Search results for: short span

Authors: Irit Rutman Halili, Tehila Zvulun, Natali Elgabsi, Revaya Cohen, Shlomo Sarig

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Active sand dunes (ASD) may cause significant damage to field crops and livelihood, and therefore, it is necessary to find a treatment that would enhance ADS soil stability. Biological soil crusts (biocrusts) contain microorganisms on the soil surface. Metabolic polysaccharides secreted by biocrust cyanobacteria glue the soil particles into aggregates, thereby stabilizing the soil surface. Filter cake powder (FCP) is a waste by-product in the final stages of the production of sugar from sugarcane, and its disposal causes significant environmental pollution. FCP contains high concentrations of polysaccharides and has recently been shown to be soil stability enhancing agent in ASD. It has been reported that adding FCP to the ASD soil surface by dispersal significantly increases the level of penetration resistance of soil biocrust (PRSB) nine weeks after a single treatment. However, it was not known whether a similar effect could be obtained by administering the FCP in liquid form by means of spraying. It has now been found that spraying a water solution of FCP onto the ASD soil surface significantly increased the level of penetration resistance of soil biocrust (PRSB) three weeks after a single treatment. These results suggest that FCP spraying can be used as a short-term soil stability-enhancing agent for ASD, while administration by dispersal might be more efficient over the long term. Finally, an additional benefit of using FCP as a soil stabilizer, either by dispersal or by spraying, is the reduction in environmental pollution that would otherwise result from the disposal of FCP solid waste.

Keywords: active sand dunes, filter cake powder, biological soil crusts, penetration resistance of soil biocrust

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Authors: Omid Khandel, Azadeh Parvin

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An increase in accidental explosions in recent years has increased the interest on investigating the response and behavior of structures in more details. The present work focused on finite element analysis of multistory steel frame structures with different plan shapes subjected to blast loadings. In order to study the effect of the geometry of the building, three different shapes for the plan of the building were modeled and studied; Rectangular, Square and L shape plans. The nonlinear dynamic analysis was considered in this study. The relocation technique was also used to improve the behavior of structure. The accuracy of the multistory frame model was confirmed with those of the existing study in the literature and they were in good agreement. The effect of span length of the buildings was also considered. Finite element analysis of various scenarios for relocating the plastic hinges and improving the response of the structure was performed. The base shear versus displacement curves were compared to reveal the best possible scenarios to provide recommendations to designers and practitioners.

Keywords: nonlinear dynamic analysis, plastic hinge relocation, Retrofit, SAP2000

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Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

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There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Mohamed S. Negm, Waleed S. Mandour

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The present study aims primarily at investigating words of peace (lexemes of peace) in the formal speeches of the Egyptian president Abdulfattah El-Sisi in a two-year span of time, from 2018 to 2019. This paper attempts to shed light not only on the contextual use of the antonyms, war and peace, but also it underpins quantitative analysis through the current methods of corpus linguistics. As such, the researchers have deployed a corpus-based approach in collecting, encoding, and processing 30 presidential speeches over the stated period (23,411 words and 25,541 tokens in total). Further, semantic fields and collocational networkzs are identified and compared statistically. Results have shown a significant propensity of adopting peace, including its relevant collocation network, textually and therefore, ideationally, at the expense of war concept which in most cases surfaces euphemistically through the noun conflict. The president has not justified the action of war with an honorable cause or a valid reason. Such results, so far, have indicated a positive sociopolitical mindset the Egyptian president possesses and moreover, reveal national and international fair dealing on arising issues.

Keywords: CADS, collocation network, corpus linguistics, critical discourse analysis

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Authors: Jiani Gao, Qingping Luo, Xinlei Fang

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In order to try to achieve better rights and interests for both doctors and patients in the new medical environment, the paper will focus on the renewal and development of medical buildings. In today's highly developed society, many factors have a profound guiding significance for the development of medical buildings. By doing social research, the paper has found that these factors come from all aspects. These factors include the optimization of traditional medical model, rapid alternation of medical technology and equipment, the reform of the social, medical security system, changes in the age structure of the population, the birth of intelligent medical care under the Internet, and the deepening of the concept of green sustainable building development, etc. The purpose of this paper is to capture sensitively these various factors that may affect the evolution of medical buildings in the context of the current era, and to put forward, by using an adaptable development strategy, some feasible suggestions on the design of medical buildings when facing these changes and challenges. Specifically speaking, the adaptable development strategy includes some basic principles and methods, such as using modular design, adopting scalable streamline, selecting a long-span structural system and using replaceable materials and components, etc.

Keywords: medical architecture, adaptable development, medical model, space design

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Authors: Livia Herle

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A large part of the Principality of Liechtenstein is covered by forest. Three-quarters of this forest is defined as protective due to the alpine landscape of the country, which is deteriorating the quality of the wood. Nevertheless, the forest is one of the most important sources of raw material. However, out of the wood harvested annually in Liechtenstein, about two-thirds are used directly as an energy source, drastically shortening up the carbon storage cycle of wood. Furthermore, due to climate change, forest structures are changing. Predictions for the forest in Liechtenstein have stated that the spruce will mostly vanish in low altitudes, only being able to survive in the higher regions. In contrast, hardwood species will experience a rise, resulting in a more mixed forest. Thus, the main research focus will be put upon the potential of hardwood as well as prolonging the lifespan of a timber log before ending up as an energy source. An analysis of the local occurrence of hardwood species and their quality will serve as a tool to implement this knowledge upon constructional solutions. As a system that works with short spam timber and thus qualifies for the regional conditions of hardwood, reciprocal frame systems will be further investigated. These can be defined as load-bearing structures with only two beams connecting at a time, avoiding complex joining situations. Furthermore, every beam is mutually supporting. This allows the usage of short pieces of preferably massive wood. As a result, the system permits for an easy assembly but also disassembly. To promote a more circular application of wood, possible cascading scenarios of the structural solutions will be added. In a workshop at the School of Architecture of the University of Liechtenstein in the Sommer Semester 2024, prototypes in 1:1 of reciprocal frame systems using only local hardwood will help as a tool to further test the theoretical analyses.

Keywords: hardwood, cascading wood, reciprocal frames, crooked wood, forest structures, climate change

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Authors: Marina Benito-Parejo, Raul Perez-Lopez, Miguel Herraiz, Carolina Guardiola-Albert, Cesar Martinez

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Persistency, long-term memory and randomness are intrinsic properties of time-series of earthquakes. The Rescaled Range Analysis (RS-Analysis) was introduced by Hurst in 1956 and modified by Mandelbrot and Wallis in 1964. This method represents a simple and elegant analysis which determines the range of variation of one natural property (the seismic energy released in this case) in a time interval. Despite the simplicity, there is complexity inherent in the property measured. The cumulative curve of the energy released in time is the well-known fractal geometry of a devil’s staircase. This geometry is used for determining the maximum and minimum value of the range, which is normalized by the standard deviation. The rescaled range obtained obeys a power-law with the time, and the exponent is the Hurst value. Depending on this value, time-series can be classified in long-term or short-term memory. Hence, an algorithm has been developed for compiling the RS-Analysis for time series of earthquakes by days. Completeness time distribution and locally stationarity of the time series are required. The interest of this analysis is their application for a complex seismic crisis where different earthquakes take place in clusters in a short period. Therefore, the Hurst exponent has been obtained for the seismic crisis of Alhoceima (Mediterranean Sea) of January-March, 2016, where at least five medium-sized earthquakes were triggered. According to the values obtained from the Hurst exponent for each cluster, a different mechanical origin can be detected, corroborated by the focal mechanisms calculated by the official institutions. Therefore, this type of analysis not only allows an approach to a greater understanding of a seismic series but also makes possible to discern different types of seismic origins.

Keywords: Alhoceima crisis, earthquake time series, Hurst exponent, rescaled range analysis

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Armin Solemanifar, Arthur Wilkinson, Kinjalkumar Patel

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Carbon fibre (CF) - polymer laminate composites have very low densities (approximately 40% lower than aluminium), high strength and high stiffness but in terms of toughness properties they often require modifications. For example, adding rubbers or thermoplastics toughening agents are common ways of improving the interlaminar fracture toughness of initially brittle thermoset composite matrices. The main aim of this project was to toughen CF-epoxy resin laminate composites using hybrid CF-fabrics incorporating Innegra™ a commercial highly-oriented polypropylene (PP) fibre, in which more than 90% of its crystal orientation is parallel to the fibre axis. In this study, the damage tolerance of hybrid (carbon-Innegra, CI) composites was investigated. Laminate composites were produced by resin-infusion using: pure CF fabric; fabrics with different ratios of commingled CI, and two different types of pure Innegra fabrics (Innegra 1 and Innegra 2). Dynamic mechanical thermal analysis (DMTA) was used to measure the glass transition temperature (Tg) of the composite matrix and values of flexural storage modulus versus temperature. Mechanical testing included drop-weight impact, compression-after-impact (CAI), and interlaminar (short-beam) shear strength (ILSS). Ultrasonic C-Scan imaging was used to determine the impact damage area and scanning electron microscopy (SEM) to observe the fracture mechanisms that occur during failure of the composites. For all composites, 8 layers of fabrics were used with a quasi-isotropic sequence of [-45°, 0°, +45°, 90°]s. DMTA showed the Tg of all composites to be approximately same (123 ±3°C) and that flexural storage modulus (before the onset of Tg) was the highest for the pure CF composite while the lowest were for the Innegra 1 and 2 composites. Short-beam shear strength of the commingled composites was higher than other composites, while for Innegra 1 and 2 composites only inelastic deformation failure was observed during the short-beam test. During impact, the Innegra 1 composite withstood up to 40 J without any perforation while for the CF perforation occurred at 10 J. The rate of reduction in compression strength upon increasing the impact energy was lowest for the Innegra 1 and 2 composites, while CF showed the highest rate. On the other hand, the compressive strength of the CF composite was highest of all the composites at all impacted energy levels. The predominant failure modes for Innegra composites observed in cross-sections of fractured specimens were fibre pull-out, micro-buckling, and fibre plastic deformation; while fibre breakage and matrix delamination were a major failure observed in the commingled composites due to the more brittle behaviour of CF. Thus, Innegra fibres toughened the CF composites but only at the expense of reducing compressive strength.

Keywords: hybrid composite, thermoplastic fibre, compression strength, damage tolerance

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Authors: Elmira Davasaz Tabrizi, Müşteba Sevil, Ercan Arican

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In recent decades, there has been a sharp increase in the prevalence of several unrelated chronic diseases. The use of long-term antibiotics for chronic illnesses is increasing. The antibiotic resistance occurrence and its relationship with host microbiomes are still unclear. Properties of the identifying antibodies have been the focus of chronic disease research, such as prostatitis or autoimmune. The immune system is made up of a complicated but well-organized network of cell types that constantly monitor and maintain their surroundings. The regulated homeostatic interaction between immune system cells and their surrounding environment shapes the microbial flora. Researchers believe that the disappearance of special bacterial species from our ancestral microbiota might have altered the body flora that can cause a rise in disease during the human life span. This unpleasant pattern demonstrates the importance of focusing on discovering and revealing the root causes behind the disappearance or alteration of our microbiota. In this review, we gathered the results of some studies that reveal changes in the diversity and quantity of microorganisms that may affect chronic and autoimmune diseases. Additionally, a Ph.D. thesis that is still in process as Metagenomic studies in chronic prostatitis samples is mentioned.

Keywords: metagenomic, autoimmune, prostatitis, microbiome

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Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

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Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

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Authors: Paresh Patel, Harshit Patel

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Superficial fungal skin infection is among the most common skin disease. The drug administration through skin has received attention due to several advantages: Avoidance of significant pre-systemic metabolism, drug levels within the therapeutic window, drugs with short biological half-lives, decreased side effects, the non-invasive character, and very high acceptance.

Keywords: transdermal spray, ketoconazole, Eudragit® RLPO, therapeutic window

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Authors: Noha M. Rashad, W. Swelam, M. H. Abd ElAzeem

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A simple design of array antenna is presented in this paper, supporting millimeter wave applications which can be used in short range wireless communications such as 5G applications. This design enhances the use of V-band, according to IEEE standards, as the antenna works in the 70 GHz band with bandwidth more than 11 GHz and peak gain more than 13 dBi. The design is simulated using different numerical techniques achieving a very good agreement.

Keywords: 5G technology, array antenna, microstrip, millimeter wave

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Authors: Rubab Ammad, Abdelgadir Abuelgasim

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UAE typically lies in one of the aridest regions of the world and is thus home to geologic features common to such climatic conditions including vast open deserts, sand dunes, saline soils, inland Sabkha and coastal Sabkha. Sabkha are characteristic salt flats formed in arid environment due to deposition and precipitation of salt and silt over sand surface because of low laying water table and rates of evaporation exceeding rates of precipitation. The study area, which comprises of western UAE, is heavily concentrated with inland Sabkha. Remote sensing is conventionally used to study the soil salinity of agriculturally degraded lands but not so broadly for Sabkha. The focus of this study was to identify these highly saline Sabkha areas on remotely sensed data, using salinity indices. The existing salinity indices in the literature have been designed for agricultural soils and they have not frequently used the spectral response of short-wave infra-red (SWIR1 and SWIR2) parts of electromagnetic spectrum. Using Landsat 8 OLI data and field ground truthing, this study formulated indices utilizing NIR-SWIR parts of spectrum and compared the results with existing salinity indices. Most indices depict reasonably good relationship between salinity and spectral index up until a certain value of salinity after which the reflectance reaches a saturation point. This saturation point varies with index. However, the study findings suggest a role of incorporating near infra-red and short-wave infra-red in salinity index with a potential of showing a positive relationship between salinity and reflectance up to a higher salinity value, compared to rest.

Keywords: Sabkha, salinity index, saline soils, Landsat 8, SWIR1, SWIR2, UAE desert

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Authors: Assad Rashid, Umair Ahmed, Zafar Baig

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A new trend in construction is widely influenced by the use of Steel-Concrete Composite Columns. The rapid growth in Steel-Concrete Composite construction has widely decreased the conventional R.C.C structures. Steel Concrete composite construction has obtained extensive receiving around the globe. It is considering the fact that R.C.C structures construction is most suitable and economical for low-rise construction, so it is used in farming systems in most of the buildings. However, increased dead load, span restriction, less stiffness and risky formwork make R.C.C construction uneconomical and not suitable when it comes to intermediate to high-rise buildings. A Base + Ground +11 storey commercial building was designed on ETABS 2017 and made a comparison between conventional R.C.C and encased composite column structure. After performing Equivalent Static non-linear analysis, it has been found that construction cost is 13.01% more than R.C.C structure but encased composite column building has 7.7% more floor area. This study will help in understanding the behavior of conventional R.C.C structure and Encased Composite column structure.

Keywords: composite columns structure, equivalent static non-linear analysis, comparison between R.C.C and encased composite column structures, cost-effective structure

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Authors: Kasra Khorsand-Kazemi, Bianca Vizcaino, Mandeep Chhajer Jain, Maryam Moradpour

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This work presents an approach to characterize a non- contact microwave sensor using waveguides for different standard liquids such as ethanol, methanol and 2-propanol (Isopropyl Alcohol). Wideband waveguides operating between 12.4GHz to 18 GHz form the core of the sensing structure. Waveguides are sensitive to changes in conductivity of the sample under test (SUT), making them an ideal tool to characterize different polar liquids. As conductivity of the sample under test increase, the loss tangent of the material increase, thereby decreasing the S21 (dB) response of the waveguide. Among all the standard liquids measured, methanol exhibits the highest conductivity and 2-Propanol exhibits the lowest. The cutoff frequency measured for ethanol, 2-propanol, and methanol are 10.28 GHz, 10.32 GHz, and 10.38 GHz respectively. The measured results can be correlated with the loss tangent results of the standard liquid measured using the dielectric probe. This conclusively enables us to characterize different liquids using waveguides expanding the potential future applications in domains ranging from water quality management to bio-medical, chemistry and agriculture.

Keywords: Waveguides, , Microwave sensors, , Standard liquids characterization, Non-contact sensing

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Authors: Hajar Hajmohammadi, Paul Pfeffer, Anna De Simoni, Jim Cole, Chris Griffiths, Sally Hull, Benjamin Heydecker

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Background: There is strong interest in the relationship between short-term air pollution exposure and human health. Most studies in this field focus on serious health effects such as death or hospital admission, but air pollution exposure affects many people with less severe impacts, such as exacerbations of respiratory conditions. A lack of quantitative analysis and inconsistent findings suggest improved methodology is needed to understand these effectsmore fully. Method: We developed a time series regression model to quantify the relationship between daily NOₓ concentration and Asthma exacerbations requiring oral steroids from primary care settings. Explanatory variables include daily NOₓ concentration measurements extracted from 8 available background and roadside monitoring stations in east London and daily ambient temperature extracted for London City Airport, located in east London. Lags of NOx concentrations up to 21 days (3 weeks) were used in the model. The dependent variable was the daily number of oral steroid courses prescribed for GP registered patients with asthma in east London. A mixed distribution model was then fitted to the significant lags of the regression model. Result: Results of the time series modelling showed a significant relationship between NOₓconcentrations on each day and the number of oral steroid courses prescribed in the following three weeks. In addition, the model using only roadside stations performs better than the model with a mixture of roadside and background stations.

Keywords: air pollution, time series modeling, public health, road transport

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Authors: Amine Rezzoug, Selsabil Rokia Laraba, Mourad Ancer, Said Abdi

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Composite materials are taking center stage in different fields thanks to their mechanical characteristics and their ease of preparation. Environmental constraints have led to the development of composite with natural reinforcements. The sandwich structure has the advantage to have good flexural proprieties for low density, which is why it was chosen in this work. The development of these materials is related to an energy saving strategy and environmental protection. The present work refers to the study of the development and characterization of sandwiches composites based on hybrids laminates with natural reinforcements (Alfa and Jute), a metal fabric was introduced into composite in order to have a compromise between weight and properties. We use different configurations of reinforcements (jute, metallic fabric) to develop laminates in order to use them as thin facings for sandwiches materials. While the core was an epoxy matrix reinforced with Alfa short fibers, a chemical treatment sodium hydroxide was cared to improve the adhesion of the Alfa fibers. The mechanical characterization of our materials was made by the tensile and bending test, to highlight the influence of jute and Alfa. After testing, the fracture surfaces are observed by scanning electron microscopy (SEM). Optical microscopy allowed us to calculate the degree of porosity and to observe the morphology of the individual layers. Laminates based on jute fabric have shown better results in tensile test as well as to bending, compared to those of the metallic fabric (100%, 65%). Sandwich Panels were also characterized in terms of bending test. Results we had provide, shows that this composite has sufficient properties for possible replacing conventional composite materials by considering the environmental factors.

Keywords: bending test, bio-composites, sandwiches, tensile test

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Authors: Sylwia Gieraltowska, Lukasz Wachnicki, Bartlomiej S. Witkowski, Marek Godlewski

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Oxide layers doped with rare-earth (RE) ions in optimized way can absorb short (ultraviolet light), which will be converted to visible light by so-called down-conversion. Down-conversion mechanisms are usually exploited to modify the incident solar spectrum. In down conversion, multiple low-energy photons are generated to exploit the energy of one incident high-energy photon. These RE-doped oxide materials have attracted a great deal of attention from researchers because of their potential for optical manipulation in optical devices (detectors, temperature sensors, and compact solid-state lasers, light-emitting diodes), bio-analysis, medical therapy, display technologies, and light harvesting (such as in photovoltaic cells). The zirconium dioxide (ZrO2) doped RE ions (Eu, Tb, Ce) multilayer structures were tested as active layers, which can convert short wave emission to light in the visible range (the down-conversion mechanism). For these applications original approach of deposition ZrO2 layers using the Atomic Layer Deposition (ALD) method and doping these layers with RE ions using the spin-coating technique was used. ALD films are deposited at relatively low temperature (well below 250°C). This can be an effective method to achieve the white-light emission and to improve on this way light conversion efficiency, by an extension of absorbed spectral range by a solar cell material. Photoluminescence (PL), X-ray diffraction (XRD), scanning electron microscope (SEM) and atomic force microscope (AFM) measurement are analyzed. The research was financially supported by the National Science Centre (decision No. DEC-2012/06/A/ST7/00398 and DEC- 2013/09/N/ST5/00901).

Keywords: ALD, oxide layers, photovoltaics, thin films

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Authors: Zhicheng Han

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This study examines the correlation between knowledge of formulaic language, working memory (WM), and phonological short-term memory (PSTM) in Chinese L2 learners of English. This study investigates if WM and PSTM correlate differently to the acquisition of formulaic language, which may be relevant for the discourse around the conceptualization of formulas. Connectionist approaches have lead scholars to argue that formulas are form-meaning connections stored whole, making PSTM significant in the acquisitional process as it pertains to the storage and retrieval of chunk information. Generativist scholars, on the other hand, argued for active participation of interlanguage grammar in the acquisition and use of formulaic language, where formulas are represented in the mind but retain the internal structure built around a lexical core. This would make WM, especially the processing component of WM an important cognitive factor since it plays a role in processing and holding information for further analysis and manipulation. The current study asked L1 Chinese learners of English enrolled in graduate programs in China to complete a preference raking task where they rank their preference for formulas, grammatical non-formulaic expressions, and ungrammatical phrases with and without the lexical core in academic contexts. Participants were asked to rank the options in order of the likeliness of them encountering these phrases in the test sentences within academic contexts. Participants’ syntactic proficiency is controlled with a cloze test and grammar test. Regression analysis found a significant relationship between the processing component of WM and preference of formulaic expressions in the preference ranking task while no significant correlation is found for PSTM or syntactic proficiency. The correlational analysis found that WM, PSTM, and the two proficiency test scores have significant covariates. However, WM and PSTM have different predictor values for participants’ preference for formulaic language. Both storage and processing components of WM are significantly correlated with the preference for formulaic expressions while PSTM is not. These findings are in favor of the role of interlanguage grammar and syntactic knowledge in the acquisition of formulaic expressions. The differing effects of WM and PSTM suggest that selective attention to and processing of the input beyond simple retention play a key role in successfully acquiring formulaic language. Similar correlational patterns were found for preferring the ungrammatical phrase with the lexical core of the formula over the ones without the lexical core, attesting to learners’ awareness of the lexical core around which formulas are constructed. These findings support the view that formulaic phrases retain internal syntactic structures that are recognized and processed by the learners.

Keywords: formulaic language, working memory, phonological short-term memory, academic language

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Authors: Rafael Muñoz, Juan Melchor, Alicia Valera, Laura Peralta, Guillermo Rus

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A torsional piezoelectric ultrasonic transducer design is proposed to measure shear moduli in soft tissue with direct access availability, using shear wave elastography technique. The measurement of shear moduli of tissues is a challenging problem, mainly derived from a) the difficulty of isolating a pure shear wave, given the interference of multiple waves of different types (P, S, even guided) emitted by the transducers and reflected in geometric boundaries, and b) the highly attenuating nature of soft tissular materials. An immediate application, overcoming these drawbacks, is the measurement of changes in cervix stiffness to estimate the gestational age at delivery. The design has been optimized using a finite element model (FEM) and a semi-analytical estimator of the probability of detection (POD) to determine a suitable geometry, materials and generated waves. The technique is based on the time of flight measurement between emitter and receiver, to infer shear wave velocity. Current research is centered in prototype testing and validation. The geometric optimization of the transducer was able to annihilate the compressional wave emission, generating a quite pure shear torsional wave. Currently, mechanical and electromagnetic coupling between emitter and receiver signals are being the research focus. Conclusions: the design overcomes the main described problems. The almost pure shear torsional wave along with the short time of flight avoids the possibility of multiple wave interference. This short propagation distance reduce the effect of attenuation, and allow the emission of very low energies assuring a good biological security for human use.

Keywords: cervix ripening, preterm birth, shear modulus, shear wave elastography, soft tissue, torsional wave

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Authors: Shao-Hsuan Chien, Ju-Hui Fu

Abstract:

Parkinson’s disease (PD) is a degenerative disorder of the central nervous system that is characterized by progressive loss of dopaminergic neurons in the substantia nigra pars compacta and motor impairment. Aggregation of α-synuclein in neuronal cells plays a key role in this disease. At present, therapeutics for PD provides moderate symptomatic benefit but is not able to delay the development of this disease. Current efforts for the treatment of PD are to identify new drugs that show slow or arrest progressive course of PD by interfering with a disease-specific pathogenetic process in PD patients. Maackiain is a bioactive compound isolated from the roots of the Chinese herb Sophora flavescens. The purpose of the present study was to assess the potential for maackiain to ameliorate PD in Caenorhabditis elegans models. Our data reveal that maackiain prevents α-synuclein accumulation in the transgenic Caenorhabditis elegans model and also improves dopaminergic neuron degeneration, food-sensing behavior, and life-span in 6-hydroxydopamine-induced Caenorhabditis elegans model, thus indicating its potential as a candidate antiparkinsonian drug.

Keywords: maackiain, Parkinson’s disease, dopaminergic neurons, α-Synuclein

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Authors: Dagikhudo Dagiev

Abstract:

This paper is a thorough contribution to the analysis of Russian, Soviet and post-Soviet scholarship on the study of Ismailism in Central Asia. It focuses on the lengthy development of Russian studies on Ismailism from the Russian colonial domination to the entire period of Soviet rule, down to the collapse of the Soviet Union and the last two decades of post-Soviet history. These studies, conducted along the lines of various disciplines in the span of more than one hundred years, have resulted in a large amount of scholarly contributions. This paper aims at probing the virtues and shortcoming of such scholarship. Particularly, our investigation of the specialised fields in the Russian-Soviet Studies has required laborious researches in Russian and Central Asian libraries, which have enabled us to provide a guide through this literature, assessing its ideological leanings and qualities, institutions and level of scholarship. Despite some shortcomings, due to Marxism and the authoritarian rule of the Communist Party over the socio-religious life of the people and religious communities, Soviet studies have produced many positive insights on Ismailis studies. These captured almost every aspects of the life of the Ismaili community from anthropology to archaeology, ethnography, history, philosophy, ritual practice and, most importantly, collection and preservation of Ismaiili manuscripts, which will be examined and assessed in this study.

Keywords: Central Asian Studies, Ismailism, Russian Studies, Soviet Studies

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Authors: Natia Kvachakidze

Abstract:

The given research aims to study and analyze the influence of Ernest Hemingway’s writing style on Georgian prose of 1950s and 1960s. It is universally known that Ernest Hemingway’s unique writing style has had an enormous effect on various writers. His work remains highly relevant and influential even today. This is especially true about the works written in English, but literary prose created in other languages is not an exception. Certain stylistic peculiarities characteristic for Hemingway’s writing can be traced in literary works written in various languages. It is particularly interesting for us, Georgians, how all these aspects were reflected in Georgian prose of the second-half of XX century. This particular paper (which is a part of a larger research) focuses on major significant peculiarities of Georgian prose of 1950-1960s that might be connected to Hemingway's writing. In this respect, GuramRcheulishvili’s (1934-1960) works should be particularly distinguished (especially his short fiction), but literary works of other Georgian authors are not at all less important. The research involves the analysis of the prose works of some Georgian writers of the given period in the context of tracing similarities and parallels between them and the characteristic features of Ernest Hemingway’s writing style. The use of everyday language as well as short and simple sentences, a concise and sparse style, repetitions, intense dialogues are some of the essential traits in question. Themes like birth and death, war and violence, family, nature, disillusionment also prove to be vitally important for this research. Complex interconnections between the author, the narrator, and the protagonist (often autobiographical) provide another interesting subject to study. At the same time, this paper aims at studying and revealing how Hemingway’s method was reflected and transformed in Georgian prose. In this respect, it is interesting to trace not only the direct effect of Hemingway’s style but also the role of certain Georgian translations of the works of this American writer.

Keywords: hemingway, prose, georgian writers, writing style

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Authors: Odai Ibrahim Mohammed Al Balasmeh, Tapas Karmaker, Richa Babbar

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In this study, the reservoir capacity and sediment deposition were estimated using remote sensing data. The satellite images were synchronized with water level and storage capacity to find out the change in sediment deposition due to soil erosion and transport by streamflow. The water bodies spread area was estimated using vegetation indices, e.g., normalize differences vegetation index (NDVI) and normalize differences water index (NDWI). The 3D reservoir bathymetry was modeled by integrated water level, storage capacity, and area. From the models of different time span, the change in reservoir storage capacity was estimated. Another reservoir with known water level, storage capacity, area, and sediment deposition was used to validate the estimation technique. The t-test was used to assess the results between observed and estimated reservoir capacity and sediment deposition.

Keywords: satellite data, normalize differences vegetation index, NDVI, normalize differences water index, NDWI, reservoir capacity, sedimentation, t-test hypothesis

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Authors: Ammarah Irum, Muhammad Ali Tahir

Abstract:

Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Fariba Jafari, Samaneh Heydarian

Abstract:

Al2(HPO4)3 was easily prepared and used as a solid acid in acetalization of carbonyl compounds at room temperature and under solvent-free conditions. The protection was done in short reaction times and in good to high isolated yields. The cheapness and availability of this reagent with easy procedure and work-up make this method attractive for the organic synthesis.

Keywords: acetalization, acid catalysis, carbonylcompounds, green condition, protection

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Authors: Nouha Bouayed Abdelmoula, Rim Louati, Nawel Abdellaoui, Balkiss Abdelmoula, Oldez Kaabi, Walid Smaoui, Samir Aloulou

Abstract:

Background and Aims: Cardiofaciocutaneous syndrome (CFC) is an autosomal dominant disorder with the vast majority of cases arising by a new mutation of BRAF, MEK1, MEK2, or rarely, KRAS genes. Here, we report a rare Tunisian case of CFC syndrome for whom we identify SOS1 mutation. Methods: Genomic DNA was obtained from peripheral blood collected in an EDTA tube and extracted from leukocytes using the phenol/chloroform method according to standard protocols. High resolution melting (HRM) analysis for screening of mutations in the entire coding sequence of PTPN11 was conducted first. Then, HRM assays to look for hot spot mutations coding regions of the other genes of the RAS-MAPK pathway (RAt Sarcoma viral oncogene homolog Mitogen-Activated Protein Kinases Pathway): SOS1, SHOC2, KRAS, RAF1, KRAS, NRAS, CBL, BRAF, MEK1, MEK2, HRAS, and RIT1, were applied. Results: Heterozygous SOS1 point mutation clustered in exon 10, which encodes for the PH domain of SOS1, was identified: c.1655 G > A. The patient was a 9-year-old female born from a consanguineous couple. She exhibited pulmonic valvular stenosis as congenital heart disease. She had facial features and other malformations of Noonan syndrome, including macrocephaly, hypertelorism, ptosis, downslanting palpebral fissures, sparse eyebrows, a short and broad nose with upturned tip, low-set ears, high forehead commonly associated with bitemporal narrowing and prominent supraorbital ridges, short and/or webbed neck and short stature. However, the phenotype is also suggestive of CFC syndrome with the presence of more severe ectodermal abnormalities, including curly hair, keloid scars, hyperkeratotic skin, deep plantar creases, and delayed permanent dentition with agenesis of the right maxillary first molar. Moreover, the familial history of the patient revealed recurrent brain malignancies in the paternal family and epileptic disease in the maternal family. Conclusions: This case report of an overlapping RASopathy associated with SOS1 mutation and familial history of brain tumorigenesis is exceptional. The evidence suggests that RASopathies are truly cancer-prone syndromes, but the magnitude of the cancer risk and the types of cancer partially overlap.

Keywords: cardiofaciocutaneous syndrome, CFC, SOS1, brain cancer, germline mutation

Procedia PDF Downloads 144