Search results for: vector density

Authors: V. Pérez-Herranz, M. Pinel, E. M. Ortega, M. García-Gabaldón

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In the present work, Electrochemical Impedance Spectrocopy (EIS) is applied to study the transport of different metal cations through a cation-exchange membrane. This technique enables the identification of the ionic-transport characteristics and to distinguish between different transport mechanisms occurring at different current density ranges. The impedance spectra are dependent on the applied dc current density, on the type of cation and on the concentration. When the applied dc current density increases, the diameter of the impedance spectra loops increases because all the components of membrane system resistance increase. The diameter of the impedance plots decreases in the order of Na(I), Ni(II) and Cr(III) due to the increased interactions between the negatively charged sulfonic groups of the membrane and the cations with greater charge. Nyquist plots are shifted towards lower values of the real impedance, and its diameter decreases with the increase of concentration due to the decrease of the solution resistance.

Keywords: ion-exchange membranes, Electrochemical Impedance Spectrocopy, multivalent metal cations, membrane system

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Authors: Abdeghani Qadem

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Climate change is now an undeniable reality with increasing impacts on water systems worldwide, especially leading to severe drought episodes. The Southern Mediterranean region is particularly affected by this drought, which can have devastating consequences on water resources. Morocco, due to its geographical location in North Africa and the Southern Mediterranean, is especially vulnerable to these effects of climate change, particularly drought. In this context, this article focuses on the study of climate variability and drought characteristics in the Saiss Plateau region and its adjacent areas with the Middle Atlas, using specific statistical indices. The study begins by analyzing the annual precipitation variation, with a particular emphasis on data homogenization and gap filling using a regional vector. Then, the analysis delves into drought episodes in the region, using the Standardized Precipitation Index (SPI) over a 12-month period. The central objective is to accurately assess significant drought changes between 1980 and 2015, based on data collected from nine meteorological stations located in the study area.

Keywords: climate variability, regional vector, drought, standardized precipitation index, Saiss Plateau, middle atlas

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Authors: Saiyed M Ishtiaque, Priyal Dixit

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Objectives: An approach is being suggested to design the filter media to maximize the filtration efficiency with minimum possible pressure drop of composite nonwoven by incorporating the layers of different packing densities induced by fibre of different deniers and punching parameters by using the concept of sequential punching technique in specific order in layered composite nonwoven structure. X-ray computed tomography technique is used to measure the packing density along the thickness of layered nonwoven structure composed by placing the layer of differently oriented fibres influenced by fibres of different deniers and punching parameters in various combinations to minimize the pressure drop at maximum possible filtration efficiency. Methodology Used: This work involves preparation of needle punched layered structure with batts 100g/m2 basis weight having fibre denier, punch density and needle penetration depth as variables to produce 300 g/m2 basis weight nonwoven composite. X-ray computed tomography technique is used to measure the packing density along the thickness of layered nonwoven structure composed by placing the layers of differently oriented fibres influenced by considered variables in various combinations. to minimize the pressure drop at maximum possible filtration efficiencyFor developing layered nonwoven fabrics, batts made of fibre of different deniers having 100g/m2 each basis weight were placed in various combinations. For second set of experiment, the composite nonwoven fabrics were prepared by using 3 denier circular cross section polyester fibre having 64 mm length on needle punched nonwoven machine by using the sequential punching technique to prepare the composite nonwoven fabrics. In this technique, three semi punched fabrics of 100 g/m2 each having either different punch densities or needle penetration depths were prepared for first phase of fabric preparation. These fabrics were later punched altogether to obtain the overall basis weight of 300 g/m2. The total punch density of the composite nonwoven fabric was kept at 200 punches/ cm2 with a needle penetration depth of 10 mm. The layered structures so formed were subcategorised into two groups- homogeneous layered structure in which all the three batts comprising the nonwoven fabric were made from same denier of fibre, punch density and needle penetration depth and were placed in different positions in respective fabric and heterogeneous layered structure in which batts were made from fibres of different deniers, punch densities and needle penetration depths and were placed in different positions. Contributions: The results concluded that reduction in pressure drop is not derived by the overall packing density of the layered nonwoven fabric rather sequencing of layers of specific packing density in layered structure decides the pressure drop. Accordingly, creation of inverse gradient of packing density in layered structure provided maximum filtration efficiency with least pressure drop. This study paves the way for the possibility of customising the composite nonwoven fabrics by the incorporation of differently oriented fibres in constituent layers induced by considered variablres for desired filtration properties.

Keywords: filtration efficiency, layered nonwoven structure, packing density, pressure drop

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Authors: Marzieh Ahmadi, Ruhullah Alikhan Gorgani

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The usual methods of measuring regional inequalities can not reflect the internal changes of the country in terms of their displacement in different development groups, and the indicators of inequalities are not effective in demonstrating the dynamics of the distribution of inequality. For this purpose, this paper examines the dynamics of the urban inertial transport in the country during the period of 2006-2016 using the CIRD multidimensional index and stochastic kernel density method. it firstly selects 25 indicators in five dimensions including macroeconomic conditions, science and innovation, environmental sustainability, human capital and public facilities, and two-stage Principal Component Analysis methodology are developed to create a composite index of inequality. Then, in the second stage, using a nonparametric analytical approach to internal distribution dynamics and a stochastic kernel density method, the convergence hypothesis of the CIRD index of the Iranian provinces center is tested, and then, based on the ergodic density, long-run equilibrium is shown. Also, at this stage, for the purpose of adopting accurate regional policies, the distribution dynamics and process of convergence or divergence of the Iranian provinces for each of the five. According to the results of the first Stage, in 2006 & 2016, the highest level of development is related to Tehran and zahedan is at the lowest level of development. The results show that the central cities of the country are at the highest level of development due to the effects of Tehran's knowledge spillover and the country's lower cities are at the lowest level of development. The main reason for this may be the lack of access to markets in the border provinces. Based on the results of the second stage, which examines the dynamics of regional inequality transmission in the country during 2006-2016, the first year (2006) is not multifaceted and according to the kernel density graph, the CIRD index of about 70% of the cities. The value is between -1.1 and -0.1. The rest of the sequence on the right is distributed at a level higher than -0.1. In the kernel distribution, a convergence process is observed and the graph points to a single peak. Tends to be a small peak at about 3 but the main peak at about-0.6. According to the chart in the final year (2016), the multidimensional pattern remains and there is no mobility in the lower level groups, but at the higher level, the CIRD index accounts for about 45% of the provinces at about -0.4 Take it. That this year clearly faces the twin density pattern, which indicates that the cities tend to be closely related to each other in terms of development, so that the cities are low in terms of development. Also, according to the distribution dynamics results, the provinces of Iran follow the single-density density pattern in 2006 and the double-peak density pattern in 2016 at low and moderate inequality index levels and also in the development index. The country diverges during the years 2006 to 2016.

Keywords: Urban Disparity, CIRD Index, Convergence, Distribution Dynamics, Random Kernel Density

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Authors: Serkan Caliskan

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The aim of this study is to understand the spin-resolved properties of ZnO armchair and zigzag nanoribbons. The spin polarization can be induced by either geometry of the nanoribbons or ferromagnetic electrodes. Hence, spin-dependent behavior is revealed in these nanostructures in the absence of external magnetic field. Both electronic structure and magnetic properties of the nanoribbons are analyzed, employing first-principles calculations through Density Functional Theory. The relevant properties using the spin-dependent band structure, conductance, transmission, density of states and magnetic moment are elucidated. These results can be utilized to describe the nanoscale structures and stimulate the experimental works.

Keywords: first principles, spin polarized transport, ZnO device, ZnO nanoribbons

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Authors: A. Gürses, Z. Eroğlu, E. Şahin, K. Güneş, Ç. Doğar

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In recent years, polymer/clay nanocomposites have generated great interest in the polymer industry as a new type of composite material because of their superior properties, which includes high heat deflection temperature, gas barrier performance, dimensional stability, enhanced mechanical properties, optical clarity and flame retardancy when compared with the pure polymer or conventional composites. The investigation of change of the tensile properties of organoclay/linear low density polyethylene (LLDPE) nanocomposites with the use of Dioctyl terephthalate (DOTP) (as plasticizer) and calcite (as filler) has been aimed. The composites and organoclay synthesized were characterized using the techniques such as XRD, HRTEM and FTIR techniques. The spectroscopic results indicate that platelets of organoclay were well dispersed within the polymeric matrix. The tensile properties of the composites were compared considering the stress-strain curve drawn for each composite and pure polymer. It was observed that the composites prepared by adding the plasticizer at different ratios and a certain amount of calcite exhibited different tensile behaviors compared to pure polymer.

Keywords: linear low density polyethylene, nanocomposite, organoclay, plasticizer

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Authors: Shahriar Ghammamy, Maryam Gholipoor

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Metronidazole nano -powders with the average mean particle size around 90 nm were synthesized by high-energy milling using a planetary ball mill is provided. The Scattering factors, milling of time,the ball size and ball to powder ratio on the material properties powder by the Ray diffraction (XRD) study, scanning electron microscopy (SEM), IR. It has been observed that the density of nano-sized grinding balls as ball to powder ratio depends. Using the dispersion factor, the density Can be reduced below the initial particle size was achieved.

Keywords: metronidazole, ball-milling, nanoparticles, characterization, XRD diffraction

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Authors: Ahmad Al-Turki

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Composting is the suitable way of recycling organic waste for agricultural application and environment protection. In Saudi Arabia, several composting facilities are available and producing high quantity of composts. The aim of this study is to evaluate the physical characteristics of composts manufactured in Saudi Arabia and acquire a comprehensive image of its quality through the comparative with international standards of compost quality such as CCQC and PAS-100. In the present study different locally produced compost were identified and most of the producing factories were visited during the manufacturing of composts. Representative samples of different compost production stage were collected and Physical characteristics were determined, which included moisture content, bulk density, percentage of sand and the size of distribution of the compost particles. Results showed wide variations in all parameters investigated. Results of the study indicated generally that there is a wide variation in the physical characteristics of the types of compost under study. The initial moister contents in composts were generally low, it was less than 60% in most samples and not sufficient for microbial activities for biodegradation in 96% of the 96% of the types of compost and this will impede the decomposition of organic materials. The initial bulk density values ranged from 117 gL-1 to 1110.0 gL-1, while the final apparent bulk density ranged from 340.0 gL-1 to 1000gL-1 and about 45.4 % did not meet the ideal bulk density value. Sand percents in composts were between 3.3 % and 12.5%. This study has confirmed the need for a standard specification for compost manufactured in Saudi Arabia for agricultural use based on international standards for compost and soil characteristics and climatic conditions in Saudi Arabia.

Keywords: compost, maturity, Saudi Arabia, organic material

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Authors: Rizwan Fazal

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This study investigates the behavior of external sector of Pakistan economy and its impact on economic growth, using quarterly data for the period 1990:01-2010:04. External sector indices used in this study are financial integration, net foreign assets and trade integration. Augmented Ducky fuller confirms that all variables of external sector are non-stationary at level, but at first difference it becomes stationary. The co-integration test suggests one co-integrating variables in the study. The analysis is based on Vector Auto Regression model followed by Vector Error Correction Model. The empirical findings show that financial integration play important role in increasing economic growth in Pakistan economy while trade integration has negative effect on economic growth of Pakistan in the long run. However, the short run confirms that output lag accounts for error correction. The estimated CUSUM and CUSUMQ stability test provide information that the period of the study equation remains stable.

Keywords: financial integration, trade integration, net foreign assets, gross domestic product

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Bowen Ding, Yihao Kuang

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In recent years, with the development of large-scale pre-trained lan-guage models, building vector representations of text through deep neural network models has become a standard practice for natural language processing tasks. From the performance on downstream tasks, we can know that the text representation constructed by these models contains linguistic information, but its encoding mode and extent are unclear. In this work, a structural probe is proposed to detect whether the vector representation produced by a deep neural network is embedded with a syntax tree. The probe is trained with the deep metric learning method, so that the distance between word vectors in the metric space it defines encodes the distance of words on the syntax tree, and the norm of word vectors encodes the depth of words on the syntax tree. The experiment results on ELMo and BERT show that the syntax tree is encoded in their parameters and the word representations they produce.

Keywords: deep metric learning, syntax tree probing, natural language processing, word representations

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Authors: Dilip K. De, Olukunle C. Olawole, Emmanuel S. Joel, Moses Emetere

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A good number of electronic properties such as electrical and thermal conductivities depend on charge carrier densities of nanomaterials. By controlling the charge carrier densities during the fabrication (or growth) processes, the physical properties can be tuned. In this paper, we discuss a new technique of estimating the charge carrier densities of nanomaterials from the thermionic emission data using the newly modified Richardson-Dushman equation. We find that the technique yields excellent results for graphene and carbon nanotube.

Keywords: charge carrier density, nano materials, new technique, thermionic emission

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Authors: Nariman Shahhosseini, Sadegh Chinikar

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Introduction: Crimean-Congo hemorrhagic fever virus (CCHFV) causes severe disease with fatality rates of 30%. The virus is transmitted to humans through the bite of an infected tick, direct contact with the products of infected livestock and nosocomially. The disease occurs sporadically throughout many of African, Asian, and European countries. Different species of ticks serve either as vector or reservoir for CCHFV. Materials and Methods: A molecular survey was conducted on hard ticks (Ixodidae) in Golestan province, north of Iran during 2014-2015. Samples were sent to National Reference Laboratory of Arboviruses (Pasteur Institute of Iran) and viral RNA was detected by RT-PCR. Results: Result revealed the presence of CCHFV in 5.3% of the selected ticks. The infected ticks belonged to Hy. dromedarii, Hy. anatolicum, Hy. marginatum, and Rh. sanguineus. Conclusions: These data demonstrates that Hyalomma ticks are the main vectors of CCHFV in Golestan province. Thus, preventive strategies such as using acaricides and repellents in order to avoid contact with Hyalomma ticks are proposed. Also, personal protective equipment (PPE) must be utilized at abattoirs.

Keywords: tick, CCHFV, surveillance, vector diversity

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Authors: Ahmed Kamil Hasan Al-Ali, Bouchra Senadji, Ganesh Naik

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We propose a system to real environmental noise and channel mismatch for forensic speaker verification systems. This method is based on suppressing various types of real environmental noise by using independent component analysis (ICA) algorithm. The enhanced speech signal is applied to mel frequency cepstral coefficients (MFCC) or MFCC feature warping to extract the essential characteristics of the speech signal. Channel effects are reduced using an intermediate vector (i-vector) and probabilistic linear discriminant analysis (PLDA) approach for classification. The proposed algorithm is evaluated by using an Australian forensic voice comparison database, combined with car, street and home noises from QUT-NOISE at a signal to noise ratio (SNR) ranging from -10 dB to 10 dB. Experimental results indicate that the MFCC feature warping-ICA achieves a reduction in equal error rate about (48.22%, 44.66%, and 50.07%) over using MFCC feature warping when the test speech signals are corrupted with random sessions of street, car, and home noises at -10 dB SNR.

Keywords: noisy forensic speaker verification, ICA algorithm, MFCC, MFCC feature warping

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Authors: Muhammad Faizan Chinannai, Jaeseung Lee, Mohamed Hassan Gundu, Hyunchul Ju

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Fuel cell is known to be an effective renewable energy resource which is commercializing in the present era. It is really important to know about the improvement in performance even when the system faces some defects. This study was carried out to analyze the performance of the Polymer electrolyte fuel cell (PEFCs) under different operating conditions such as current density, relative humidity and Pt loadings considering defects with load changes. The purpose of this study is to analyze the response of the fuel cell system with defects in Balance of Plants (BOPs) and catalyst layer (CL) degradation by maintaining the coolant flow rate as such to preserve the cell temperature at the required level. Multi-Scale Simulation of 3D two-phase PEFC model with coolant was carried out under different load conditions. For detailed analysis and performance comparison, extensive contours of temperature, current density, water content, and relative humidity are provided. The simulation results of the different cases are compared with the reference data. Hence the response of the fuel cell stack with defects in BOP and CL degradations can be analyzed by the temperature difference between the coolant outlet and membrane electrode assembly. The results showed that the Failure of the humidifier increases High-Frequency Resistance (HFR), air flow defects and CL degradation results in the non-uniformity of current density distribution and high cathode activation overpotential, respectively.

Keywords: PEM fuel cell, fuel cell modeling, performance analysis, BOP components, current density distribution, degradation

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Habtamu Anagaw Muluneh, Gebregziabher Kahsay, Tamiru Negussie

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Theoretical study of the density of state, condensation energy, specific heat, and magnetization in a spin-triplet superconductor are the main goals of this work. Utilizing the retarded double-time temperature-dependent Green's function formalism and building a model Hamiltonian for the system at hand, we were able to derive the expressions for the parameters mentioned above. The phase diagrams are plotted using MATLAB scripts. From the phase diagrams, the density of electrons increases as the excitation energy increases, and the maximum excitation energy is equal to the superconducting gap, but it decreases when the value exceeds the gap and finally becomes the same as the density of the normal state. On the other hand, the condensation energy decreases with the increase in temperature and attains its minimum value at the superconducting transition temperature but increases with the increase in superconducting transition temperature (TC) and finally becomes zero, implying the superconducting energy is equal to the normal state energy. The specific heat increases with the increase in temperature, attaining its maximum value at the TC and then undergoing a jump, showing the presence of a second-order phase transition from the superconducting state to the normal state. Finally, the magnetization of both the itinerant and localized electrons decreases with the increase in temperature and finally becomes zero at TC = 1.6 K and magnetic phase transition temperature T = 2 K, respectively, which results in a magnetic phase transition from a ferromagnetic to a paramagnetic state. Our finding is in good agreement with the previous findings.

Keywords: spin triplet superconductivity, Green’s function, condensation energy, density of state, specific heat, magnetization

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Asif Mahmood, Yousef Alzeghayer

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The size effects of a precursor Y2BaCuO5 (Y211) powder on the microstructure and critical current density (Jc) of liquid infiltration growth (LIG)-processed YBa2Cu3O7-y (Y123) bulk superconductors were investigated in terms of milling time (t). YBCO bulk samples having high Jc values have been selected for the flywheel energy storage system. Y211 powders were attrition-milled for 0-10 h in 2 h increments at a fixed rotation speed of 400 RPM. Y211 pre-forms were made by pelletizing the milled Y211 powders followed by subsequent sintering, after which an LIG process with top seeding was applied to the Y211/Ba3Cu5O8 (Y035) pre-forms. Spherical pores were observed in all LIG-processed Y123 samples, and the pore density gradually decreased as t increased from 0 h to 8 h. In addition to the reduced pore density, the Y211 particle size in the final Y123 products also decreased with increasing t. As t increased further to 10 h, unexpected Y211 coarsening and large pore evolutions were observed. The magnetic susceptibility-temperature curves showed that the onset superconducting transition temperature (Tc, onset) of all samples was the same (91.5 K), but the transition width became greater as t increased. The Jc of the Y123 bulk superconductors fabricated in this study was observed to correlate well with t of the Y211 precursor powder. The maximum Jc of 1.0×105 A cm-2 (at 77 K, 0 T) was achieved at t = 8 h, which is attributed to the reduction in pore density and Y211 particle size. The prolonged milling time of t = 10 h decreased the Jc of the LIG-processed Y123 superconductor owing to the evolution of large pores and exaggerated Y211 growth. YBCO bulk samples having high Jc (samples prepared using 8 h milled powders) have been used for the energy storage system in flywheel energy storage system.

Keywords: critical current, bulk superconductor, liquid infiltration, bioinformatics

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Authors: Mahvish Maqbool, Muhmmad Sohail Sajid

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Ticks (Acari: Ixodidae); bloodsucking parasites of domestic animals, have significant importance in the transmission of diseases and causing huge economic losses. This study aimed to screen endophilic ticks for the Piroplasms using polymerase chain reaction in three districts Sialkot, Gujranwala and Gujarat of Punjab, Pakistan. Ticks were dissected under a stereomicroscope, and internal organs (midguts& salivary glands) were procured to generate pools of optimum weights. DNA extraction was done through standard protocol followed by primer specific PCR for Piroplasma spp. A total of 22.95% tick pools were found positive for piroplasma spp. In districts, Sialkot and Gujranwala Piroplasma prevalence are higher in riverine animals while in Gujarat Prevalence is higher in non-riverine animals. Female animals were found more prone to piroplasma as compared to males. This study will provide useful data on the distribution of Piroplasma in the vector population of the study area and devise future recommendations for better management of ruminants to avoid subclinical and clinical infections and vector transmitted diseases.

Keywords: babesia, hyalomma, piroplasmposis, tick infectivity

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Authors: Natarajan Ramasamy, Gurulingamurthy Haralur, Ramesh Nivarthu, Nikhil Kumar Singha

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Elastomers are polymeric materials with varied backbone architectures ranging from linear to dendrimeric structures and wide varieties of monomeric repeat units. These elastomers show strongly viscous and weakly elastic when it is not cross-linked. But when crosslinked, based on the extent the properties of these elastomers can range from highly flexible to highly stiff nature. Lightly cross-linked systems are well studied and reported. Understanding the nature of highly cross-linked rubber based upon chemical structure and architecture is critical for varieties of applications. One of the critical parameters is cross-link density. In the current work, we have studied the highly cross-linked state of linear, lightly branched to star-shaped branched elastomers and determined the cross-linked density by using different models. Change in hardness, shift in Tg, change in modulus and swelling behavior were measured experimentally as a function of the extent of curing. These properties were analyzed using varied models to determine cross-link density. We used hardness measurements to examine cure time. Hardness to the extent of curing relationship is determined. It is well known that micromechanical transitions like Tg and storage modulus are related to the extent of crosslinking. The Tg of the elastomer in different crosslinked state was determined by DMA, and based on plateau modulus the crosslink density is estimated by using Nielsen’s model. Usually for lightly crosslinked systems, based on equilibrium swelling ratio in solvent the cross link density is estimated by using Flory–Rhener model. When it comes to highly crosslinked system, Flory-Rhener model is not valid because of smaller chain length. So models based on the assumption of polymer as a Non-Gaussian chain like 1) Helmis–Heinrich–Straube (HHS) model, 2) Gloria M.gusler and Yoram Cohen Model, 3) Barbara D. Barr-Howell and Nikolaos A. Peppas model is used for estimating crosslink density. In this work, correction factors are determined to the existing models and based upon it structure-property relationship of highly crosslinked elastomers was studied.

Keywords: dynamic mechanical analysis, glass transition temperature, parts per hundred grams of rubber, crosslink density, number of networks per unit volume of elastomer

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Authors: Pager Mansaram Pandit

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The present paper aims to changing trends of population in Nashik district. The spatial variation of changing trends of population from 1901 to 2011. Nasik, lying between 19° 33’ and 20° 53’ north latitude and 73° 16’ and 75° 16’, with an area of 15530 Sq. K.M.North South length is 120 km. East West length is 200 km. Nashik has a population of 6,109,052 of which 3,164,261 are males and 2,944,791 and females. Average literacy rate of Nashik district in 2011 was 82.91 compared to 80.96 in 2001. In 1901 the density was 52 and in 2011 the density was 393 per sq. km. The progressive growth rate from 1901 to 2012 was 11.25 to 642.22 percent, respectively. The population trend is calculated with the help of time series. In 1901 population was 45.44% more and less in 1941 i.e. -13.86. From 1921 to 1981 the population was below the population trend but after 1991 population it gradually increased. The average rainfall it receives is 1034 mm. In the present times, because of advances in good climate, industrialization, development of road, University level educational facilities, religious importance, cargo services, good quality of grapes, pomegranates and onions, more and more people are being attracted towards Nashik districts. Another cause for the increase in the population is the main attraction of Ramkund, Muktidham Temple, Kalaram Temple, Coin Museum, and Trimbakeshwar.

Keywords: density, growth, population, population trend

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Authors: Anika Zafiah M. Rus, Nik Normunira Mat Hassan

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Biopolymer made from renewable material are one of the most important group of polymer because of their versatility and they can be manufactured in a wide range of densities and stiffness. In this project, biopolymer based on waste vegetable oil were synthesized and crosslink with commercial polymethane polyphenyl isocyanate (known as BF).The BF was compressed by using hot compression moulding technique at 90 oC based on the evaporation of volatile matter and known as compress biopolymer (CB). The density, vibration and damping characteristic of CB were determined after UV irradiation. Treatment with titanium dioxide (TiO2) was found to affect the physical property of compress biopolymer composite (CBC). The density of CBC samples was steadily increased with an increase of UV irradiation time and TiO2 loading. The highest density of CBC samples is at 10 % of TiO2 loading of 1.1088 g/cm3 due to the amount of filler loading. The vibration and damping characteristic of CBC samples was generated at displacements of 1 mm and 1.5 mm and acceleration of 0.1 G and 0.15 G base excitation according to ASTM D3580-9. It was revealed that, the vibration and damping characteristic of CBC samples is significantly increased with the increasing of UV irradiation time, lowest thickness and percentages of TiO2 loading at the frequency range of 15 - 25 Hz. Therefore, this study indicated that the damping property of CBC could be improved upon prolonged exposure to UV irradiation.

Keywords: biopolymer flexible foam, TGA, UV irradiation, vibration and damping

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Authors: Mohsina Akhter

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Cancer has become a wide spread disease around the globe and takes many lives every year. Different treatments are being practiced but all have potential side effects with somewhat less specificity towards target sites. Pseudomonas aeruginosa is known to secrete a protein azurin with special anti-cancer function. It has unique cell penetrating peptide comprising of 18 amino acids that have ability to enter cancer cells specifically. Reported function of Azurin is to stabilize p53 inside the tumor cells and induces apoptosis through Bax mediated cytochrome c release from mitochondria. At laboratory scale, we have made recombinant azurin through cloning rpTZ57R/T-azu vector into E.coli strain DH-5α and subcloning rpET28-azu vector into E.coli BL21-CodonPlus (DE3). High expression was ensured with IPTG induction at different concentrations then optimized high expression level at 1mM concentration of IPTG for 5 hours. Purification has been done by using Ni+2 affinity chromatography. We have concluded that azurin can be a remarkable improvement in cancer therapeutics if it produces on a large scale. Azurin does not enter into the normal cells so it will prove a safe and secure treatment for patients and prevent them from hazardous anomalies.

Keywords: azurin, pseudomonas aeruginosa, cancer, therapeutics

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Authors: Samuel Fekadu A., Esayas Alemayehu B., Bultum Oljira D., Seid Tiku D., Dessalegn Dadi D., Bart Van Der Bruggen A.

Abstract:

The peroxi-photoelectrocoagulation process was evaluated for the removal of chemical oxygen demand (COD) and color from healthcare wastewater. A 2-level full factorial design with center points was created to investigate the effect of the process parameters, i.e., initial COD, H₂O₂, pH, reaction time and current density. Furthermore, the total energy consumption and average current efficiency in the system were evaluated. Predictive models for % COD, % color removal and energy consumption were obtained. The initial COD and pH were found to be the most significant variables in the reduction of COD and color in peroxi-photoelectrocoagulation process. Hydrogen peroxide only has a significant effect on the treated wastewater when combined with other input variables in the process like pH, reaction time and current density. In the peroxi-photoelectrocoagulation process, current density appears not as a single effect but rather as an interaction effect with H₂O₂ in reducing COD and color. Lower energy expenditure was observed at higher initial COD, shorter reaction time and lower current density. The average current efficiency was found as low as 13 % and as high as 777 %. Overall, the study showed that hybrid electrochemical oxidation can be applied effectively and efficiently for the removal of pollutants from healthcare wastewater.

Keywords: electrochemical oxidation, UV, healthcare pollutants removals, factorial design

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Authors: Shreyas Gambhirrao, Aditya Vichare, Aniket Tembhurne, Shahuraj Bhosale

Abstract:

In today's rapidly evolving environment, stress has emerged as a significant health concern across different age groups. Stress that isn't controlled, whether it comes from job responsibilities, health issues, or the never-ending news cycle, can have a negative effect on our well-being. The problem is further aggravated by the ongoing connection to technology. In this high-tech age, identifying and controlling stress is vital. In order to solve this health issue, the study focuses on three key metrics for stress detection: body temperature, heart rate, and galvanic skin response (GSR). These parameters along with the Support Vector Machine classifier assist the system to categorize stress into three groups: 1) Stressed, 2) Not stressed, and 3) Moderate stress. Proposed training model, a NodeMCU combined with particular sensors collects data in real-time and rapidly categorizes individuals based on their stress levels. Real-time stress detection is made possible by this creative combination of hardware and software.

Keywords: real time stress detection, NodeMCU, sensors, heart-rate, body temperature, galvanic skin response (GSR), support vector machine

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Authors: Qiuhao Chang, Liangliang Huang, Xingru Wu

Abstract:

In the United States, over 90% of the roads are paved with asphalt. The aging of asphalt is the most serious problem that causes the deterioration of asphalt pavement. Waste cooking oils (WCOs) have been found they can restore the properties of aged asphalt and promote the reuse of aged asphalt pavement. In our previous study, it was found the optimal WCO concentration to restore the aged asphalt sample should be in the range of 10~15 wt% of the aged asphalt sample. After the WCO concentration exceeds 15 wt%, as the WCO concentration increases, some important properties of the asphalt sample can be weakened by the addition of WCO, such as cohesion energy density, surface free energy density, bulk modulus, shear modulus, etc. However, maximizing the utilization of WCO can create environmental and economic benefits. Therefore, in this study, a new idea about using the waste polymer is another additive to restore the WCO modified asphalt that contains a high concentration of WCO (15-25 wt%) is proposed, which has never been reported before. In this way, both waste polymer and WCO can be utilized. The molecular dynamics simulation is used to study the effect of waste polymer on properties of WCO modified asphalt and understand the corresponding mechanism at the molecular level. The radial distribution function, self-diffusion, cohesion energy density, surface free energy density, bulk modulus, shear modulus, adhesion energy between asphalt and aggregate are analyzed to validate the feasibility of combining the waste polymer and WCO to restore the aged asphalt. Finally, the optimal concentration of waste polymer and WCO are determined.

Keywords: reclaim aged asphalt pavement, waste cooking oil, waste polymer, molecular dynamics simulation

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Authors: Chao Hu, Xinwen Liao, Qing-Hua Qin, Gang Wang

Abstract:

The hierarchical carbon nanotube (CNT)/carbon fiber (CF)/high density polyethylene (HDPE) was fabricated via compound extrusion and injection molding, in which to author’s best knowledge CNT was employed as a nano-coatings on the surface of CF for the first time by spray coating technique. The CNT coatings relative to CF was set at 1 wt% and the CF content relative to the composites varied from 0 to 25 wt% to study the influence of CNT coatings and CF contents on the mechanical, thermal and morphological performance of this hierarchical composites. The results showed that with the rise of CF contents, the mechanical properties, including the tensile properties, flexural properties, and hardness of CNT/CF/HDPE composites, were effectively improved. Furthermore, the CNT-coated composites showed overall higher mechanical performance than the uncoated counterparts. It can be ascribed to the enhancement of interfacial bonding between the CF and HDPE via the incorporation of CNT, which was demonstrated by the scanning electron microscopy observation. Meanwhile, the differential scanning calorimetry data indicated that by the introduction of CNT and CF, the crystallization temperature and crystallinity of HDPE were affected while the melting temperature did not have an obvious alteration.

Keywords: carbon fibers, carbon nanotubes, extrusion, high density polyethylene

Procedia PDF Downloads 138

Authors: Chusak Thanawattano, Roongroj Bhidayasiri

Abstract:

This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

Abstract:

The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

Procedia PDF Downloads 313