Search results for: (FrFT) fractional fourier transform

Authors: Shivani Singla, Om Prakash Pandey, Gopi Sharma

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Metallic nanoparticle doped glasses has lead to rapid development in the field of optics. Large third order non-linearity, ultrafast time response, and a wide range of resonant absorption frequencies make these metallic nanoparticles more important in comparison to their bulk material. All these properties are highly dependent upon the size, shape, and surrounding environment of the nanoparticles. In a quest to find a suitable material for optical applications, several efforts have been devoted to improve the properties of such glasses in the past. In the present study, bismuth borate glass doped with different size gold nanoparticles (AuNPs) has been prepared using the conventional melt-quench technique. Synthesized glasses are characterized by X-ray diffraction (XRD) and Fourier Transformation Infrared spectroscopy (FTIR) to observe the structural modification in the glassy matrix with the variation in the size of the AuNPs. Glasses remain purely amorphous in nature even after the addition of AuNPs, whereas FTIR proposes that the main structure contains BO₃ and BO₄ units. Field emission scanning electron microscopy (FESEM) confirms the existence and variation in the size of AuNPs. Differential thermal analysis (DTA) depicts that prepared glasses are thermally stable and are highly suitable for the fabrication of optical fibers. The nonlinear optical parameters (nonlinear absorption coefficient and nonlinear refractive index) are calculated out by using the Z-scan technique with a Ti: sapphire laser at 800 nm. It has been concluded that the size of the nanoparticles highly influences the structural thermal and optical properties system.

Keywords: bismuth borate glass, different size, gold nanoparticles, nonlinearity

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Authors: Rodrigo Buaiz Boabaid

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Tokenization of Blue Bonds is an emerging Green Finance tool that has the potential to scale Blue Carbon Projects to fight climate change. This innovative solution has a huge potential to democratize the green finance market and catalyze innovations in the climate change finance sector. Switzerland has emerged as a leader in the Green Finance space and is well-positioned to drive the adoption of Tokenization of Blue & Green Bonds. This unique approach has the potential to unlock new sources of capital and enable global investors to participate in the financing of sustainable blue carbon projects. By leveraging the power of blockchain technology, Tokenization of Blue Bonds can provide greater transparency, efficiency, and security in the investment process, while also reducing transaction costs. Investments are in line with the highest regulations and designed according to the stringent legal framework and compliance standards set by Switzerland. The potential benefits of Tokenization of Blue Bonds are significant and could transform the way that sustainable projects are financed. By unlocking new sources of capital, this approach has the potential to accelerate the deployment of Blue Carbon projects and create new opportunities for investors to participate in the fight against climate change.

Keywords: blue carbon, blue bonds, green finance, Tokenization, blockchain solutions

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Authors: Tae Ho Kim

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Using the center of gravity method, we intend to find the center of gravity of Eurasia and North America, focusing on the local population, and study economic development plans in Eurasia and North America. By analyzing the strengths and opportunities of an industrial location for each region, we find ways for the country to grow and develop. Through economic cooperation and support between countries, we want to reduce the cause of conflict and dispute through economic growth in countries or regions. Furthermore, we want to create conditions for peaceful and happy regions or countries. Eurasia and North America are rich in resources, have great growth potential in terms of global supply chains, and have a good position to develop further. By analyzing intimacy between countries using REM, a CRM method, we intend to transform it into a region where a hopeful future of peace and prosperity begins. The future can be transformed through positive thinking or love for humanity. Indicators of intimacy between countries or regions can also be created anew if they change how they view each other. The Earth we live on is facing great risks, such as climate change and war. In order to reduce this crisis and maintain peace and prosperity, we must cooperate with each other in new directions.

Keywords: supply chain economy, REM, Indicators of intimacy, peace and prosperity

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Authors: Filimonova Alexanra

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Inviscid incompressible fluid flows are considered. The object of the study is a vortex parquet – a structure consisting of distributed vortex spots of different directions, occupying the entire plane. The main attention is paid to the study of advection processes of passive particles in the corresponding velocity field. The dynamics of the vortex structures is considered in a rectangular region under the assumption that periodic boundary conditions are imposed on the stream function. Numerical algorithms are based on the solution of the initial-boundary value problem for nonstationary Euler equations in terms of vorticity and stream function. For this, the spectral-vortex meshless method is used. It is based on the approximation of the stream function by the Fourier series cut and the approximation of the vorticity field by the least-squares method from its values in marker particles. A vortex configuration, consisting of four vortex patches is investigated. Results of a numerical study of the dynamics and interaction of the structure are presented. The influence of the patch radius and the relative position of positively and negatively directed patches on the processes of interaction and mixing is studied. The obtained results correspond to the following possible scenarios: the initial configuration does not change over time; the initial configuration forms a new structure, which is maintained for longer times; the initial configuration returns to its initial state after a certain period of time. The processes of mass transfer of vorticity by liquid particles on a plane were calculated and analyzed. The results of a numerical analysis of the particles dynamics and trajectories on the entire plane and the field of local Lyapunov exponents are presented.

Keywords: ideal fluid, meshless methods, vortex structures in liquids, vortex parquet.

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Authors: Bienvenu Gael Fouda Mbanga

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This study reports a new approach of preparation of carbon nanoparticles coated cerium oxide nanorods (CNPs/CeONRs) nanocomposite and reusing the spent adsorbent of Cd2+- CNPs/CeONRs nanocomposite for latent fingerprint detection (LFP) after removing Cd2+ ions from aqueous solution. CNPs/CeONRs nanocomposite was prepared by using CNPs and CeONRs with adsorption processes. The prepared nanocomposite was then characterized by using UV-visible spectroscopy (UV-visible), Fourier transforms infrared spectroscopy (FTIR), X-ray diffraction pattern (XRD), scanning electron microscope (SEM), Transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDS), Zeta potential, X-ray photoelectron spectroscopy (XPS). The average size of the CNPs was 7.84nm. The synthesized CNPs/CeONRs nanocomposite has proven to be a good adsorbent for Cd2+ removal from water with optimum pH 8, dosage 0. 5 g / L. The results were best described by the Langmuir model, which indicated a linear fit (R2 = 0.8539-0.9969). The adsorption capacity of CNPs/CeONRs nanocomposite showed the best removal of Cd2+ ions with qm = (32.28-59.92 mg/g), when compared to previous reports. This adsorption followed pseudo-second order kinetics and intra particle diffusion processes. ∆G and ∆H values indicated spontaneity at high temperature (40oC) and the endothermic nature of the adsorption process. CNPs/CeONRs nanocomposite therefore showed potential as an effective adsorbent. Furthermore, the metal loaded on the adsorbent Cd2+- CNPs/CeONRs has proven to be sensitive and selective for LFP detection on various porous substrates. Hence Cd2+-CNPs/CeONRs nanocomposite can be reused as a good fingerprint labelling agent in LFP detection so as to avoid secondary environmental pollution by disposal of the spent adsorbent.

Keywords: Cd2+-CNPs/CeONRs nanocomposite, cadmium adsorption, isotherm, kinetics, thermodynamics, reusable for latent fingerprint detection

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Authors: Farzad Khajavi

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Studies about the interaction between active pharmaceutical ingredients (API) and excipients are so important in the pre-formulation stage of development of all dosage forms. Analytical techniques such as differential scanning calorimetry (DSC), Thermal gravimetry (TG), and Furrier transform infrared spectroscopy (FTIR) are commonly used tools for investigating regarding compatibility and incompatibility of APIs with excipients. Sometimes the interpretation of data obtained from these techniques is difficult because of severe overlapping of API spectrum with excipients in their mixtures. Principal component analysis (PCA) as a powerful factor analytical method is used in these situations to resolve data matrices acquired from these analytical techniques. Binary mixtures of API and interested excipients are considered and produced. Peaks of FTIR, DSC, or TG of pure API and excipient and their mixtures at different mole ratios will construct the rows of the data matrix. By applying PCA on the data matrix, the number of principal components (PCs) is determined so that it contains the total variance of the data matrix. By plotting PCs or factors obtained from the score of the matrix in two-dimensional spaces if the pure API and its mixture with the excipient at the high amount of API and the 1:1mixture form a separate cluster and the other cluster comprise of the pure excipient and its blend with the API at the high amount of excipient. This confirms the existence of compatibility between API and the interested excipient. Otherwise, the incompatibility will overcome a mixture of API and excipient.

Keywords: API, compatibility, DSC, TG, interactions

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Authors: Kewen Li

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Much attention has been paid to the application of low temperature thermal resources, especially for power generation in recent years. Most of the current commercialized thermal, including geothermal, power-generation technologies convert thermal energy to electric energy indirectly, that is, making mechanical work before producing electricity. Technology using thermoelectric generator (TEG), however, can directly transform thermal energy into electricity by using Seebeck effect. TEG technology has many advantages such as compactness, quietness, and reliability because there are no moving parts. One of the big disadvantages of TEGs is the low efficiency from thermal to electric energy. For this reason, we redesigned and modified our previous 1 KW (at a temperature difference of around 120 °C) TEG system. The efficiency of the system was improved significantly, about 20% greater. Laboratory experiments have been conducted to measure the output power, including both open and net power, at different conditions: different modes of connections between TEG modules, different mechanical structures, different temperature differences between hot and cold sides. The cost of the TEG power generator has been reduced further because of the increased efficiency and is lower than that of photovoltaics (PV) in terms of equivalent energy generated. The TEG apparatus has been pilot tested and the data will be presented. This kind of TEG power system can be applied in many thermal and geothermal sites with low temperature resources, including oil fields where fossil and geothermal energies are co-produced.

Keywords: TEG, direct power generation, efficiency, thermoelectric effect

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Authors: Thuan Nguyen

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In the present time, data to a data-driven knowledge-based economy is the same as oil to the industrial age hundreds of years ago. Data is everywhere in vast volumes! Big data analytics is expected to help firms not only efficiently improve performance but also completely transform how they should run their business. However, employing the emergent technology successfully is not easy, and assessing the roles of big data in improving firm performance is even much harder. There was a lack of studies that have examined the impacts of big data analytics on organizational performance. This study aimed to fill the gap. The present study suggested using firms’ intellectual capital as a proxy for big data in evaluating its impact on organizational performance. The present study employed the Value Added Intellectual Coefficient method to measure firm intellectual capital, via its three main components: human capital efficiency, structural capital efficiency, and capital employed efficiency, and then used the structural equation modeling technique to model the data and test the models. The financial fundamental and market data of 100 randomly selected publicly listed firms were collected. The results of the tests showed that only human capital efficiency had a significant positive impact on firm profitability, which highlighted the prominent human role in the impact of big data technology.

Keywords: big data, big data analytics, intellectual capital, organizational performance, value added intellectual coefficient

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Luis Rodrigo Valencia Perez, Francisco Flores Aguero, Gibran Aguilar Rangel

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Artificial Intelligence (AI) is rapidly transforming diverse sectors, and higher education in Latin America is no exception. This article explores the impact of AI on higher education institutions in the region, highlighting the imperative need for well-trained teachers in emerging technologies and a cultural shift towards the adoption and efficient use of these tools. AI offers significant opportunities to improve learning personalization, optimize administrative processes, and promote more inclusive and accessible education. However, the effectiveness of its implementation depends largely on the preparation and willingness of teachers to integrate these technologies into their pedagogical practices. Furthermore, it is essential that Latin American countries develop and implement public policies that encourage the adoption of AI in the education sector, thus ensuring that institutions can compete globally. Policies should focus on the continuous training of educators, investment in technological infrastructure, and the creation of regulatory frameworks that promote innovation and the ethical use of AI. Only through a comprehensive and collaborative approach will it be possible to fully harness the potential of AI to transform higher education in Latin America, thereby boosting the region's development and competitiveness on the global stage.

Keywords: artificial intelligence (AI), higher education, teacher training, public policies, latin america, global competitiveness

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Authors: Juan Carlos Quiñones

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Time has passed since the industrial design has put murder on a mass-production basis. The industrial design applies methods from different disciplines with a strategic approach, to place humans at the centers of the design process and to deliver solutions that are meaningful and desirable for users and for the market. This analysis summarizes some of the discussions that occurred in the 6th International Forum of Design as a Process, June 2016, Valencia. The aims of this conference were finding new linkages between systems and design interactions in order to define the social consequences. Through knowledge management we are able to transform the intangible aspect by using design as a transforming function capable of converting intangible knowledge into tangible solutions (i.e. products and services demanded by society). Industrial designers use knowledge consciously as a starting point for the ideation of the product. The handling of the intangible becomes more and more relevant over time as different methods emerge for knowledge extraction and subsequent organization. The different methodologies applied to the industrial design discipline and the evolution of the same discipline methods underpin the cultural and scientific background knowledge as a starting point of thought as a response to the needs; the whole thing coming through the instrument of creativity for the achievement of the proper and necessary balance between intuition and reason, design and science.

Keywords: creative process, creativity, industrial design, intangible

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Authors: Henok Asfaw Hailu, P. D. Rwelamila

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Creating a suitable environment for successful projects needs a rethink of the organisational design of the parent organisations. A Project-based organisation (PBO) is a unique organizational form suitable for implementing and managing business activities around projects. A construction firm is inherently a PBO as it executes most of its activities through projects. PBO design and development require an empirical foundation. This study aimed to fill this gap by developing a conceptual model to help transform Ethiopian construction firms (ECFs) into full-fledged PBOs by assimilating the required PBO characteristics. The study used an exploratory QUAL-quant research design approach. A thematic content analysis was performed to analyse the qualitative (Interviews) research data. Means, standard deviations, frequencies, percentages, one-way ANOVA, and Pearson correlation were used to analyse the quantitative data. A transformational conceptual model was proposed and illustrated that transformation needs to begin by assessing the environment, strategic documents, and PBO characteristics. Assimilating missing PBO characteristics into ECFs is vital to realise organisations’ transformation into full-fledged PBOs.

Keywords: project-based organization, organizational design, dimensions, construction firms

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Authors: Peter Akayuure, Michael Johnson Nabie

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Similar to many colonized nations in the world, one indelible mark left by colonial masters after Ghana’s independence in 1957 has been the fact that many contexts used to teach statistics and probability concepts are often alien and do not resonate with the social domain of our indigenous Ghanaian child. This has seriously limited the understanding, discoveries, and applications of mathematics for national developments. With the recent curriculum demands of making the Ghanaian child mathematically literate, this qualitative study involved video recordings and mathematical analysis of play sessions of an indigenous girl game called Ampe with the aim to demystify the concepts in probability theorem, which is applied in mathematics related fields of study. The mathematical analysis shows that the game of Ampe, which is widely played by school girls in Ghana, is suitable for learning concepts of the probability theorems. It was also revealed that as a girl game, the use of Ampe provides good lessons to educators, textbook writers, and teachers to rethink about the selection of mathematics tasks and learning contexts that are sensitive to gender. As we undertake to transform teacher education and student learning, the use of indigenous games should be critically revisited.

Keywords: Ampe, mathematical analysis, probability theorem, Ghanaian girl game

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Authors: Burak Bal

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Mechanical characterization tests might come with a remarkable cost of time and money for both companies and academics. The inquiry to transform laboratory experiments to the computational media is getting a trend; accordingly, the literature supplies many analytical ways to explain the mechanics of deformation. In our work, we focused on the crystal plasticity finite element modeling (CPFEM) analysis on various materials in various crystal structures to predict the stress-strain curve without tensile tests. For FEM analysis, which we used in this study was ABAQUS, a standard user-defined material subroutine (UMAT) was prepared. The geometry of a specimen was created via DREAM 3D software with the inputs of Euler angles taken by Electron Back-Scattered Diffraction (EBSD) technique as orientation, or misorientation angles. The synthetic crystal created with DREAM 3D is also meshed in a way the grains inside the crystal meshed separately, and the computer can realize interaction of inter, and intra grain structures. The mechanical deformation parameters obtained from the literature put into the Fortran based UMAT code to describe how material will response to the load applied from specific direction. The mechanical response of a synthetic crystal created with DREAM 3D agrees well with the material response in the literature.

Keywords: crystal plasticity finite element modeling, ABAQUS, Dream.3D, microstructure

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Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

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Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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Authors: Stephen McCarthy, Joanne Gray, Esther Carr, Gerard Danjoux, Paul Baker, Rhiannon Hackett

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Background: The Go Well Health (GWH) platform is a web-based programme that allows patients to access personalised care plans and resources, aimed at prehabilitation prior to surgery. The online digital platform delivers essential patient education and support for patients prior to undergoing total hip replacements (THR) and total knee replacements (TKR). This study evaluated the impact of an online digital platform (ODP) in terms of functional health outcomes, health related quality of life and hospital length of stay following surgery. Methods: A retrospective cohort study comparing a cohort of patients who used the online digital platform (ODP) to deliver patient education and support (PES) prior to undergoing THR and TKR surgery relative to a cohort of patients who did not access the ODP and received usual care. Routinely collected Patient Reported Outcome Measures (PROMs) data was obtained on 2,406 patients who underwent a knee replacement (n=1,160) or a hip replacement (n=1,246) between 2018 and 2019 in a single surgical centre in the United Kingdom. The Oxford Hip and Knee Score and the European Quality of Life Five-Dimensional tool (EQ5D-5L) was obtained both pre-and post-surgery (at 6 months) along with hospital LOS. Linear regression was used to compare the estimate the impact of GWH on both health outcomes and negative binomial regressions were used to impact on LOS. All analyses adjusted for age, sex, Charlson Comorbidity Score and either pre-operative Oxford Hip/Knee scores or pre-operative EQ-5D scores. Fractional polynomials were used to represent potential non-linear relationships between the factors included in the regression model. Findings: For patients who underwent a knee replacement, GWH had a statistically significant impact on Oxford Knee Scores and EQ5D-5L utility post-surgery (p=0.039 and p=0.002 respectively). GWH did not have a statistically significant impact on the hospital length of stay. For those patients who underwent a hip replacement, GWH had a statistically significant impact on Oxford Hip Scores and EQ5D-5L utility post (p=0.000 and p=0.009 respectively). GWH also had a statistically significant reduction in the hospital length of stay (p=0.000). Conclusion: Health Outcomes were higher for patients who used the GWH platform and underwent THR and TKR relative to those who received usual care prior to surgery. Patients who underwent a hip replacement and used GWH also had a reduced hospital LOS. These findings are important for health policy and or decision makers as they suggest that prehabilitation via an ODP can maximise health outcomes for patients following surgery whilst potentially making efficiency savings with reductions in LOS.

Keywords: digital prehabilitation, online digital platform, orthopaedics, surgery

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Authors: Lucas Kurth de Azambuja, Loise Silveira da Silva, Gean Vitor Salmoria, Darlan Dallacosta, Carlos Rodrigo de Mello Roesler

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This work provides a physicochemical and thermal characterization assessment of three different hyaluronic acid (HA)-based injections used for rejuvenation skin treatments. The three products analyzed are manufactured by the same manufacturer and commercialized for application on different skin levels. According to the manufacturer, all three HA-based injections are crosslinked and have a concentration of 23 mg/mL of HA, and 0.3% of lidocaine. Samples were characterized by Fourier-transformed infrared (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and scanning electron microscope (SEM) techniques. FTIR analysis resulted in a similar spectrum when comparing the different products. DSC analysis demonstrated that the fusion points differ in each product, with a higher fusion temperature observed in specimen A, which is used for subcutaneous applications, when compared with B and C, which are used for the middle dermis and deep dermis, respectively. TGA data demonstrated a considerable mass loss at 100°C, which means that the product has more than 50% of water in its composition. TGA analysis also showed that Specimen A had a lower mass loss at 100°C when compared to Specimen C. A mass loss of around 220°C was observed on all samples, characterizing the presence of hyaluronic acid. SEM images displayed a similar structure on all samples analyzed, with a thicker layer for Specimen A when compared with B and C. This series of analyses demonstrated that, as expected, the physicochemical and thermal properties of the products differ according to their application. Furthermore, to better characterize the crosslinking degree of each product and their mechanical properties, a set of different techniques should be applied in parallel to correlate the results and, thereby, relate injection application with material properties.

Keywords: hyaluronic acid, characterization, soft-tissue fillers, injectable gels

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Authors: Okafor E. Ijeoma, Isimi C. Yetunde, Okoh E. Judith, Kunle O. Olobayo, Emeje O. Martins

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Starch has gained interest as a renewable and environmentally compatible polymer due to the increase in its use. However, starch by itself could not be satisfactorily applied in industrial processes due to some inherent disadvantages such as its hydrophilic character, poor mechanical properties, its inability to withstand processing conditions such as extreme temperatures, diverse pH, high shear rate, freeze-thaw variation and dimensional stability. The range of physical properties of parent starch can be enlarged by chemical modification which invariably enhances their use in a number of applications found in industrial processes and food manufacture. In this study, Manihot esculentus starch was subjected to modification by oxidation. Fourier Transmittance Infra- Red (FTIR) and Raman spectroscopies were used to confirm the synthesis while Scanning Electron Microscopy (SEM) and X- Ray Diffraction (XRD) were used to characterize the new polymer. DPPH (2, 2-diphenyl-1-picryl-hydrazyl-hydrate) free radical assay was used to determine the antioxidant property of the oxidized starch. Our results show that the modification had no significant effect on the foaming capacity as well as on the emulsion capacity. Scanning electron microscopy revealed that oxidation did not alter the predominantly circular-shaped starch granules, while the X-ray pattern of both starch, native and modified were similar. FTIR results revealed a new band at 3007 and 3283cm-1. Differential scanning calorimetry returned two new endothermic peaks in the oxidized starch with an improved gelation capacity and increased enthalpy of gelatinization. The IC50 of oxidized starch was notably higher than that of the reference standard, ascorbic acid.

Keywords: antioxidant activity, DPPH, M. esculentus, oxidation, starch

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Authors: E. Gil, A. Zepeda, J. Rivera, C. Ben-Youssef, S. Rincón

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Water pollution has become one of the most serious environmental problems. Multiple methods have been proposed for the removal of Pb(II) from contaminated water. Among these, adsorption processes have shown to be more efficient, cheaper and easier to handle with respect to other treatment methods. However, research for adsorbents with high adsorption capacities is still necessary. For this purpose, we proposed in this work the study of metal-organic Framework [Co2(btec)(bipy)(DMF)2]n (MOF-Co) as adsorbent material of Pb (II) in aqueous media. MOF-Co was synthesized by a simple method. Firstly 4, 4’ dipyridyl, 1,2,4,5 benzenetetracarboxylic acid, cobalt (II) and nitrate hexahydrate were first mixed each one in N,N dimethylformamide (DMF) and then, mixed in a reactor altogether. The obtained solution was heated at 363 K in a muffle during 68 h to complete the synthesis. It was washed and dried, obtaining MOF-Co as the final product. MOF-Co was characterized before and after the adsorption process by Fourier transforms infrared spectra (FTIR) and X-ray photoelectron spectroscopy (XPS). The Pb(II) in aqueous media was detected by Absorption Atomic Spectroscopy (AA). In order to evaluate the adsorption process in the presence of Pb(II) in aqueous media, the experiments were realized in flask of 100 ml the work volume at 200 rpm, with different MOF-Co quantities (0.0125 and 0.025 g), pH (2-6), contact time (0.5-6 h) and temperature (298,308 and 318 K). The kinetic adsorption was represented by pseudo-second order model, which suggests that the adsorption took place through chemisorption or chemical adsorption. The best adsorption results were obtained at pH 5. Langmuir, Freundlich and BET equilibrium isotherms models were used to study the adsorption of Pb(II) with 0.0125 g of MOF-Co, in the presence of different concentration of Pb(II) (20-200 mg/L, 100 mL, pH 5) with 4 h of reaction. The correlation coefficients (R2) of the different models show that the Langmuir model is better than Freundlich and BET model with R2=0.97 and a maximum adsorption capacity of 833 mg/g. Therefore, the Langmuir model can be used to best describe the Pb(II) adsorption in monolayer behavior on the MOF-Co. This value is the highest when compared to other materials such as the graphene/activated carbon composite (217 mg/g), biomass fly ashes (96.8 mg/g), PVA/PAA gel (194.99 mg/g) and MOF with Ag12 nanoparticles (120 mg/g).

Keywords: adsorption, heavy metals, metal-organic frameworks, Pb(II)

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Authors: Krzysztof Malczewski

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PET is widely applied scanning procedure in medical imaging based research. It delivers measurements of functioning in distinct areas of the human brain while the patient is comfortable, conscious and alert. This article presents the new compression sensing based super-resolution algorithm for improving the image resolution in clinical Positron Emission Tomography (PET) scanners. The issue of motion artifacts is well known in Positron Emission Tomography (PET) studies as its side effect. The PET images are being acquired over a limited period of time. As the patients cannot hold breath during the PET data gathering, spatial blurring and motion artefacts are the usual result. These may lead to wrong diagnosis. It is shown that the presented approach improves PET spatial resolution in cases when Compressed Sensing (CS) sequences are used. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. The application of CS to PET has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the goal is to combine super-resolution image enhancement algorithm with CS framework to achieve high resolution PET output. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity.

Keywords: PET, super-resolution, image reconstruction, pattern recognition

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Authors: Abdulfatah A Raji

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This paper started with the definitions of literature, Arabic literature, transformation and went further to highlight the components of educational transformation. The general history of Arabic literature was discussed with focus on how it undergoes some transformations from pre-Islamic period through Quranic era, Abbasid literature to renaissance period in which the modernization of Arabic literature started in Egypt. It also traces the spread of Arabic literature in Nigeria from the pre-colonial era during the Kanuri rulers to Jihad of Usman Dan Fodio and the development of literature which manifested to the Teacher’s Colleges and Bayero University in Northern Nigeria. Also, the establishment of primary and post-primary schools by Muslim organizations in many cities and towns of the Western part of Nigeria. Literary criticism was also discussed in line with Arabic literature. Poetry work of eminent poets were cited to show its importance in line with educational transformation in Nigerian literature and lessons from the cited Arabic poetry works were also highlighted to include: motivation to behave well and to tolerate others, better spirits of interaction, love and co-existence among different sexes, religion etc. All these can help in developing a better educational transformation in Nigeria which can in turn help in how to conduct researches for national development. The paper recommended compulsory Arabic literature at all levels of the nations’ educational system as well as publication of Arabic books and journals to encourage peace in this era of conflicts and further transform Nigeria’s educational system for better.

Keywords: Arabic, literature, peace, development, Nigeria

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Authors: Logaiswari Indiran, Noraindah Abdullah Fahim, Zainab Khalifah, Rohaizat Baharun, Kamariah Ismail

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Innovation capability is believed to give an important impact on organization’s sustainability and high performance. For instance, innovation capability able to transform technology into a specific organization’s operation, managerial, and transaction which increase organizational performance and economic growth of a country. In fact, research on high level of various antecedents has also shown positive impact on innovation capability. However, there are lacking studies explored on various kinds of antecedents which relate innovation capability’s role as mediator in the relationship. Thus, the purpose of this study is to specifically exhibit the mediation role of innovation capability between variety of antecedents and with different outcomes of an organization across industries. This study reviewed previous literature that has identified 'innovation capability' as mediator between the period of 2010 – 2016 and carries out a literature-based analysis of the findings in each article. From our review, innovation capability has been seen as a key role to mediate the relationship between independent variable and dependent variable in various industry. As the role of innovation capability as mediator is significant, new researchers should focus on varieties of independent variables. The review of this study will be useful for practitioners and researchers to understand and apply innovation capability as mediator to increase organizational success and innovativeness.

Keywords: innovation capability, mediator, organization performance, antecedents

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Authors: Aiman Elragig, Hanan Dreiwi, Dung Ly, Idriss Elmabrook

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This paper highlights a new approach to look at online principle components analysis (OPCA). Given a data matrix X ∈ R,^m x n we characterise the online updates of its covariance as a matrix perturbation problem. Up to the principle components, it turns out that online updates of the batch PCA can be captured by symmetric matrix perturbation of the batch covariance matrix. We have shown that as n→ n0 >> 1, the batch covariance and its update become almost similar. Finally, utilize our new setup of online updates to find a bound on the angle distance of the principle components of X and its update.

Keywords: online data updates, covariance matrix, online principle component analysis, matrix perturbation

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Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

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Authors: Nneka Augustina Akwu, Yougasphree Naidoo

Abstract:

Molecular advancement in technology has created a means whereby the atoms and molecules (solid forms) of certain materials such as plants, can now be reduced to a range of 1-100 nanometres. Green synthesis of silver nanoparticles (AgNPs) was carried out at room temperature (RT) 25 ± 2°C and 80°C, using the metabolites in the aqueous extracts of the leaves and stem bark of Grewia lasiocarpa as reductants and stabilizing agents. The biosynthesized AgNPs were characterized by UV-Vis spectrophotometry, attenuated total reflectance - Fourier transforms infrared (ATR-FTIR) spectroscopy, nanoparticle tracking analysis (NTA), Energy Dispersive X-ray fluorescence scanning electron microscope (SEM-EDXRF) and high-resolution transmission electron microscopy (HRTEM). The AgNPs were biologically evaluated for antioxidant, antibacterial and cytotoxicity activities. The phytochemical and FTIR analyses revealed the presence of metabolites that act as reducing and capping agents, while the UV-Vis spectroscopy of the biosynthesized NPs showed absorption between 380-460 nm, confirming AgNP synthesis. The Zeta potential values were between -9.1 and -20.6 mV with a hydrodynamics diameter ranging from 38.3 to 46.7 nm. SEM and HRTEM analyses revealed that AgNPs were predominately spherical with an average particle size of 2- 31 nm for the leaves and 5-27 nm for the stem bark. The cytotoxicity IC50 values of the AgNPs against HeLa, Caco-2 and MCF-7 were >1 mg/mL. The AgNPs were sensitive to all strains of bacteria used, with methicillin-resistant Staphylococcus aureus (MRSA), Staphylococcus aureus (ATCC 25923) and Escherichia coli (ATCC 25922) being more sensitive to the AgNPs. Our findings propose that antibacterial and anticancer agents could be derived from these AgNPs of G. lasiocarpa, and warrant their further investigation.

Keywords: antioxidant, cytotoxicity, Grewia lasiocarpa, silver nanoparticles, Zeta potentials

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Authors: Hadjadj Abdechafik, Kious Mecheri, Ameur Aissa

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The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the Root Mean Square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an online monitoring system. Although we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal, this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored.

Keywords: flank wear, vibration, milling, signal processing, monitoring

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Authors: Eduarda Dutra De Souza, Gabriela Hammes, Marina Bouzon, Carlos M. Taboada Rodriguez

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The search for minimizing harmful impacts on the environment has become the focus of global society, affecting mainly how to manage organizations. Thus, companies have sought to transform their activities into environmentally friendly initiatives by applying green practices throughout their supply chains. In the logistics domain, the implementation of environmentally sound practices is still in its infancy in emerging countries such as Brazil. Given the need to reduce these environmental damages, this study aims to evaluate the performance of green logistics (GL) in the plastics industry sector in order to help to improve environmental performance within organizations and reduce the impact caused by their activities. The performance tool was based on theoretical research and the use of experts in the field. The Analytic Hierarchy Process (AHP) was used to prioritize green practices and assign weight to the indicators contained in the proposed tool. The tool also allows the co-production of a single indicator. The developed tool was applied in an industry of the plastic packaging sector. However, this tool may be applied in different industry sectors, and it is adaptable to different sizes of companies. Besides the contributions to the literature, this work also presents future paths of research in the field of green logistics.

Keywords: AHP, green logistics, green supply chain, performance evaluation

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

Abstract:

The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Iyad A. A. Abusahloub

Abstract:

This research aimed to measure the level of perception and application of Integrated Talent Management according to IBM standards, by the upper and middle categories in Palestinian government institutions in Gaza, using a descriptive-analytical method. Using a questionnaire based on the standards of the IBM Institute for Business Value, the researcher added a second section to measure the perception of integrated talent management, the sample was 248 managers. The SPSS package was used for statistical analysis. The results showed that government institutions in Gaza apply Integrated Talent Management according to IBM standards at a medium degree did not exceed 59.8%, there is weakness in the perception of integrated talent management at the level of 53.6%, and there is a strong correlation between (Integrated Talent Management) and (the perception of the integrated talent management) amounted to 92.9%, and 88.9% of the change in the perception of the integrated talent management is by (motivate and develop, deploy and manage, connect and enable, and transform and sustain) talents, and 11.1% is by other factors. Conclusion: This study concluded that the integrated talent management model presented by IBM with its six dimensions is an effective model to reach your awareness and understanding of talent management, especially that it must rely on at least four basic dimensions out of the six dimensions: 1- Stimulating and developing talent. 2- Organizing and managing talent. 3- Connecting with talent and empowering it. 4- Succession and sustainability of talent. Therefore, this study recommends the adoption of the integrated talent management model provided by IBM to any organization across the world, regardless of its specialization or size, to reach talent sustainability.

Keywords: HR, talent, talent management, IBM

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Authors: Narek Margaryan, Zhozef Panosyan

Abstract:

Due to their unique properties, carbon nanofilms have become the object of general attention and intensive research. In this case it plays a very important role to study surface properties of these films. It is also important to study processes of forming of this films, which is accompanied by a process of self-organization at the nano and micro levels. For more detailed investigation, we examined diamond-like carbon (DLC) layers deposited by chemical vapor deposition (CVD) method on Ge substrate and hydro-generated grapheme layers obtained on surface of colloidal solution using grouping method. In this report surface transformation of these CVD nanolayers is studied by atomic force microscopy (AFM) upon deposition time. Also, it can be successfully used to study surface properties of self-assembled grapheme layers. In turn, it is possible to sketch out their boundary line, which enables one to draw an idea of peculiarities of formation of these layers. Images obtained by AFM are investigated as a mathematical set of numbers and fractal and roughness analysis were done. Fractal dimension, Regne’s fractal coefficient, histogram, Fast Fourier transformation, etc. were obtained. The dependence of fractal parameters on the deposition duration for CVD films and on temperature of solution tribolayers was revealed. As an important surface parameter for our carbon films, surface energy was calculated as function of Regne’s fractal coefficient. Surface potential was also measured with Kelvin probe method using semi-contacting AFM. The dependence of surface potential on the deposition duration for CVD films and on temperature of solution for hydro-generated graphene was found as well. Results obtained by fractal analysis method was related with purly esperimental results for number of samples.

Keywords: nanostructured films, self-assembled grapheme, diamond-like carbon, surface potential, Kelvin probe method, fractal analysis

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