Search results for: normalized Laplacian matrix

Authors: A. Maghari, V. M. Maleki

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In this paper, we present a quantum statistical mechanical formulation from our recently analytical expressions for partial-wave transition matrix of a three-particle system. We report the quantum reactive cross sections for three-body scattering processes 1 + (2,3)-> 1 + (2,3) as well as recombination 1 + (2,3) -> 2 + (3,1) between one atom and a weakly-bound dimer. The analytical expressions of three-particle transition matrices and their corresponding cross-sections were obtained from the three-dimensional Faddeev equations subjected to the rank-two non-local separable potentials of the generalized Yamaguchi form. The equilibrium quantum statistical mechanical properties such partition function and equation of state as well as non-equilibrium quantum statistical properties such as transport cross-sections and their corresponding transport collision integrals were formulated analytically. This leads to obtain the transport properties, such as viscosity and diffusion coefficient of a moderate dense gas.

Keywords: statistical mechanics, nonlocal separable potential, three-body interaction, faddeev equations

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

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Authors: Rogelio Portillo Vélez, Eduardo Vázquez-Santacruz, Mariano Gamboa-Zúñiga

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In this paper a new mechanical architecture design of a multi functional robot bed, is presented. The importance of this design relies on the fact that in next years the need of assistive devices development will increase in such way that elderly patients will use this kind of devices. This mechanical design implies following specific mechanisms which attend Mexican hospital requirements. This design is the base of next step of this kind of development given that it shows all technical details of the mechanical systems which are needed in order to construct the bed. This is first hospital bed design which could responds to the Latin America hospital requirements. We have obtained these hospital requirements using our diagnosis methodology [14]. From these results we have designed the mechanical system. This is the mechanical base of the hospital robotic bed which is being developed in our robotics laboratory. It will be useful in different hospital environments for elderly and disabled patients.

Keywords: assistive robotics, methodology, feasibility analysis, robotics, operational feasibility, assistive technology, viability analysis matrix, social impact

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Anil Saini, Jatinder Kumar Ratan

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Now a day, the key issue for the scientific community is to devise the innovative technologies for sustainable control of urban pollution. In urban cities, a large surface area of the masonry structures, buildings, and pavements is exposed to the open environment, which may be utilized for the control of air pollution, if it is built from the photocatalytically active cement-based constructional materials such as concrete, mortars, paints, and blocks, etc. The photocatalytically active cement is formulated by incorporating a photocatalyst in the cement matrix, and such cement is generally known as self-cleaning cement In the literature, self-cleaning cement has been synthesized by incorporating nanosized-TiO₂ (n-TiO₂) as a photocatalyst in the formulation of the cement. However, the utilization of n-TiO₂ for the formulation of self-cleaning cement has the drawbacks of nano-toxicity, higher cost, and agglomeration as far as the commercial production and applications are concerned. The use of microsized-TiO₂ (m-TiO₂) in place of n-TiO₂ for the commercial manufacture of self-cleaning cement could avoid the above-mentioned problems. However, m-TiO₂ is less photocatalytically active as compared to n- TiO₂ due to smaller surface area, higher band gap, and increased recombination rate. As such, the use of m-TiO₂ in the formulation of self-cleaning cement may lead to a reduction in photocatalytic activity, thus, reducing the self-cleaning, depolluting, and antimicrobial abilities of the resultant cement material. So improvement in the photoactivity of m-TiO₂ based self-cleaning cement is the key issue for its practical applications in the present scenario. The current work proposes the use of surface-fluorinated m-TiO₂ for the formulation of self-cleaning cement to enhance its photocatalytic activity. The calcined dolomite, a constructional material, has also been utilized as co-adsorbent along with the surface-fluorinated m-TiO₂ in the formulation of self-cleaning cement to enhance the photocatalytic performance. The surface-fluorinated m-TiO₂, calcined dolomite, and the formulated self-cleaning cement were characterized using diffuse reflectance spectroscopy (DRS), X-ray diffraction analysis (XRD), field emission-scanning electron microscopy (FE-SEM), energy dispersive x-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), BET (Brunauer–Emmett–Teller) surface area, and energy dispersive X-ray fluorescence spectrometry (EDXRF). The self-cleaning property of the as-prepared self-cleaning cement was evaluated using the methylene blue (MB) test. The depolluting ability of the formulated self-cleaning cement was assessed through a continuous NOX removal test. The antimicrobial activity of the self-cleaning cement was appraised using the method of the zone of inhibition. The as-prepared self-cleaning cement obtained by uniform mixing of 87% clinker, 10% calcined dolomite, and 3% surface-fluorinated m-TiO₂ showed a remarkable self-cleaning property by providing 53.9% degradation of the coated MB dye. The self-cleaning cement also depicted a noteworthy depolluting ability by removing 5.5% of NOx from the air. The inactivation of B. subtiltis bacteria in the presence of light confirmed the significant antimicrobial property of the formulated self-cleaning cement. The self-cleaning, depolluting, and antimicrobial results are attributed to the synergetic effect of surface-fluorinated m-TiO₂ and calcined dolomite in the cement matrix. The present study opens an idea and route for further research for acile and economical formulation of self-cleaning cement.

Keywords: microsized-titanium dioxide (m-TiO₂), self-cleaning cement, photocatalysis, surface-fluorination

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Authors: Yan Lu, Song Hong, Janakiraman Udaiyappan, Aarti Nagayach, Quoc-Viet A. Duong, Masao Morita, Shun Saito, Yuichi Kobayashi, Yuhai, Zhao, Hongying Peng, Nicholas B. Pham, Walter J Lukiw, Christopher A. Vuong, Nicolas G. Bazan

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Aims: Neurodegeneration and behavior dysfunction occurs in patients with Alzheimer's Disease (AD), and as the disease progresses many patients develop cognitive impairment. 5XFAD mouse model of AD is widely used to study AD pathogenesis and treatment. This study aimed to investigate the effect of maresin like 1 (MaR-L1) treatment in AD pathology using 5XFAD mice. Methods: We tested 12-month-old male 5XFAD mice and wild type control mice treated with MaR-L1 in a battery of behavioral tasks. We performed open field test, beam walking test, clasping test, inverted grid test, acetone test, marble burring test, elevated plus maze test, cross maze test and novel object recognition test. We also studied neuronal loss, amyloid β burden, and inflammation in the brains of 5XFAD mice using immunohistology and Western blotting. Results: MaR-L1 treatment to the 5XFAD mice showed improved cognitive function of 5XFAD mice. MaR-L1 showed decreased anxiety behavior in open field test and marble burring test, increased muscular strength in the beam walking test, clasping test and inverted grid test. Cognitive function was improved in MaR-L1 treated 5XFAD mice in the novel object recognition test. MaR-L1 prevented neuronal loss and aberrant inflammation. Conclusion: Our finding suggests that behavioral abnormalities were normalized by the administration of MaR-L1 and the neuroprotective role of MaR-L1 in the AD. It also indicates that MaR-L1 treatment is able to prevent and or ameliorate neuronal loss and aberrant inflammation. Further experiments to validate the results are warranted using other AD models in the future.

Keywords: Alzheimer's disease, motor and cognitive behavior, 5XFAD mice, Maresin Like 1, microglial cell, astrocyte, neurodegeneration, inflammation, resolution of inflammation

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Authors: Elena Barbaro, Elena Gregoris, Rossano Piazza, Boris Mifka, Tatjana Ivošević, Ivo Orlić, Ana Alebić-Juretić, Andrea Gambaro, Daniele Contini

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The aim of the POSEIDON project is to quantify the relative contribution of maritime traffic and harbor activities to atmospheric pollutants concentration in four port-cities of the Adriatic Sea. This study focuses on the harbors of Venice and Rijeka. In order to investigate the main pollution sources, emission inventories were used as input for receptor models: PMF (positive matrix factorization) and PCA (principal components analysis); moreover source identification was also conducted using PAHs diagnostic ratios. The ship traffic impact was quantified: i) on gaseous and particulate PAHs, collected using a new method which consisted in a double simultaneous sampling, in different wind sectors; ii) applying PMF to data of metals, PAHs and ions in PM10; iii) using the vanadium concentration according to the Agrawal methodology.

Keywords: ship traffic, PMF, harbor, POSEIDON

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Authors: Reshma Jolly, Mohammad Shakir, Mohammad Shoeb Khan, Noor E. Iram

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A nanocomposite system integrating hydroxyapatite, chitin and starch (n-HA/CT/ST) has been synthesized via co-precipitation approach at room temperature, addressing the issues of biocompatibility, mechanical strength and cytotoxicity required for Bone tissue engineering. The interactions, crystallite size and surface morphology against n-HA/CT (nano-hydroxyapatite/chitin) nanocomposite have been obtained by correlating and comparing the results of FTIR, SEM, TEM and XRD. The comparative study of the bioactivity of n-HA/CT and n-HA/CT/ST nanocomposites revealed that the incorporation of starch as templating agent improved these properties in n-HA/CT/ST nanocomposite. The rise in thermal stability in n-HA/CT/ST nanocomposite as compared to n-HA/CT has been observed by comparing the TGA results. The comparison of SEM images of both the scaffolds indicated that the addition of ST influenced the surface morphology of n-HA/CT scaffold which appeared to be rougher and porous. The MTT assay on murine fibroblast L929 cells and in-vitro bioactivity of n-HA/CT/ST matrix referred superior non-toxic property of n-HA/CT/ST nanocomposite and higher possibility of osteo-integration in-vivo, respectively.

Keywords: bioactive, chitin, hyroxyapatite, nanocomposite

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Authors: F. Brunke, L. Waalkes, C. Siemers

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Due to reduced stiffness, research on second generation titanium alloys for implant applications, like the metastable β-titanium alloy Ti-15Mo, become more and more important in the recent years. The machinability of these alloys is generally poor leading to problems during implant production and comparably large production costs. Therefore, in the present study, Ti 15Mo was alloyed with 0.8 wt.-% of the rare earth metals lanthanum (Ti-15Mo+0.8La) and neodymium (Ti-15Mo+0.8Nd) to improve its machinability. Their microstructure consisted of a titanium matrix and micrometer-size particles of the rare earth metals and two of their oxides. The particles stabilized the micro structure as grain growth was minimized. As especially the ductility might be affected by the precipitates, the behavior of Ti-15Mo+0.8La and Ti-15Mo+0.8Nd was investigated during static and dynamic deformation at elevated temperature to develop a processing route. The resulting mechanical properties (static strength and ductility) were similar in all investigated alloys.

Keywords: Ti 15Mo, titanium alloys, rare earth metals, free machining alloy

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Authors: Nazila Dehbari, Javad Tavakoli, Yakani Kambu, Youhong Tang

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Superabsorbent hydrogels (SAP), as an enviro-sensitive material have been widely used for industrial and biomedical applications due to their unique structure and capabilities. Poor mechanical properties of SAPs - which is extremely related to their large volume change – count as a great weakness in adopting for high-tech applications. Therefore, improving SAPs’ mechanical properties via toughening methods by mixing different types of cross-linked polymer or introducing energy-dissipating mechanisms is highly focused. In this work, in order to change the intrinsic brittle character of commercialized Poly Acrylic Acid (here as SAP) to be semi-ductile, a commercial available highly branched tree-like dendritic polymers with numerous –OH end groups known as hyper-branched polymer (HB) has been added to PAA-SAP system in a single step, cost effective and environment friendly solvent casting method. Samples were characterized by FTIR, SEM and TEM and their physico-chemical characterization including swelling capabilities, hydraulic permeability, surface tension and thermal properties had been performed. Toughness energy, stiffness, elongation at breaking point, viscoelastic properties and samples extensibility were mechanical properties that had been performed and characterized as a function of samples lateral cracks’ length in different HB concentration. Addition of HB to PAA-SAP significantly improved mechanical and surface properties. Increasing equilibrium swelling ratio by about 25% had been experienced by the SAP-HB samples in comparison with SAPs; however, samples swelling kinetics remained without changes as initial rate of water uptake and equilibrium time haven’t been subjected to any changes. Thermal stability analysis showed that HB is participating in hybrid network formation while improving mechanical properties. Samples characterization by TEM showed that, the aggregated HB polymer binders into nano-spheres with diameter in range of 10–200 nm. So well dispersion in the SAP matrix occurred as it was predictable due to the hydrophilic character of the numerous hydroxyl groups at the end of HB which enhance the compatibility of HB with PAA-SAP. As the profused -OH groups in HB could react with -COOH groups in the PAA-SAP during the curing process, the formation of a 2D structure in the SAP-HB could be attributed to the strong interfacial adhesion between HB and the PAA-SAP matrix which hinders the activity of PAA chains (SEM analysis). FTIR spectra introduced new peaks at 1041 and 1121 cm-1 that attributed to the C–O(–OH) stretching hydroxyl and O–C stretching ester groups of HB polymer binder indicating the incorporation of HB polymer into the SAP structure. SAP-HB polymer has significant effects on the final mechanical properties. The brittleness of PAA hydrogels are decreased by introducing HB as the fracture energies of hydrogels increased from 8.67 to 26.67. PAA-HBs’ stretch ability enhanced about 10 folds while reduced as a function of different notches depth.

Keywords: superabsorbent polymer, toughening, viscoelastic properties, hydrogel network

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Authors: Longlong Zhang, Xiaohua Zhu, Ping Zhao, Yu Wang

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The construction of mines, railways, highways, water conservancy projects, etc., have formed a large number of high steep slope wounds in China. Under the premise of slope stability and safety, the minimum cost, green and close to natural wound space repair, has become a new problem. Nowadays, in situ element testing and analysis, monitoring, field quantitative factor classification, and assignment evaluation will produce vast amounts of data. Data processing and analysis will inevitably differentiate the morphology, mineral composition, physicochemical properties between rock wounds, by which to dynamically match the appropriate techniques and materials for restoration. In the present research, based on the grid partition of the slope surface, tested the content of the combined oxide of rock mineral (SiO₂, CaO, MgO, Al₂O₃, Fe₃O₄, etc.), and classified and assigned values to the hardness and breakage of rock texture. The data of essential factors are interpolated and normalized in GIS, which formed the differential zoning map of slope space. According to the physical and chemical properties and spatial morphology of rocks in different zones, organic acids (plant waste fruit, fruit residue, etc.), natural mineral powder (zeolite, apatite, kaolin, etc.), water-retaining agent, and plant gum (melon powder) were mixed in different proportions to form rock aging agents. To spray the aging agent with different formulas on the slopes in different sections can affectively age the fresh rock wound, providing convenience for seed implantation, and reducing the transformation of heavy metals in the rocks. Through many practical engineering practices, a dynamic data platform of rock aging agent formula system is formed, which provides materials for the restoration of different slopes. It will also provide a guideline for the mixed-use of various natural materials to solve the complex, non-uniformity ecological restoration problem.

Keywords: data-driven, dynamic state, high steep slope, rock aging agent, wounds

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Authors: Maryam Kiani

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The aim of this study was to investigate the influence of nanoparticles additive on the properties of fly ash-based geopolymer. The geopolymer samples were prepared using fly ash as the primary source material, along with an alkali activator solution and different concentrations of carbon black additive. The effects of nanoparticles flexural strength, water absorption, and micro-structural properties of the cured samples. The results revealed that the inclusion of nanoparticles additive significantly enhanced the mechanical and electrical properties of the geopolymer binder. Micro-structural analysis using scanning electron microscopy (SEM) revealed a more compact and homogeneous structure in the geopolymer samples with nanoparticles. The dispersion of nanoparticles particles within the geopolymer matrix was observed, suggesting improved inter-particle bonding and increased density. Overall, this study demonstrates the positive impact of nanoparticles additive on the qualities of fly ash-based geopolymer, emphasizing its potential as an effective enhancer for geopolymer binder applications for the development of construction and infrastructure for energy buildings.

Keywords: fly-ash, geopolymer, energy buildings, nanotechnology

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Saltanat Zhilkibayeva, Muratulla Utenov, Nurzhan Utenov

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The distributed inertia forces of complex nature appear in links of rod mechanisms within the motion process. Such loads raise a number of problems, as the problems of destruction caused by a large force of inertia; elastic deformation of the mechanism can be considerable, that can bring the mechanism out of action. In this work, a new analytical approach for the definition of internal forces in links of robotic systems and mechanisms with statically indeterminate and determinate structures taking into account the distributed inertial and concentrated forces is proposed. The relations between the intensity of distributed inertia forces and link weight with geometrical, physical and kinematic characteristics are determined in this work. The distribution laws of inertia forces and dead weight make it possible at each position of links to deduce the laws of distribution of internal forces along the axis of the link, in which loads are found at any point of the link. The approximation matrixes of forces of an element under the action of distributed inertia loads with the trapezoidal intensity are defined. The obtained approximation matrixes establish the dependence between the force vector in any cross-section of the element and the force vector in calculated cross-sections, as well as allow defining the physical characteristics of the element, i.e., compliance matrix of discrete elements. Hence, the compliance matrixes of an element under the action of distributed inertial loads of trapezoidal shape along the axis of the element are determined. The internal loads of each continual link are unambiguously determined by a set of internal loads in its separate cross-sections and by the approximation matrixes. Therefore, the task is reduced to the calculation of internal forces in a final number of cross-sections of elements. Consequently, it leads to a discrete model of elastic calculation of links of rod mechanisms. The discrete model of the elements of mechanisms and robotic systems and their discrete model as a whole are constructed. The dynamic equilibrium equations for the discrete model of the elements are also received in this work as well as the equilibrium equations of the pin and rigid joints expressed through required parameters of internal forces. Obtained systems of dynamic equilibrium equations are sufficient for the definition of internal forces in links of mechanisms, which structure is statically definable. For determination of internal forces of statically indeterminate mechanisms (in the way of determination of internal forces), it is necessary to build a compliance matrix for the entire discrete model of the rod mechanism, that is reached in this work. As a result by means of developed technique the programs in the MAPLE18 system are made and animations of the motion of the fourth class mechanisms of statically determinate and statically indeterminate structures with construction on links the intensity of cross and axial distributed inertial loads, the bending moments, cross and axial forces, depending on kinematic characteristics of links are obtained.

Keywords: distributed inertial forces, internal forces, statically determinate mechanisms, statically indeterminate mechanisms

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Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Siddhartha Khare, Suyash Khare

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Phenology, a crucial discipline in ecology, offers insights into the seasonal dynamics of organisms within natural ecosystems and the underlying environmental triggers. Leveraging the potent capabilities of digital repeat photography, PhenoCams capture invaluable data on the phenology of crops, plants, and trees. These cameras yield digital imagery in Red Green Blue (RGB) color channels, and some advanced systems even incorporate Near Infrared (NIR) bands. This study presents compelling case studies employing PhenoCam technology to unravel the phenology of black spruce trees. Through the analysis of RGB color channels, a range of essential color metrics including red chromatic coordinate (RCC), green chromatic coordinate (GCC), blue chromatic coordinate (BCC), vegetation contrast index (VCI), and excess green index (ExGI) are derived. These metrics illuminate variations in canopy color across seasons, shedding light on bud and leaf development. This, in turn, facilitates a deeper understanding of phenological events and aids in delineating the growth periods of trees and plants. The initial phase of this study addresses critical questions surrounding the fidelity of continuous canopy greenness records in representing bud developmental phases. Additionally, it discerns which color-based index most accurately tracks the seasonal variations in tree phenology within evergreen forest ecosystems. The subsequent section of this study delves into the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology. This is achieved through a fortnightly comparative analysis of the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). By employing PhenoCam technology and leveraging advanced color metrics, this study significantly advances our comprehension of black spruce tree phenology, offering valuable insights for ecological research and management.

Keywords: phenology, remote sensing, phenocam, color metrics, NDVI, GCC

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Authors: Hyuk Sang Yoo, Young Ju Son, Wei Mao, Myung Gu Kang, Sol Lee

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Biomedical applications of electrospun nanofibrous meshes have been received tremendous attentions because of their unique structures and versatilities as biomaterials. Incorporation of growth factors in fibrous meshes can be performed by surface-modification and encapsulation. Those growth factors stimulate differentiation and proliferation of specific types of cells and thus lead tissue regenerations of specific cell types. Topographical cues of electrospun nanofibrous meshes also increase differentiation of specific cell types according to alignments of fibrous structures. Wound healing treatments of diabetic ulcers were performed using nanofibrous meshes encapsulating multiple growth factors. Aligned nanofibrous meshes and those with random configuration were compared for differentiating mesenchymal stem cells into neuronal cells. Thus, nanofibrous meshes can be applied to drug delivery carriers and matrix for promoting cellular proliferation.

Keywords: nanofiber, tissue, mesh, drug

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Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

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Authors: Sujosh Nandi, Proshanta Guha

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Synthetic plastics are preferred for food packaging due to high strength, stretch-ability, good water vapor and gas barrier properties, transparency and low cost. However, environmental pollution generated by these synthetic plastics is a major concern of modern human civilization. Therefore, use of biodegradable polymers as a substitute for synthetic non-biodegradable polymers are encouraged to be used even after considering drawbacks related to mechanical and barrier properties of the films. Starch is considered one of the potential raw material for the biodegradable polymer, encounters poor water barrier property and mechanical properties due to its hydrophilic nature. That apart, recrystallization of starch molecules occurs during aging which decreases flexibility and increases elastic modulus of the film. The recrystallization process can be minimized by blending of other hydrocolloids having similar structural compatibility, into the starch matrix. Therefore, incorporation of guar gum having a similar structural backbone, into the starch matrix can introduce a potential film into the realm of biodegradable polymer. However, hydrophilic nature of both starch and guar gum, water barrier property of the film is low. One of the prospective solution to enhance this could be modification of the potato starch/guar gum (PSGG) composite film using cross-linker. Over the years, several cross-linking agents such as phosphorus oxychloride, sodium trimetaphosphate, etc. have been used to improve water vapor permeability (WVP) of the films. However, these chemical cross-linking agents are toxic, expensive and take longer time to degrade. Therefore, naturally available carboxylic acid (tartaric acid, malonic acid, succinic acid, etc.) had been used as a cross-linker and found that water barrier property enhanced substantially. As per our knowledge, no works have been reported with tartaric acid and succinic acid as a cross-linking agent blended with the PSGG films. Therefore, the objective of the present study was to examine the changes in water vapor barrier property and mechanical properties of the PSGG films after cross-linked with tartaric acid (TA) and succinic acid (SA). The cross-linkers were blended with PSGG film-forming solution at four different concentrations (4, 8, 12 & 16%) and cast on teflon plate at 37°C for 20 h. From the fourier-transform infrared spectroscopy (FTIR) study of the developed films, a band at 1720cm-1 was observed which is attributed to the formation of ester group in the developed films. On the other hand, it was observed that tensile strength (TS) of the cross-linked film decreased compared to non-cross linked films, whereas strain at break increased by several folds. Moreover, the results depicted that tensile strength diminished with increasing the concentration of TA or SA and lowest TS (1.62 MPa) was observed for 16% SA. That apart, maximum strain at break was also observed for TA at 16% and the reason behind this could be a lesser degree of crystallinity of the TA cross-linked films compared to SA. However, water vapor permeability of succinic acid cross-linked film was reduced significantly, but it was enhanced significantly by addition of tartaric acid.

Keywords: cross linking agent, guar gum, organic acids, potato starch

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Authors: Rania F. Ahmed, Sally A. El Awdan, Gehad A. Abdel Jaleel, Dalia O. Saleh, Omar A. H. Ahmed-Farid

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The metabolic syndrome is an important public health concern often related to obesity, improper diet, and sedentary lifestyles and can predispose individuals to the development of many dangerous health conditions, disability and early death. This research aimed to investigate the efficacy of resveratrol (RSV) to reverse the neuro-complications associated with metabolic syndrome experimentally-induced in rats using an eight weeks high fat, high fructose diet (HFHF) model. The corresponding drug treatments were administered orally during the last 10 days of the diet. Behavioural tests namely the open field test (OFT) and the forced swimming test (FST) were conducted. Brain levels of monoamines viz. serotonin, norepinephrine and dopamine as well as their metabolites were assessed. 8-hydroxyguanosine (8-OHDG) as an indicative of DNA-fragmentation, nitric oxide (NOx) and tumor necrosis factor-α (TNF- α) were estimated. Finally, brain antioxidant parameters namely malondialdehyde (MDA), reduced and oxidized glutathione (GSH, GSSG) were evaluated. HFHF-induced metabolic syndrome resulted in decreased activity in the OFT and increased immobility duration in the FST. Furthermore, HFHF-induced metabolic syndrome lead to a significant increase in brain monoamines turn over as well as elevation in 8-OHDG, NOx, TNF- α, MDA and GSSG; and reduction in GSH. Ten days daily treatment with RSV (20 and 40 mg/kg p.o) dose dependently increased activity in the OFT and decreased immobility duration in the FST. Moreover, RSV normalized brain monoamines contents, reduced 8-OHDG, NOx, TNF- α, MDA and GSSG; and elevated GSH. In conclusion, we can say that RSV showed neuro-protective properties against HFHF-induced metabolic syndrome represented by monoamines preservation, prevention of neurodegeneration, anti-inflammatory and antioxidant potentials and could be recommended as a beneficial daily dietary supplement to treat the neuronal side effects associated with HFHF-induced metabolic syndrome.

Keywords: antioxidants, DNA-fragmentation, forced swimming test, HFHF-induced metabolic syndrome, monoamines, nitric oxide (NOx), open field, resveratrol, tumor necrosis factor-α (TNF- α), 8-hydroxyguanosine (8-OHDG)

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Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

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Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: FSDWT, key frame extraction, shot detection, singular value decomposition

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Authors: Huanhuan Zhao, Bryony J. James

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The relationship between the non-fat solid ratio and bloom formation in untempered chocolate was investigated using two types of chocolate: model chocolate made of varying cocoa powder ratios (46, 49.5 and 53%) and cocoa butter, and commercial Lindt chocolate with varying cocoa content (70, 85 and 90%). X-ray diffraction and colour measurement techniques were used to examine the polymorphism of cocoa butter and the surface whiteness index (WI), respectively. The polymorphic transformation of cocoa butter was highly correlated with the changes of WI during 30 days of storage since it led to the redistribution of fat within the chocolate matrix and resulted in a bloomed surface. The change in WI indicated a similar bloom rate in the chocolates, but the model chocolates with a higher cocoa powder ratio had more pronounced total bloom. This is due to a higher ratio of non-fat solid particles on the surface resulting in microscopic changes in morphology. The ratio of non-fat solids is an important factor in determining the extent of bloom but not the bloom rate.

Keywords: untempered chocolate, microstructure of bloom, polymorphic transformation, surface whiteness

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Authors: Kathryn Nderitu, Atunga Nyachieo, Ezekiel Mecha

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Introduction: Solanum nigrum , also known as black nightshade, biosynthesizes various phytochemical compounds with various pharmacological activities, including treating cardiovascular diseases and type 2 diabetes, among others. Materials and Methods: To assess the anti-obesity effects of Solanum nigrum using high-fat-fed diet rats, Sprague Dawley male rats (n = 35) of weights 160–180 g were assigned randomly into seven groups comprising n = 5 rats each. Each group was fed for 11 weeks as follows: normal group (normal chow rat feed); high-fat diet control (HFD); HFD and standard drug (Orlistat 30 mg/kg bw); HFD and methanolic extract 150 mg/kgbw; HFD and methanolic extract 300 mg/kgbw; HFD and dichloromethane extract 150 mg/kgbw; HFD and dichloromethane extract 300 mg/kgbw. Body mass index and food intake were monitored per week, and an oral glucose tolerance test was measured in weeks 5 and 10. Lipid profiles, liver function tests, adipose tissue, liver weights, and phytochemical analysis of Solanum nigrum were later carried out. Results: High-fat diet control group rats exhibited a significant increase in body mass index (BMI), while rats administered with leaf extracts of Solanum nigrum showed a reduction in BMI. Both low doses of dichloromethane (150 mg/kgbw) and high doses of methanol extracts (300 mg/kgbw) showed a better reduction in BMI than the other treatment groups. A significant decrease (p <0.05) in low-density lipoprotein-cholesterol, triglycerides, and cholesterol was observed among the rats administered with Solanum nigrum extracts compared to those of HFD control. Moreover, the HFD control group significantly increased liver and adipose tissue weights compared to other treatment groups (p<0.05). Solanum nigrum also decreased glycemic levels and normalized the hepatic enzymes of HFD control. However, food intake among the groups showed no significant difference (p>0.05). Qualitative analysis of Solanum nigrum leaf extracts indicated the presence of various bioactive compounds associated with anti-obesity. Conclusion: These results validate the use of Solanum nigrum in controlling obesity.

Keywords: solanum nigrum, High fat diet, phytocompounds, obesity

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Authors: K. Shahril, A. Nizam, M. Sabri, A. Siti Rohana, H. Salmah

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Chemical modifier (Acrylic Acid) is used as filler treatment to improve mechanical properties and swelling behavior of polypropylene/coconut fiber (PP/CF) composites by creating more adherent bonding between CF filler and PP Matrix. Treated (with chemical modifier) and untreated (without chemical modifier) composites were prepared in the formulation of 10 wt%, 20 wt%, 30 wt%, and 40 wt%. The mechanical testing indicates that composite with 10 wt% of untreated composite has the optimum value of tensile strength, and the composite with chemical modifier shows the tensile strength was increased. By increasing of filler loading, elastic modulus was increased while the elongation at brake was decreased. Meanwhile, the swelling test discerned that the increase of filler loading increased the water absorption of composites and the presence of chemical modifier reduced the equilibrium water absorption percentage.

Keywords: coconut fiber, polypropylene, acid acrylic, ethanol, chemical modifier, composites

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Authors: M. Naderi, N. Iyyer, K. Goel, N. Phan

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A micromechanical analysis of the influence of fiber-matrix interface fracture properties on the transverse tensile response of fiber-reinforced composite is investigated. Augmented finite element method (AFEM) is used to provide high-fidelity damage initiation and propagation along the micromechanical analysis. Effects of fiber volume fraction and fiber shapes are also studies in representative volume elements (RVE) to capture the stochastic behavior of the composite under loading. In addition, defects and voids influence on the composite response are investigated in micromechanical analysis. The results reveal that the response of RVE with constant interface properties overestimates the composite transverse strength. It is also seen that the damage initiation and propagation locations are controlled by the distributions of fracture properties, fibers’ shapes, and defects.

Keywords: cohesive model, fracture, computational mechanics, micromechanics

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Authors: S. Kudlacik-Kramarczyk, M. Kedzierska, B. Tyliszczak

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Recently, the continuous development of medicine and related sciences has been observed. Particular emphasis is directed on the development of biomaterials, i.e., non-toxic, biocompatible and biodegradable materials that may improve the effectiveness of treatment as well as the comfort of patients. This is particularly important in the case of cancer treatment. Currently, there are many methods of cancer treatment based primarily on chemotherapy and the surgical removal of the tumor, but it is worth noting that these therapies also cause many side effects. Among women, the most common cancer is breast cancer. It may be completely cured, but the consequence of treatment is partial or complete breast mastectomy and radiation therapy, which results in severe skin burns. The skin of the patient after radiation therapy is very burned, and therefore requires intensive care and high frequency of dressing changes. The traditional dressing adheres to the burn wounds and does not absorb adequate amount of exudate from injuries and the patient is forced to change the dressing every 2 hours. Therefore, the main purpose was to develop an innovative combination of dressing material with drug carriers that may be used in anti-cancer therapy. The innovation of this solution is the combination of these two products into one system, i.e., a transdermal system with the possibility of a controlled release of the drug- cytostatic. Besides, the possibility of modifying the hydrogel matrix with aloe vera juice provides this material with new features favorable from the point of view of healing processes of burn wounds resulting from the radiation therapy. In this study, hydrogel materials containing protein spheres with the active substance have been obtained as a result of photopolymerization process. The reaction mixture consisting of the protein (albumin) spheres incorporated with cytostatic, chitosan, adequate crosslinking agent and photoinitiator has been subjected to the UV radiation for 2 minutes. Prepared materials have been subjected to the numerous studies including the analysis of cytotoxicity using murine fibroblasts L929. Analysis was conducted based on the mitochondrial activity test (MTT reduction assay) which involves the determining the number of cells characterized by proper metabolism. Hydrogel materials obtained using different amount of crosslinking agents have been subjected to the cytotoxicity analysis. According to the standards, tested material is defined as cytotoxic when the viability of cells after 24 h incubation with this material is lower than 70%. In the research, hydrogel polymer materials containing protein spheres incorporated with the active substance, i.e. a cytostatic, have been developed. Such a dressing may support the treatment of cancer due to the content of the anti-cancer drug - cytostatic, and may also provide a soothing effect on the healing of the burn wounds resulted from the radiation therapy due to the content of aloe vera juice in the hydrogel matrix. Based on the conducted cytotoxicity studies, it may be concluded that the obtained materials do not adversely affect the tested cell lines, therefore they can be subjected to more advanced analyzes.

Keywords: hydrogel polymers, cytostatics, drug carriers, cytotoxicity

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Authors: S. Cichosz, A. Masek

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A new cellulose hybrid modification approach, which is undoubtedly a scientific novelty, is introduced. The study reports the properties of cellulose (Arbocel UFC100 – Ultra Fine Cellulose) and characterizes cellulose filled polymer composites based on an ethylene-norbornene copolymer (TOPAS Elastomer E-140). Moreover, the approach of physicochemical two-stage cellulose treatment is introduced: solvent exchange (to ethanol or hexane) and further chemical modification with maleic anhydride (MA). Furthermore, the impact of the drying process on cellulose properties was investigated. Suitable measurements were carried out to characterize cellulose fibers: spectroscopic investigation (Fourier Transform Infrared Spektrofotometer-FTIR, Near InfraRed spectroscopy-NIR), thermal analysis (Differential scanning calorimetry, Thermal gravimetric analysis ) and Karl Fischer titration. It should be emphasized that for all UFC100 treatments carried out, a decrease in moisture content was evidenced. FT-IR reveals a drop in absorption band intensity at 3334 cm-1, the peak is associated with both –OH moieties and water. Similar results were obtained with Karl Fischer titration. Based on the results obtained, it may be claimed that the employment of ethanol contributes greatly to the lowering of cellulose water absorption ability (decrease of moisture content to approximately 1.65%). Additionally, regarding polymer composite properties, crucial data has been obtained from the mechanical and thermal analysis. The highest material performance was noted in the case of the composite sample that contained cellulose modified with MA after a solvent exchange with ethanol. This specimen exhibited sufficient tensile strength, which is almost the same as that of the neat polymer matrix – in the region of 40 MPa. Moreover, both the Payne effect and filler efficiency factor, calculated based on dynamic mechanical analysis (DMA), reveal the possibility of the filler having a reinforcing nature. What is also interesting is that, according to the Payne effect results, fibers dried before the further chemical modification are assumed to allow more regular filler structure development in the polymer matrix (Payne effect maximum at 1.60 MPa), compared with those not dried (Payne effect in the range 0.84-1.26 MPa). Furthermore, taking into consideration the data gathered from DSC and TGA, higher thermal stability is obtained in case of the materials filled with fibers that were dried before the carried out treatments (degradation activation energy in the region of 195 kJ/mol) in comparison with the polymer composite samples filled with unmodified cellulose (degradation activation energy of approximately 180 kJ/mol). To author’s best knowledge this work results in the introduction of a novel, new filler hybrid treatment approach. Moreover, valuable data regarding the properties of composites filled with cellulose fibers of various moisture contents have been provided. It should be emphasized that plant fiber-based polymer bio-materials described in this research might contribute significantly to polymer waste minimization because they are more readily degraded.

Keywords: cellulose fibers, solvent exchange, moisture content, ethylene-norbornene copolymer

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Authors: Paloma Mendes Saldanha

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Access to information is a prerequisite for democracy while also guiding the material construction of fundamental rights. The exercise of citizenship requires knowing, understanding, questioning, advocating for, and securing rights and responsibilities. In other words, it goes beyond mere active electoral participation and materializes through awareness and the struggle for rights and responsibilities in the various spaces occupied by the population in their daily lives. In times of hyper-cultural connectivity, active citizenship is shaped through ethical trust processes, most often established between humans and algorithms. Automated decisions, so prevalent in various everyday situations, such as purchase preference predictions, virtual voice assistants, reduction of accidents in autonomous vehicles, content removal, resume selection, etc., have already found their place as a normalized discourse that sometimes does not reveal or make clear what violations of fundamental rights may occur when algorithmic explainability is lacking. In other words, technological and market development promotes a normalization for the use of automated decisions while silencing possible restrictions and/or breaches of rights through a culturally modeled, unethical, and unexplained trust process, which hinders the possibility of the right to a healthy, transparent, and complete exercise of citizenship. In this context, the article aims to identify the violations caused by the absence of algorithmic explainability in the exercise of citizenship through the construction of an unethical and silent trust process between humans and algorithms in automated decisions. As a result, it is expected to find violations of constitutionally protected rights such as privacy, data protection, and transparency, as well as the stipulation of algorithmic explainability as a fundamental right in the exercise of Brazilian citizenship in the era of virtualization, facing a threefold foundation called trust: culture, rules, and systems. To do so, the author will use a bibliographic review in the legal and information technology fields, as well as the analysis of legal and official documents, including national documents such as the Brazilian Federal Constitution, as well as international guidelines and resolutions that address the topic in a specific and necessary manner for appropriate regulation based on a sustainable trust process for a hyperconnected world.

Keywords: artificial intelligence, ethics, citizenship, trust

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Authors: M. Fakharian, M. I. Khodakarami

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In this paper, a new trend for improvement in semi-analytical method based on scale boundaries in order to solve the 2D elastodynamic problems is provided. In this regard, only the boundaries of the problem domain discretization are by specific sub-parametric elements. Mapping functions are uses as a class of higher-order Lagrange polynomials, special shape functions, Gauss-Lobatto -Legendre numerical integration, and the integral form of the weighted residual method, the matrix is diagonal coefficients in the equations of elastodynamic issues. Differences between study conducted and prior research in this paper is in geometry production procedure of the interpolation function and integration of the different is selected. Validity and accuracy of the present method are fully demonstrated through two benchmark problems which are successfully modeled using a few numbers of DOFs. The numerical results agree very well with the analytical solutions and the results from other numerical methods.

Keywords: 2D elastodynamic problems, lagrange polynomials, G-L-Lquadrature, decoupled SBFEM

Procedia PDF Downloads 444