane, N. Ouali, F. Z. Berrabah, A. Bentaleb

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For a long time, the Gram-positive spore-forming bacteria Bacillus thuringiensis (Bt) has been widely used in biological control against devastating and disease vectors insects. This is due to the insecticidal activity of its crystalline parasporal inclusion (crystals) predominantly comprised of one or more proteins (Cry and Cyt proteins) also called δ-endotoxins, produced during sporulation. The shape and composition of Bt crystals vary among strains and crystalline proteins are extremely varied (more than 475 cry gene were discovered). The insecticidal activity of Bt crystals is very well studied, thus their insecticidal mode of action is well established, however, their antimicrobial effect is largely unknown. The lack of data on the antimicrobial effect of crystalline proteins of Bt and the need for searching new antimicrobial molecules encouraged us to carried out this study. The antibacterial effect of δ-endotoxines produced by two Bt stains; a strain isolated from soil at northern of Algeria (Bt 7.2.B), and a strain isolated from a bioinsecticide (Bacillus thuringiensis var aizawai), activated by proteolysis, was assayed on clinical bacterial strains and ATCC collection ones respectively. Gram positive and negative clinical bacterial strains (Escherichia coli, Klebsiella pneumonaie, Pseudomonas aeruginosa, Staphylococcus aureus) were sensitive to activated Bt 72B endotoxins. Similarly, bacterial strains from ATCC collection (Escherichia coli ATCC 25922, Pseudomonas aerugenosa ATCC 27853, Staphylococcus aureus ATCC 25923) were sensitive to activated B. thuringiensis var aizawai δ-endotoxines. The activated δ-endotoxins were separated by SDS-PAGE.

Keywords: Bacillus thuringiensis, crystals, cry proteins, δ-endotoxins, antibacterial activity

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Authors: Jyh Sheen, Yong-Lin Wang

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This research dedicates to find a different measurement procedure of microwave dielectric properties of ceramic materials with high dielectric constants. For the composite of ceramic dispersed in the polymer matrix, the dielectric constants of the composites with different concentrations can be obtained by various mixture equations. The other development of mixture rule is to calculate the permittivity of ceramic from measurements on composite. To do this, the analysis method and theoretical accuracy on six basic mixture laws derived from three basic particle shapes of ceramic fillers have been reported for dielectric constants of ceramic less than 40 at microwave frequency. Similar researches have been done for other well-known mixture rules. They have shown that both the physical curve matching with experimental results and low potential theory error are important to promote the calculation accuracy. Recently, a modified of mixture equation for high dielectric constant ceramics at microwave frequency has also been presented for strontium titanate (SrTiO3) which was selected from five more well known mixing rules and has shown a good accuracy for high dielectric constant measurements. However, it is still not clear the accuracy of this modified equation for other high dielectric constant materials. Therefore, the five more well known mixing rules are selected again to understand their application to other high dielectric constant ceramics. The other high dielectric constant ceramic, TiO2 with dielectric constant 100, was then chosen for this research. Their theoretical error equations are derived. In addition to the theoretical research, experimental measurements are always required. Titanium dioxide is an interesting ceramic for microwave applications. In this research, its powder is adopted as the filler material and polyethylene powder is like the matrix material. The dielectric constants of those ceramic-polyethylene composites with various compositions were measured at 10 GHz. The theoretical curves of the five published mixture equations are shown together with the measured results to understand the curve matching condition of each rule. Finally, based on the experimental observation and theoretical analysis, one of the five rules was selected and modified to a new powder mixture equation. This modified rule has show very good curve matching with the measurement data and low theoretical error. We can then calculate the dielectric constant of pure filler medium (titanium dioxide) by those mixing equations from the measured dielectric constants of composites. The accuracy on the estimating dielectric constant of pure ceramic by various mixture rules will be compared. This modified mixture rule has also shown good measurement accuracy on the dielectric constant of titanium dioxide ceramic. This study can be applied to the microwave dielectric properties measurements of other high dielectric constant ceramic materials in the future.

Keywords: microwave measurement, dielectric constant, mixture rules, composites

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Authors: Sangwoo Oh, Jaewoo Kim, Dongmin Seo, Jaewon Park, Yongha Hwang, Sungkyu Seo

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Plasmonics has been regarded one of the most powerful bio-sensing modalities to evaluate bio-molecular interactions in real-time. However, most of the plasmonic sensing methods are based on labeling metallic nanoparticles, e.g. gold or silver, as optical modulation markers, which are non-recyclable and expensive. This plasmonic modulation can be usually achieved through various nano structures, e.g., nano-hole arrays. Among those structures, plasmonic lens has been regarded as a unique plasmonic structure due to its light focusing characteristics. In this study, we introduce a custom designed plasmonic lens array for bio-sensing, which was simulated by finite-difference-time-domain (FDTD) approach and fabricated by top-down approach. In our work, we performed the FDTD simulations of various plasmonic lens designs for bacteria sensor, i.e., Samonella and Hominis. We optimized the design parameters, i.e., radius, shape, and material, of the plasmonic lens. The simulation results showed the change in the peak intensity value with the introduction of each bacteria and antigen i.e., peak intensity 1.8711 a.u. with the introduction of antibody layer of thickness of 15nm. For Salmonella, the peak intensity changed from 1.8711 a.u. to 2.3654 a.u. and for Hominis, the peak intensity changed from 1.8711 a.u. to 3.2355 a.u. This significant shift in the intensity due to the interaction between bacteria and antigen showed a promising sensing capability of the plasmonic lens. With the batch processing and bulk production of this nano scale design, the cost of biological sensing can be significantly reduced, holding great promise in the fields of clinical diagnostics and bio-defense.

Keywords: plasmonic lens, FDTD, fabrication, bacteria sensor, salmonella, hominis

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

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The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

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Authors: Saqib Ali

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Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

Keywords: distributed generation, demand-side management, hybrid power system, micro grid, renewable energy resources, supply-side management

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Authors: Mehmet Demir Kaya, Engin Gökhan Kulan, Onur İleri, Süleyman Avcı

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Due to variation in seed size, shape and oil content of safflower cultivars, germination and emergence performance have been severely influenced by seed characteristics. This study aimed to determine genotypic variation among safflower genotypes for one thousand seed weight, oil content, germination and seed vigor using electrical conductivity (EC) and cold test. In the study, safflower lines ES37-5, ES38-4, ES43-11, ES55-14 and ES58-11 which were developed by single seed selection method, and Dinçer and Remzibey-05 were used as standard varieties. The genotypes were grown under rainfed conditions in Eskişehir, Turkey with four replications. The seeds of each genotype were subjected to standard germination and emergence test at 25°C for 10 days with four replications and 50 seeds per replicate. Electrical conductivity test was performed at 25°C for 24 h to assess the seed vigor. Also, cold test were applied to each safflower genotype at 10°C for 4 days and 25°C for 6 days. Results showed that oil content of the safflower genotypes were different. The highest oil content was determined in ES43-11 with 36.6% while the lowest was 25.9% in ES38-4. Higher germination and emergence rate were obtained from ES55-14 with 96.5% and 73.0%, respectively. There was no significant difference among the safflower genotypes for EC values. Cold test showed that ES43-11 and ES55-14 gave the maximum germination percentages. It was concluded that genotypic factors except for soil and climatic conditions play an important role for determining seed vigor because safflower genotypes grown at the same condition produced various seed vigor values.

Keywords: Carthamus tinctorius L., germination, emergence, cold test, electrical conductivity

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Authors: D. Shamatov

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Becoming a teacher is a journey with significant learning experiences. Exploring teachers’ lives and experiences can provide much-needed insights into the multiple realities of teaching. Teachers’ stories through qualitative narrative studies help understand and appreciate the complexities of the socio-political, economic and practical realities facing teachers. Events and experiences, both past and present, that take place at home, school, and in the broader social sphere help to shape these teachers’ lives and careers. Researchers and educators share the responsibility of listening to these teachers’ stories and life experiences and being sensitive to their voices in order to develop effective models for teacher development. A better understanding of how teachers learn to become teachers can help teacher educators prepare more effective teacher education programs. This paper is based on qualitative research which includes individual and focus group interviews, as well as auto-biography stories of Master of Science in School Leadership students at Graduate School of Education of Nazarbayev University. Twenty five MSc students from across Kazakhstan reflected on their professional journey and wrote their professional autobiographies as teachers. Their autobiographies capture the richness of their experiences and beliefs as a teacher, but also serve as window to understand broader socio-economic and political contexts where these teachers live and work. The study also provides an understanding of the systemic and socio-economic challenges of teachers in the context of post-Soviet Kazakhstan. It helps the reader better understand how wider societal forces interact and frame the development of teachers. The paper presents the findings from these stories of MSc students and offers some practical and policy implications for teacher preparation and teacher development.

Keywords: becoming a teacher, Kazakhstan, teacher stories, teacher development

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Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

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The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

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Authors: Chuan Yang, Jing Bie, Panagiotis Psimoulis, Zhong Wang

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Modelling and understanding vehicle volume distribution over the urban network are essential for urban design and transport planning. The space syntax approach was widely applied as the main conceptual and methodological framework for contemporary vehicle volume models with the help of the statistical method of multiple regression analysis (MRA). However, the MRA model with space syntax variables shows a limitation in vehicle volume predicting in accounting for the crossed effect of the urban configurational characters and socio-economic factors. The aim of this paper is to construct models by interacting with the combined impact of the street network structure and socio-economic factors. In this paper, we present a multilevel linear (ML) and an agent-based (AB) vehicle volume model at an urban scale interacting with space syntax theoretical framework. The ML model allowed random effects of urban configurational characteristics in different urban contexts. And the AB model was developed with the incorporation of transformed space syntax components of the MRA models into the agents’ spatial behaviour. Three models were implemented in the same urban environment. The ML model exhibit superiority over the original MRA model in identifying the relative impacts of the configurational characters and macro-scale socio-economic factors that shape vehicle movement distribution over the city. Compared with the ML model, the suggested AB model represented the ability to estimate vehicle volume in the urban network considering the combined effects of configurational characters and land-use patterns at the street segment level.

Keywords: space syntax, vehicle volume modeling, multilevel model, agent-based model

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Authors: Bartlomiej Przybyszewski, Rafal Kozera, Katarzyna Zolynska, Anna Boczkowska, Daria Pakula

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The build-up and accumulation of dirt, ice, and snow on structural elements and vehicles is an unfavorable phenomenon, leading to economic losses and often also posing a threat to people. This problem occurs wherever the use of polymer coatings has become a standard, among others in photovoltaic farms, aviation, wind energy, and civil engineering. The accumulated pollution on the photovoltaic modules can reduce their efficiency by several percent, and snow stops power production. Accumulated ice on the blades of wind turbines or the wings of airplanes and drones disrupts the airflow by changing their shape, leading to increased drag and reduced efficiency. This results in costly maintenance and repairs. The goal of the work is to reduce or completely eliminate the accumulation of dirt, snow, and ice build-up on polymer coatings by achieving self-cleaning and icephobic properties. It is done by the use of a multi-step surface modification of the polymer nanocoatings. For this purpose, two methods of surface structuring and the preceding volumetric modification of the chemical composition with proprietary organosilicon compounds and/or mineral additives were used. To characterize the surface topography of the modified coatings, light profilometry was utilized. Measurements of the wettability parameters (static contact angle and contact angle hysteresis) on the investigated surfaces allowed to identify their wetting behavior and determine relation between hydrophobic and anti-icing properties. Ice adhesion strength was measured to assess coatings' anti-icing behavior.

Keywords: anti-icing properties, self-cleaning, polymer coatings, icephobic coatings

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Authors: V. Marzal, J. C. Torres, B. Garcia-Camara, Manuel Cano-Garcia, Xabier Quintana, I. Perez Garcilopez, J. M. Sanchez-Pena

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At the present time, the use of nanostructures in complex media, like liquid crystals, is widely extended to manipulate their properties, either electrical or optical. In addition, these media can also be used to control the optical properties of the nanoparticles, for instance when they are resonant. In this work, the change on electrical properties of a liquid crystal cell by adding TiO₂ nanoparticles on one of the alignment layers has been analyzed. These nanoparticles, with a diameter of 100 nm and spherical shape, were deposited in one of the substrates (ITO + polyimide) by spin-coating in order to produce a homogeneous layer. These substrates were checked using an optical microscope (objective x100) to avoid potential agglomerates. The liquid crystal cell is then fabricated, using one of these substrates and another without nanoparticles, and filled with E7. The study of the electrical response was done through impedance measurements in a long range of frequencies (3 Hz- 6 MHz) and at ambient temperature. Different nanoparticle concentrations were considered, as well as pure E7 and an empty cell for comparison purposes. Results about the effective dielectric permittivity and conductivity are presented along with models of equivalent electric circuits and its physical interpretation. As a summary, it has been observed the clear influence of the presence of the nanoparticles, strongly modifying the electric response of the device. In particular, a variation of both the effective permittivity and the conductivity of the device have been observed. This result requires a deep analysis of the effect of these nanoparticles on the trapping of free ions in the device, allowing a controlled manipulation and frequency tuning of the electrical response of these devices.

Keywords: alignment layer, electrical behavior, liquid crystal, TiO₂ nanoparticles

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Authors: Saeid Jafari, Khursheed Ahmad Sheikh, Randy W. Worobo, Kitipong Assatarakul

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In this study, the extraction of cocoa shell powder (CSP) was optimized, and the optimized extracts were spray-dried for encapsulation purposes. Temperature (45-65 ◦C), extraction time (30–60 min), and ethanol concentration (60–100%) were the extraction parameters. The response surface methodology analysis revealed that the model was significant (p ≤ 0.05) in interactions between all variables (total phenolic compound, total flavonoid content, and antioxidant activity as measured by 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP assays), with a lack of fit test for the model being insignificant (p > 0.05). Temperature (55 ◦C), time (45 min), and ethanol concentration (60%) were found to be the optimal extraction conditions. For spray-drying encapsulation, some quality metrics (e.g., water solubility, water activity) were insignificant (p > 0.05). The microcapsules were found to be spherical in shape using a scanning electron microscope. Thermogravimetric and differential thermogravimetric measurements of the microcapsules revealed nearly identical results. The gum arabic + maltodextrin microcapsule (GMM) showed potential antibacterial (zone of inhibition: 11.50 mm; lower minimum inhibitory concentration: 1.50 mg/mL) and antioxidant (DPPH: 1063 mM trolox/100g dry wt.) activities (p ≤ 0.05). In conclusion, the microcapsules in this study, particularly GMM, are promising antioxidant and antibacterial agents to be fortified as functional food ingredients for the production of nutraceutical foods with health-promoting properties.

Keywords: functional foods, coco shell powder, antioxidant activity, encapsulation, extraction

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: Arsalan Makinian

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Our future cities will constantly evolve the necessary technologies for tomorrow’s needs. Technologies which enable a better kind of prosperity and security. This paper reports on the precedent of a smart city from its beginning to prevalence among urbanism academic literature and reports of tech companies. The article aims to direct urban foresight studies and to build a pathway for the future of smart city concept by gathering theoretical and empirical experiences related to smart cities with both top-down and bottom-up approaches. It hopes to deliver results of different studies, pilot projects, and development strategies of some of the smart cities in order to allow a shareable knowledge to take shape and develop in terms of qualitative aspects of a smart city. Now the definition of the smart city goes beyond removing physical boundaries, changing the concept of mobility and providing electronic service for citizens, it now constitutes fields such as energy efficiency, economic competitiveness, protecting the environment and finally, it takes advantage of technology and data science to improve the quality of life. In the smart city, the role of citizens is considered as both final purpose and contributor. Emerging issues which are almost implications of advanced technologies -as the most important trends of the future- and their reflection on the society need to be foresighted. Educating and fostering knowledge of smartness is one of the targets of the smart city concept. In this regard, some of these smart cites have established research and development units to share their projects and smart city initiatives. Due to this fact, gaining experience and sharing the results of this subject is necessary for technology management and moving toward a smart urban future.

Keywords: age of urban tech, bottom-up approach, role of citizens, smart city

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Authors: Amina Smaï, Habiba Idouhar-Saadi, Safia Zenia, Fairouz Haddadj, Salaheddine Doumandji

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The poultry industry (chicken and egg consumption) has become important in Algeria, but that does not prevent other farms from beginning to position themselves on the ground like the turkey, guinea fowl, partridge and quail Japanese. The breeding importance of this last, reside, also in game meat, egg quality and their therapeutic role without forgetting its growth performance. To the same effect, a study was held at the center of Zeralda hunting on various parameters such as the weight and number of eggs laid and this in order to know better the potential of production and reproduction of domestic quail. Egg laying has started from the 8th week of reproductive age, their harvest and their counts are performed daily up to 32 weeks of age and more. We have given the biometrics of incubated eggs and unhatched eggs. The parameters studied were the weight, large and small diameter, density, volume, shell index and the shape index. The work revealed that the maximum weight in males is reached in the 11th week, against the female, he reached the 13th week of age. Indeed, there is a good correlation (R = 0.79) between the weight of females and egg production. The rate of unhatched eggs varies between 11 and 43%, these values are recorded respectively in breeding under the age of 25 and 43 weeks. Furthermore, the biometric parameters of hatched and unhatched eggs have differences that are marked, especially during the beginning and end of lay. Further results will be subsequently exploited. Indeed, rearing Japanese quail is easy in technical terms and does not require big investment but its practical application vigilance and daily presence of the breeder within the farm who oversees the hygiene and well-being of its poultry.

Keywords: Japanese quail, biometrics, eggs, unhatching eggs, reproduction

Procedia PDF Downloads 193

Authors: Joo-Hack Lee, Jin-Seung Choi, Dong-Won Kang, Jeong-Woo Seo, Ju-Young Kim, Dae-Hyeok Kim, Seung-Tae Yang, Gye-Rae Tack

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For cycling, the analysis of the pedal force is one of the important factors in the study of exercise ability assessment and overuse injuries. In past studies, a two-axis measurement sensor was used at the sagittal plane to measure the force only in the anterior, posterior, and vertical directions and to analyze the loss of force and the injury on the frontal plane due to the forces in the right and left directions. In this study, which is a basic study on diverse analyses of the pedal force that consider the forces on the sagittal plane and the frontal plane, a three-axis pedal force measurement sensor was developed to measure the anterior-posterior (Fx), medio-lateral (Fz), and vertical (Fy) forces. The sensor was fabricated with a size and shape similar to those of the general flat pedal, and had a 550g weight that allowed smooth pedaling. Its measurement range was ±1000 N for Fx and Fz and ±2000 N for Fy, and its non-linearity, hysteresis, and repeatability were approximately 0.5%. The data were sampled at 1000 Hz using a signal collector. To use the developed sensor, the pedaling efficiency (index of efficiency, IE) and the range of left and right (medio-lateral, ML) forces were measured with two seat heights (low and high). The results of the measurement showed that the IE was higher and the force range in the ML direction was lower with the high position than with the low position. The developed measurement sensor and its application results will be useful in understanding and explaining the complicated pedaling technique, and will enable diverse kinematic analyses of the pedal force on the sagittal plane and the frontal plane.

Keywords: cycling, pedal force, index of effectiveness, measuring

Procedia PDF Downloads 658

Authors: Chang Liang, Weizhi Gong, Yan Zhang

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Purpose: Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis worldwide. Murine double minute 2 (MDM2) regulates the tumor suppressor p53, increasing cancer risk and accelerating tumor progression. Speckle-type POX virus and zinc finger protein (SPOP), a key of subunit of Cullin-Ring E3 ligase, inhibits tumor genesis and progression by the ubiquitination of its downstream substrates. This study aimed to clarify whether SPOP and MDM2 are mutually regulated in HCC and the correlation between SPOP and MDM2 and the prognosis of HCC patients. Methods: First, the expression of SPOP and MDM2 in HCC tissues were detected by TCGA database. Then, 53 paired samples of HCC tumor and adjacent tissues were collected to evaluate the expression of SPOP and MDM2 using immunohistochemistry. Chi-square test or Fisher’s exact test were used to analyze the relationship between clinicopathological features and the expression levels of SPOP and MDM2. In addition, Kaplan‒Meier curve analysis and log-rank test were used to investigate the effects of SPOP and MDM2 on the survival of HCC patients. Last, the Multivariate Cox proportional risk regression model analyzed whether the different expression levels of SPOP and MDM2 were independent risk factors for the prognosis of HCC patients. Results: Bioinformatics analysis revealed the low expression of SPOP and high expression of MDM2 were related to worse prognosis of HCC patients. The relationship between the expression of SPOP and MDM2 and tumor stem-like features showed an opposite trend. The immunohistochemistry showed the expression of SPOP protein was significantly downregulated while MDM2 protein significantly upregulated in HCC tissue compared to that in para-cancerous tissue. Tumors with low SPOP expression were related to worse T stage and Barcelona Clinic Liver Cancer (BCLC) stage, but tumors with high MDM2 expression were related to worse T stage, M stage, and BCLC stage. Kaplan–Meier curves showed HCC patients with high SPOP expression and low MDM2 expression had better survival than those with low SPOP expression and high MDM2 expression (P < 0.05). A multivariate Cox proportional risk regression model confirmed that a high MDM2 expression level was an independent risk factor for poor prognosis in HCC patients (P <0.05). Conclusion: The expression of SPOP protein was significantly downregulated, while the expression of MDM2 significantly upregulated in HCC. The low expression of SPOP and high expression. of MDM2 were associated with malignant progression and poor prognosis of HCC patients, indicating a potential therapeutic target for HCC patients.

Keywords: hepatocellular carcinoma, murine double minute 2, speckle-type POX virus and zinc finger protein, ubiquitination

Procedia PDF Downloads 142

Authors: Chaouki Ghenai

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Computational fluid dynamics analysis of the burning of syngas fuels derived from biomass and plastic solid waste mixture through gasification process is presented in this paper. The syngas fuel is burned in gas turbine can combustor. Gas turbine can combustor with swirl is designed to burn the fuel efficiently and reduce the emissions. The main objective is to test the impact of the alternative syngas fuel compositions and lower heating value on the combustion performance and emissions. The syngas fuel is produced by blending Palm Kernel Shell (PKS) with Polyethylene (PE) waste via catalytic steam gasification (fluidized bed reactor). High hydrogen content syngas fuel was obtained by mixing 30% PE waste with PKS. The syngas composition obtained through the gasification process is 76.2% H2, 8.53% CO, 4.39% CO2 and 10.90% CH4. The lower heating value of the syngas fuel is LHV = 15.98 MJ/m3. Three fuels were tested in this study natural gas (100%CH4), syngas fuel and pure hydrogen (100% H2). The power from the combustor was kept constant for all the fuels tested in this study. The effect of syngas fuel composition and lower heating value on the flame shape, gas temperature, mass of carbon dioxide (CO2) and nitrogen oxides (NOX) per unit of energy generation is presented in this paper. The results show an increase of the peak flame temperature and NO mass fractions for the syngas and hydrogen fuels compared to natural gas fuel combustion. Lower average CO2 emissions at the exit of the combustor are obtained for the syngas compared to the natural gas fuel.

Keywords: CFD, combustion, emissions, gas turbine combustor, gasification, solid waste, syngas, waste to energy

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Authors: Subbarao Pichuka, Amar Balakrishna Tej, Vikas Vemula

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In recent years, the frequency and intensity of urban floods have increased due to climate change all over the world provoking a significant loss in terms of human lives and property. This study investigates the effect of Land Use and Land Cover (LULC) changes and population growth on the urban environmental conditions in the Indian metropolitan city namely Hyderabad. The centennial built-up area data have been downloaded from the Global Human Settlement Layer (GHSL) web portal for various periods (1975 to 2014). The ArcGIS version 10.8 software is employed to convert the GHSL data into shape files and also to calculate the amount of built-up area in the study locations. The decadal population data are obtained from the Census from 1971 to 2011 and forecasted for the required years (1975 and 2014) utilizing the Geometric Increase Method. Next, the analysis has been carried out with respect to the increase in population and the corresponding rise in the built-up area. Further the effects of extreme rainfall events, which exacerbate urban flooding have also been reviewed. Results demonstrate that the population growth was the primary cause of the increase in impervious surfaces in the urban regions. It in turn leads to the intensification of surface runoff and thereby leads to Urban flooding. The built-up area has been doubled from 1975 to 2014 and the population growth has been observed between 109.24% to 400% for the past four decades (1971 to 2014) in the study area (Hyderabad). Overall, this study provides the hindsight on the current urban flooding scenarios, and the findings of this study can be used in the future planning of cities.

Keywords: urban LULC change, urban flooding, GHSL built-up data, climate change, ArcGIS

Procedia PDF Downloads 80

Authors: R. Vasireddi, J. Kruse, M. Vakili, M. Trebbin

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Here we present a gas dynamic virtual nozzle (GDVN) based microfluidic jetting devices for spinning of nano/microfibers. The device is fabricated by soft lithography techniques and is based on the principle of a GDVN for precise three-dimensional gas focusing of the spinning solution. The nozzle device is used to produce micro/nanofibers of a perfluorinated terpolymer (THV), which were collected on an aluminum substrate for scanning electron microscopy (SEM) analysis. The influences of air pressure, polymer concentration, flow rate and nozzle geometry on the fiber properties were investigated. It was revealed that surface properties are controlled by air pressure and polymer concentration while the diameter and shape of the fibers are influenced mostly by the concentration of the polymer solution and pressure. Alterations of the nozzle geometry had a negligible effect on the fiber properties, however, the jetting stability was affected. Round and flat fibers with differing surface properties from craters, grooves to smooth surfaces could be fabricated by controlling the above-mentioned parameters. Furthermore, the formation of surface roughness was attributed to the fast evaporation rate and velocity (mis)match between the polymer solution jet and the surrounding air stream. The diameter of the fibers could be tuned from ~250 nm to ~15 µm. Because of the simplicity of the setup, the precise control of the fiber properties, access to biocompatible nanofiber fabrication and the easy scale-up of parallel channels for high throughput, this method offers significant benefits compared to existing solution-based fiber production methods.

Keywords: gas dynamic virtual nozzle (GDVN) principle, microfluidic device, spinning, uniform nanofibers

Procedia PDF Downloads 149

Authors: Letizia Maria Drammis, Maria Antonella Brandimonte

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The idea that people use space representations to think about time and number received support from several lines of research. However, how these representations develop in children and then shape space-time and space-number mappings is still a debated issue. In the present study, 40 children (20 pre-schoolers and 20 elementary-school children) performed 4 main tasks, which required the use of more concrete (non-symbolic) or more abstract (symbolic) space-time and space-number associations. In the non-symbolic conditions, children were required to order pictures of everyday-life events occurring in a specific temporal order (Temporal sequences) and of quantities varying in numerosity (Numerical sequences). In the symbolic conditions, they were asked to perform the typical time-to-position and number-to-position tasks by mapping time-related words and numbers onto lines. Results showed that children performed reliably better in the non-symbolic Time conditions than the symbolic Time conditions, independently of age, whereas only pre-schoolers performed worse in the Number-to-position task (symbolic) as compared to the Numerical sequence (non-symbolic) task. In addition, only older children mapped time-related words onto space following the typical left-right orientation, pre-schoolers’ performance being somewhat mixed. In contrast, mapping numbers onto space showed a clear left-right orientation, independently of age. Overall, these results indicate a cross-domain difference in the way younger and older children process time and number, with time-related tasks being more difficult than number-related tasks only when space-time tasks require symbolic representations.

Keywords: space-time associations, space-number associations, orientation, children

Procedia PDF Downloads 334

Authors: Jesus Salmeron, Carmen De Vega, Maria Soledad Vicente, Mireia Olabarria, Olaia Martinez

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Dysphagia or difficulty in swallowing affects mostly elder people: 56-78% of the institutionalized and 44% of the hospitalized. Liquid food thickening is a necessary measure in this situation because it reduces the risk of penetration-aspiration. Until now, and as proposed by the American Dietetic Association in 2002, possible consistencies have been categorized in three groups attending to their viscosity: nectar (50-350 mPa•s), honey (350-1750 mPa•s) and pudding (>1750 mPa•s). The adequate viscosity level should be identified for every patient, according to her/his impairment. Nevertheless, a systematic review on dysphagia diet performed recently indicated that there is no evidence to suggest that there is any transition of clinical relevance between the three levels proposed. It was also stated that other physical properties of the bolus (slipperiness, density or cohesiveness, among others) could influence swallowing in affected patients and could contribute to the amount of remaining residue. Texture parameters need to be evaluated as possible alternative to viscosity. The aim of this study was to evaluate the instrumental extrusion-compression test as a possible tool to characterize changes along time in water thickened with various products and in the three theoretical consistencies. Six commercial thickeners were used: NM® (NM), Multi-thick® (M), Nutilis Powder® (Nut), Resource® (R), Thick&Easy® (TE) and Vegenat® (V). All of them with a modified starch base. Only one of them, Nut, also had a 6,4% of gum (guar, tara and xanthan). They were prepared as indicated in the instructions of each product and dispensing the correspondent amount for nectar, honey and pudding consistencies in 300 mL of tap water at 18ºC-20ºC. The mixture was stirred for about 30 s. Once it was homogeneously spread, it was dispensed in 30 mL plastic glasses; always to the same height. Each of these glasses was used as a measuring point. Viscosity was measured using a rotational viscometer (ST-2001, Selecta, Barcelona). Extrusion-compression test was performed using a TA.XT2i texture analyzer (Stable Micro Systems, UK) with a 25 mm diameter cylindrical probe (SMSP/25). Penetration distance was set at 10 mm and a speed of 3 mm/s. Measurements were made at 1, 5, 10, 20, 30, 40, 50 and 60 minutes from the moment samples were mixed. From the force (g)–time (s) curves obtained in the instrumental assays, maximum force peak (F) was chosen a reference parameter. Viscosity (mPa•s) and F (g) showed to be highly correlated and had similar development along time, following time-dependent quadratic models. It was possible to predict viscosity using F as an independent variable, as they were linearly correlated. In conclusion, compression-extrusion test could be an alternative and a useful tool to assess physical characteristics of thickened liquids.

Keywords: compression-extrusion test, dysphagia, texture analyzer, thickener

Procedia PDF Downloads 365