Search results for: spectroscopy data analysis

Authors: Abbas Raza Ali

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Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

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Authors: Sudipto Shanker Dasgupta

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One of the largest mining companies wanted to look at health analytics for their driverless trucks. These trucks were the key to their supply chain logistics. The automated trucks had multi-level sub-assemblies which would send out sensor information. The use case that was worked on was to capture the sensor signal from the truck subcomponents and analyze the health of the trucks from repair and replacement purview. Open source software was used to stream the data into a clustered Hadoop setup in Amazon Web Services cloud and Apache Spark SQL was used to analyze the data. All of this was achieved through a 10 node amazon 32 core, 64 GB RAM setup real-time analytics was achieved on ‘300 million records’. To check the scalability of the system, the cluster was increased to 100 node setup. This talk will highlight how Open Source software was used to achieve the above use case and the insights on the high data throughput on a cloud set up.

Keywords: streaming analytics, data science, big data, Hadoop, high throughput, sensor data

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Authors: G. S. Sudha, Smita Mohanty, S. K. Nayak

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Epoxidized oils can replace petroleum derived materials in numerous industrial applications, because of their respectable oxirane oxygen content and high reactivity of oxirane ring. Epoxidized castor oil (ECO) has synthesized in the presence of a sulphonated polystyrene type cation exchange resin. The formation of the oxirane ring was confirmed by Fourier Transform Infrared Spectroscopy (FTIR) analysis. The epoxidation reaction was evaluated by Nuclear Magnetic Resonance (NMR) studies. ECO is used as a toughening phase to increase the toughness of petroleum-based epoxy resin.

Keywords: epoxy resin, epoxidized castor oil, sulphonated polystyrene type cation exchange resin, petroleum derived materials

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Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

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Authors: Jovana Bogojeski, Dusan Cocic, Nenad Jankovic, Angelina Petrovic

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Kinetically-inert transition metal complexes, such as Rh(III) and Os(III) complexes, attract increasing attention as leading scaffolds for the development of potential pharmacological agents due to their inertness and stability. Therefore, we have designed and fully characterized a few novel rhodium(III) and osmium(III) complexes with a tridentate nitrogen−donor chelate system. For some complexes, the crystal X-ray structure analysis was performed. Reactivity of the newly synthesized complexes towards small biomolecules, such as L-methionine (L-Met), guanosine-5’-monophosphate (5’-GMP), and glutathione (GSH) has been examined. Also, the reactivity of these complexes towards the DNA/RNA (Ribonucleic acid) duplexes was investigated. Obtained results show that the newly synthesized complexes exhibit good affinity towards the studied ligands. Results also show that the complexes react faster with the RNA duplex than with the DNA and that in the DNA duplex reaction is faster with 15mer GG than with the 22mer GG. The UV-Vis (Ultraviolet-visible spectroscopy) is absorption spectroscopy, and the EB (Ethidium bromide) displacement studies were used to examine the interaction of these complexes with CT-DNA and BSA (Bovine serum albumin). All studied complex showed good interaction ability with both the DNA and BSA. Furthermore, the DFT (Density-functional theory) calculation and docking studies were performed. The impact of the metal complex on the cytotoxicity was tested by MTT assay (a colorimetric assay for assessing cell metabolic activity) on HCT-116 lines (human colon cancer cell line). In addition, all these tests were repeated in the presence of several water-soluble biologically active ionic liquids. Attained results indicate that the ionic liquids increase the activity of the investigated complexes. All obtained results in this study imply that the introduction of different spectator ligand can be used to improve the reactivity of rhodium(III) and osmium(III) complexes. Finally, these results indicate that the examined complexes show reactivity characteristics needed for potential anti-tumor agents, with possible targets being both the DNA and proteins. Every new contribution in this field is highly warranted due to the current lack of clinically used Metallo-based alternatives to cisplatin.

Keywords: biomolecules, ionic liquids, osmium(III), rhodium(III)

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Authors: Takele Nemomsa, Girma Mamo, Tesfaye Balemi

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Climate change refers to a change in the state of the climate that can be identified (e.g. using statistical tests) by changes in the mean and/or variance of its properties and that persists for an extended period, typically decades or longer. In Ethiopia; Maize production in relation to climate change at regional and sub- regional scales have not been studied in detail. Thus, this study was aimed to analyse the impact of climate change on maize yield in Ambo Districts, Central Ethiopia. To this effect, weather data, soil data and maize experimental data for Arganne hybrid were used. APSIM software was used to investigate the response of maize (Zea mays) yield to different agronomic management practices using current and future (2020s–2080s) climate data. The climate change projections data which were downscaled using SDSM were used as input of climate data for the impact analysis. Compared to agronomic practices the impact of climate change on Arganne in Central Ethiopia is minute. However, within 2020s-2080s in Ambo area; the yield of Arganne hybrid is projected to reduce by 1.06% to 2.02%, and in 2050s it is projected to reduce by 1.56 While in 2080s; it is projected to increase by 1.03% to 2.07%. Thus, to adapt to the changing climate; farmers should consider increasing plant density and fertilizer rate per hectare.

Keywords: APSIM, downscaling, response, SDSM

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Authors: M. Goodarzi, M. Mohammadi, A. Gharib

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Solar energy is a renewable energy which has attracted special attention in many countries. Solar cathodic protectionsystems harness the sun’senergy to protect underground pipelinesand tanks from galvanic corrosion. The object of this study is to design and the economic analysis a cathodic protection system by impressed current supplied with solar energy panels applied to underground pipelines. In the present study, the technical and economic analysis of using solar energy for cathodic protection system in southwestern of Iran (Khuzestan province) is investigated. For this purpose, the ecological conditions such as the weather data, air clearness and sunshine hours are analyzed. The economic analyses were done using computer code to investigate the feasibility analysis from the using of various energy sources in order to cathodic protection system. The overall research methodology is divided into four components: Data collection, design of elements, techno economical evaluation, and output analysis. According to the results, solar renewable energy systems can supply adequate power for cathodic protection system purposes.

Keywords: renewable energy, solar energy, solar cathodic protection station, lifecycle cost method

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Authors: L. R. Shobin, S. Manivannan

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One dimensional silver nanowires and nanoparticles gained more interest in developing transparent conducting films, catalysis, biological and chemical sensors. Silver nanostructures can be synthesized by varying reaction conditions such as the precursor concentration, molar ratio of the surfactant, injection speed of silver ions, etc. in the polyol process. However, the reaction proceeds for greater than 2 hours for the formation of silver nanowires. The introduction of etchant in the medium promotes the growth of silver nanowires from silver nanoparticles along the [100] direction. Rapid growth of silver nanowires is accomplished using the Cl- ions from NaCl and polyvinyl pyrrolidone (PVP) as surfactant. The role of Cl- ion was investigated in the growth of the nanostructured silver. Silver nanoparticles (<100 nm) were harvested from glycerol medium in the absence of Cl- ions. Trace amount of Cl- ions (2.5 mM -NaCl) produced the edge joined nanowires of length upto 2 μm and width ranging from 40 to 65 nm. Formation and rapid growth (within 25 minutes) of long, uniform silver nanowires (upto 5 μm) with good yield were realized in the presence of 5 mM NaCl at 200ºC. The growth of nanostructures was monitored by UV-vis-NIR spectroscopy. Scanning and transmission electron microscopes reveal the morphology of the silver nano harvests. The role of temperature in the reduction of silver ions, growth mechanism for nanoparticles, edge joined and straight nanowires will be discussed.

Keywords: silver nanowires, glycerol mediated polyol process, scanning electron microscopy, UV-Vis- NIR spectroscopy, transmission electron microscopy

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Authors: Shadatul Hanom Rashid, Xiaorong Zhou

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Hybrid sol-gel coatings are the blend of both advantages of inorganic and organic networks have been reported as environmentally friendly anti-corrosion surface pre-treatment for several metals, including aluminum alloys. In this current study, Si-Zr hybrid sol-gel coatings were synthesized from (3-glycidoxypropyl)trimethoxysilane (GPTMS), tetraethyl orthosilicate (TEOS) and zirconium(IV) propoxide (TPOZ) precursors and applied on AA6111 aluminum alloy by dip coating technique. The hybrid sol-gel coatings doped with different concentrations of cerium nitrate (Ce(NO3)3) as a corrosion inhibitor were also prepared and the effect of Ce(NO3)3 concentrations on the morphology and corrosion resistance of the coatings were examined. The surface chemistry and morphology of the hybrid sol-gel coatings were analyzed by Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). The corrosion behavior of the coated aluminum alloy samples was evaluated by electrochemical impedance spectroscopy (EIS). Results revealed that good corrosion resistance of hybrid sol-gel coatings were prepared from hydrolysis and condensation reactions of GPTMS, TEOS and TPOZ precursors deposited on AA6111 aluminum alloy. When the coating doped with cerium nitrate, the properties were improved significantly. The hybrid sol-gel coatings containing lower concentration of cerium nitrate offer the best inhibition performance. A proper doping concentration of Ce(NO3)3 can effectively improve the corrosion resistance of the alloy, while an excessive concentration of Ce(NO3)3 would reduce the corrosion protection properties, which is associated with defective morphology and instability of the sol-gel coatings.

Keywords: AA6111, Ce(NO3)3, corrosion, hybrid sol-gel coatings

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Authors: M. Hoseinnezhad, K. Gharanjig

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Two organic dyes comprising carbazole as the electron donors and cyanoacetic acid moieties as the electron acceptors were synthesized. The organic dye was prepared by standard reaction from carbazole as the starting material. To this end, carbazole was reacted with bromobenzene and further oxidation and reacted with cyanoacetic acid. The obtained organic dye was purified and characterized using differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (¹HNMR), carbon nuclear magnetic resonance (¹³CNMR) and elemental analysis. The influence of heteroatom on carbazole donors and cyno substitution on the acid acceptor is evidenced by spectral and electrochemical photovoltaic experiments. Finally, light fastness properties for organic dye were investigated.

Keywords: dye-sensitized solar cells, indoline dye, nanostructure, oxidation potential, solar energy

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

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Authors: Ebrahim Mansoori, Datin Joriah Muhammad

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Recent studies in finance have focused on the effect of external variables on working capital management. This study investigates the effect of corruption indexes on firms' working capital management. A large data set that covers data from 2005 to 2013 from five ASEAN countries, namely, Malaysia, Indonesia, Singapore, Thailand, and the Philippines, was selected to investigate how the level of corruption in these countries affect working capital management. The results of panel data analysis include fixed effect estimations showed that a high level of countries' corruption indexes encourages managers to shorten the CCC length. Meanwhile, the managers reduce the level of investment in cash and cash equivalents when the levels of corruption indexes increase. Therefore, increasing the level of countries' corruption indexes encourages managers to select conservative working capital strategies by reducing the level of NLB.

Keywords: ASEAN, corruption indexes, panel data analysis, working capital management

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Authors: L. Parisi

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Kinematic data wisely correlate vector quantities in space to scalar parameters in time to assess the degree of symmetry between the intact limb and the amputated limb with respect to a normal model derived from the gait of control group participants. Furthermore, these particular data allow a doctor to preliminarily evaluate the usefulness of a certain rehabilitation therapy. Kinetic curves allow the analysis of ground reaction forces (GRFs) to assess the appropriateness of human motion. Electromyography (EMG) allows the analysis of the fundamental lower limb force contributions to quantify the level of gait asymmetry. However, the use of this technological tool is expensive and requires patient’s hospitalization. This research work suggests overcoming the above limitations by applying artificial neural networks.

Keywords: kinetics, kinematics, cyclograms, neural networks, transtibial amputation

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: M. Al Huwayz, A. Salhi, S. Alhassan, S. Alotaibi, A. Almalki, M.Almunyif, A. Alhassni, M. Henini

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Recently, there has been much research carried out to investigate quantum dots (QDs) lasers with the aim to increase the gain of quantum well lasers. However, one of the difficulties with these structures is that electrically active defects can lead to serious issues in the performance of these devices. It is therefore essential to fully understand the types of defects introduced during the growth and/or the fabrication process. In this study, the effects of Gamma radiation on the electrically active defects in p-i-n InAs/InGaAsQDs laser structures grown by Molecular Beam Epitaxy (MBE) technique on GaAs substrates were investigated. Deep Level Transient Spectroscopy (DLTS), current-voltage (I-V), and capacitance-voltage (C-V) measurements were performed to explore these effects on the electrical properties of these QDs lasers. I-V measurements showed that as-grown sample had better electrical properties than the irradiated sample. However, DLTS and Laplace DLTS measurements at different reverse biases revealed that the defects in the-region of the p-i-n structures were decreased in the irradiated sample. In both samples, a trap with an activation energy of ~ 0.21 eV was assigned to the well-known defect M1 in GaAs layers

Keywords: quantum dots laser structures, gamma radiation, DLTS, defects, nAs/IngaAs

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Authors: K. P. Ganesh, T. Gomathi, L. Arul Pragasan

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Degradation of lake water quality is one of the serious environmental threats for the last few decades, particularly, the lakes situated in and around urban and industrial areas. The present study aimed to analyze the physicochemical and biological parameters, and metal elements to determine the water quality of Krishnampathi, Ukkadam, Kurichi, Sulur and Singanallur Lakes. Of the 23 physicochemical parameters analyzed in the five lakes, except TDS, Chloride and Total hardness values all the 20 parameters were found within the prescribed limit as recommended by World Health Organization (WHO) and Bureau of Indian Standards (BIS). In case of biological parameter, both Total Coliform and Fecal Coliform bacteria (Escherichia coli) were identified. This indicates the contamination of lakes by fecal matter, and warns of potential of disease causing by viruses, bacteria and other organisms. Among the twelve metal elements (Al, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Mo, Cd and Pb) determined by inductively coupled plasma-mass spectroscopy, except Cd (for all lakes), and Pb (for Ukkadam, Kurichi, Sulur & Singanallur), all the elements were found above the prescribed limits of BIS. The results of the present study revealed that all the five major lakes of Coimbatore were contaminated. It is recommended that proper implementation of the new wetland waste management system and monitoring of water quality be of the urgent need to sustain the water bodies for future generations.

Keywords: heavy metals, inductively coupled plasma-mass spectroscopy, physicochemical and biological parameters, water quality

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Authors: Debadi Chakraborty, John E. Sader

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Nanomechanical devices have emerged as a versatile platform for a host of applications due to their extreme sensitivity to environmental conditions. For example, mass measurements with sensitivity at the atomic level have recently been demonstrated. Ultrafast laser spectroscopy coherently excite the vibrational modes of metal nanoparticles and permits precise measurement of the vibration characteristics as a function of nanoparticle shape, size and surrounding environment. This study reports that the vibration of metal nanoparticles in simple liquids, like water and glycerol are not described by conventional fluid mechanics, i.e., Navier Stokes equations. The intrinsic molecular relaxation processes in the surrounding liquid are found to have a profound effect on the fluid-structure interaction of mechanical devices at nanometre scales. Theoretical models have been developed based on the non-Newtonian viscoelastic fluid-structure interaction theory to investigate the vibration of nanoparticles immersed in simple fluids. The utility of this theoretical framework is demonstrated by comparison to measurements on single nanowires and ensembles of metal rods. This study provides a rigorous foundation for the use of metal nanoparticles as ultrasensitive mechanical sensors in fluid and opens a new paradigm for understanding extremely high frequency fluid mechanics, nanoscale sensing technologies, and biophysical processes.

Keywords: fluid-structure interaction, nanoparticle vibration, ultrafast laser spectroscopy, viscoelastic damping

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Authors: C. Copilusi, C. Ploscaru

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This paper addresses attention to a research regarding the design of a knee orthosis in a modular form used on children walking rehabilitation. This research is focused on the human lower limb kinematic analysis which will be used as input data on virtual simulations and prototype validation. From this analysis, important data will be obtained and used as input for virtual simulations of the knee modular orthosis. Thus, a knee orthosis concept was obtained and validated through virtual simulations by using MSC Adams software. Based on the obtained results, the modular orthosis prototype will be manufactured and presented in this article.

Keywords: human lower limb, children orthoses, kinematic analysis, knee orthosis

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Authors: Mochamad Nuruz Zaman, Mangatur Rudolf Nababan, M. A. Djatmika

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Both society and education areas teach to have good communication for building the interpersonal skills up. Everyone has the capacity to understand something new, either well comprehension or worst understanding. Worst understanding makes the language errors when the interactions are done by someone in the first meeting, and they do not know before it because of distance area. “The Space between Us” movie delivers the love-adventure story between Mars Boy and Earth Girl. They are so many missing conversations because of the different climate and environment. As the moviegoer also must be focused on the subtitle in order to enjoy well the movie. Furthermore, Indonesia subtitle and English conversation on the movie still have overlapping understanding in the translation. Translation hereby consists of source language -SL- (English conversation) and target language -TL- (Indonesia subtitle). These research gap above is formulated in research question by how the language errors happened in that movie and their effects on translation quality which is deepest analyzed by translation study toward discourse analysis approach. The research goal is to expand the language errors and their translation qualities in order to create a good atmosphere in movie media. The research is studied by embedded research in qualitative design. The research locations consist of setting, participant, and event as focused determined boundary. Sources of datum are “The Space between Us” movie and informant (translation quality rater). The sampling is criterion-based sampling (purposive sampling). Data collection techniques use content analysis and questioner. Data validation applies data source and method triangulation. Data analysis delivers domain, taxonomy, componential, and cultural theme analysis. Data findings on the language errors happened in the movie are referential, register, society, textual, receptive, expressive, individual, group, analogical, transfer, local, and global errors. Data discussions on their effects to translation quality are concentrated by translation techniques on their data findings; they are amplification, borrowing, description, discursive creation, established equivalent, generalization, literal, modulation, particularization, reduction, substitution, and transposition.

Keywords: discourse analysis, language errors, The Space between Us movie, translation techniques, translation quality instruments

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Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: Claudia Ehrentraut, Osama Ibrahim, Hercules Dalianis

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Policy making situations are real-world problems that exhibit complexity in that they are composed of many interrelated problems and issues. To be effective, policies must holistically address the complexity of the situation rather than propose solutions to single problems. Formulating and understanding the situation and its complex dynamics, therefore, is a key to finding holistic solutions. Analysis of text based information on the policy problem, using Natural Language Processing (NLP) and Text analysis techniques, can support modelling of public policy problem situations in a more objective way based on domain experts knowledge and scientific evidence. The objective behind this study is to support modelling of public policy problem situations, using text analysis of verbal descriptions of the problem. We propose a formal methodology for analysis of qualitative data from multiple information sources on a policy problem to construct a causal diagram of the problem. The analysis process aims at identifying key variables, linking them by cause-effect relationships and mapping that structure into a graphical representation that is adequate for designing action alternatives, i.e., policy options. This study describes the outline of an algorithm used to automate the initial step of a larger methodological approach, which is so far done manually. In this initial step, inferences about key variables and their interrelationships are extracted from textual data to support a better problem structuring. A small prototype for this step is also presented.

Keywords: public policy, problem structuring, qualitative analysis, natural language processing, algorithm, inference extraction

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Authors: Saleh Alotaibi, Mohammed Quddus, Craig Morton, Jobair Bin Alam

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This paper explores the role of large-scale investment in transport sectors and the impact of increased railway accessibility on the efficiency of the regional economic productivity in the Kingdom of Saudi Arabia (KSA). There are considerable differences among the KSA regions in terms of their levels of investment and productivity due to their geographical scale and location, which in turn greatly affect their relative efficiency. The study used a non-parametric linear programming technique - Data Envelopment Analysis (DEA) - to measure the regional efficiency change over time and determine the drivers of inefficiency and their scope of improvement. In addition, Window DEA analysis is carried out to compare the efficiency performance change for various time periods. Malmquist index (MI) is also analyzed to identify the sources of productivity change between two subsequent years. The analysis involves spatial and temporal panel data collected from 1999 to 2018 for the 13 regions of the country. Outcomes reveal that transport investment and improved railway accessibility, in general, have significantly contributed to regional economic development. Moreover, the endowment of the new railway stations has spill-over effects. The DEA Window analysis confirmed the dynamic improvement in the average regional efficiency over the study periods. MI showed that the technical efficiency change was the main source of regional productivity improvement. However, there is evidence of investment allocation discrepancy among regions which could limit the achievement of development goals in the long term. These relevant findings will assist the Saudi government in developing better strategic decisions for future transport investments and their allocation at the regional level.

Keywords: data envelopment analysis, transport investment, railway accessibility, efficiency

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Authors: Federica Laface, Cristina Pedà, Francesco Longo, Francesca de Domenico, Riccardo Minichino, Pierpaolo Consoli, Pietro Battaglia, Silvestro Greco, Teresa Romeo

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Plastics pollution represents one of the most important threats to marine biodiversity. In the last decades, different species are investigated to evaluate the extent of the plastic ingestion phenomenon. Even if the cephalopods play an important role in the food chain, they are still poorly studied. The aim of this research was to investigate the plastic ingestion in two commercial cephalopod species from the southern Tyrrhenian Sea: the common octopus, Octopus vulgaris (n=6; mean mantle length ML 10.7 ± 1.8) and the common cuttlefish, Sepia officinalis (n=13; mean ML 13.2 ± 1.7). Plastics were extracted from the filters obtained by the chemical digestion of cephalopods gastrointestinal tracts (GITs), using 10% potassium hydroxide (KOH) solution in a 1:5 (w/v) ratio. Once isolated, particles were photographed, measured, and their size class, shape and color were recorded. A total of 81 items was isolated from 16 of the 19 examined GITs, representing a total occurrence (%O) of 84.2% with a mean value of 4.3 ± 8.6 particles per individual. In particular, 62 plastics were found in 6 specimens of O. vulgaris (%O=100) and 19 particles in 10 S. officinalis (%O=94.7). In both species, the microplastics size class was the most abundant (93.8%). Plastic items found in O. vulgaris were mainly fibers (61%) while fragments were the most frequent in S. officinalis (53%). Transparent was the most common color in both species. The analysis will be completed by Fourier transform infrared (FT-IR) spectroscopy technique in order to identify polymers nature. This study reports preliminary data on plastic ingestion events in two cephalopods species and represents the first record of plastic ingestion by the common octopus. Microplastic items detected in both common octopus and common cuttlefish could derive from secondary and/or accidental ingestion events, probably due to their behavior, feeding habits and anatomical features. Further studies will be required to assess the effect of marine litter pollution in these ecologically and commercially important species.

Keywords: cephalopods, GIT analysis, marine pollution, Mediterranean sea, microplastics

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Authors: Elmineh Tsegahun Gedif

Abstract:

Zinc oxide nanoparticles (ZnO NPs) have attracted huge attention due to catalytic, optical, photonic, and antibacterial activity. Zinc oxide nanoparticles were successfully synthesized via a fast, non-toxic, cost-effective, and eco-friendly method by biologically reducing Zn(NO3)2.6H2O solution with Neem (Azadirachta indica) leaf extract under optimum conditions (pH = 9). The presence of active flavonoids, phenolic groups, alkaloids, terpenoids, and tannins, which were in the biomass of the Neem leaf extract before and after reduction, was identified using qualitative screening methods (observing the color changes) and FT-IR Spectroscopy. The formation of ZnO NPs was visually indicated by the color changes from colorless to light yellow color. Biosynthesized nanoparticles were also characterized by UV-visible, FT-IR, and XRD spectroscopies. The reduction process was simple and convenient to handle and was monitored by UV-visible spectroscopy that showed surface plasmon resonance (SPR) of the ZnO NPs at 321 nm. This result clearly revealed the formation of ZnO NPs. X-ray diffraction was used to investigate the crystal structure. The average particle size of ZnO powder and around 20 nm using the line width of the plane, and the refraction peak using Scherrer’s equation. The synthesized zinc oxide nanoparticles were evaluated for antimicrobial activities against Gram-positive and Gram-negative bacteria. Zinc nanoparticles exhibited the maximum zone of inhibition against Escherichia coli (15 mm), while the least activity was seen against Staphylococcus aureus.

Keywords: antimicrobial activity, azadirachta indica, green synthesis, ZnO NPs

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Authors: Rimzhim Gupta, Bhanupriya Boruah, Jayant M. Modak, Giridhar Madras

Abstract:

Microbial contamination is one of the major concerns in the field of water treatment. AOP (advanced oxidation processes) is well-established method to resolve the issue of removal of contaminants in water. A Z-scheme composite g-C₃N₄/CuWO₄ was synthesized by sol-gel method for the photocatalytic inactivation of a mixed population of Gram-positive bacteria (S. aureus) and Gram-negative bacteria (E. coli). The photoinactivation was observed for different types of bacteria in the same medium together and individually in the absence of the nutrients. The lattice structures and phase purities were determined by X-ray diffraction. For morphological and topographical features, scanning electron microscopy and transmission electron microscopy analyses were carried out. The band edges of the semiconductor (valence band and conduction band) were determined by ultraviolet photoelectron microscopy. The lifetime of the charge carriers and band gap of the semiconductors were determined by time resolved florescence spectroscopy and diffused reflectance spectroscopy, respectively. The effect of weight ratio of C₃N₄ and CuWO₄ was observed by performing photocatalytic experiments. To investigate the exact mechanism and major responsible radicals for photocatalysis, scavenger studies were performed. The rate constants and order of the inactivation reactions were obtained by power law kinetics. For E. coli and S. aureus, the order of reaction and rate constants are 1.15, 0.9 and 1.39 ± 0.03 (CFU/mL)⁻⁰.¹⁵ h⁻¹, 47.95 ± 1.2 (CFU/mL)⁰.¹ h⁻¹, respectively.

Keywords: z-scheme, E. coli, S. aureus, sol-gel

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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Authors: M. Bouhoun Ali, A. Y. Badjah Hadj Ahmed, M. Attou, A. Elias, M. A. Didi

Abstract:

The extraction of uranium(VI) from aqueous solutions has been investigated using 1-hydroxyhexadecylidene-1,1-diphosphonic acid (HHDPA) and 1-hydroxydodecylidene-1,1-diphosphonic acid (HDDPA), which were synthesized and characterized by elemental analysis and by FT-IR, 1H NMR, 31P NMR spectroscopy. In this paper, we propose a tentative assignment for the shifts of those two ligands and their specific complexes with uranium(VI). We carried out the extraction of uranium(VI) by HHDPA and HDDPA from [carbon tetrachloride + 2-octanol (v/v: 90%/10%)] solutions. Various factors such as contact time, pH, organic/aqueous phase ratio and extractant concentration were considered. The optimum conditions obtained were: contact time= 20 min, organic/aqueous phase ratio = 1, pH value = 3.0 and extractant concentration = 0.3M. The extraction yields are more significant in the case of the HHDPA which is equipped with a hydrocarbon chain, longer than that of the HDDPA. Logarithmic plots of the uranium(VI) distribution ratio vs. pHeq and the extractant concentration showed that the ratio of extractant to extracted uranium(VI) (ligand/metal) is 2:1. The formula of the complex of uranium(VI) with the HHDPA and the DHDPA is UO2(H3L)2 (HHDPA and DHDPA are denoted as H4L). A spectroscopic analysis has showed that coordination of uranium(VI) takes place via oxygen atoms.

Keywords: liquid-liquid extraction, uranium(vi), 1-hydroxyalkylidene-1, 1-diphosphonic acids, hhdpa, hddpa, aqueous solution

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Authors: Vijay Kumar Bajpai, Sudhir Kumar Singh

Abstract:

In this study, the performance analyses of the twenty five coal-fired power plants (CFPPs) used for electricity generation are carried out through various data envelopment analysis (DEA) models. Three efficiency indices are defined and pursued. During the calculation of the operational performance, energy and non-energy variables are used as input, and net electricity produced is used as desired output. CO2 emitted to the environment is used as the undesired output in the computation of the pure environmental performance while in Model-3 CO2 emissions is considered as detrimental input in the calculation of operational and environmental performance. Empirical results show that most of the plants are operating in increasing returns to scale region and Mettur plant is efficient one with regards to energy use and environment. The result also indicates that the undesirable output effect is insignificant in the research sample. The present study will provide clues to plant operators towards raising the operational and environmental performance of CFPPs.

Keywords: coal fired power plants, environmental performance, data envelopment analysis, operational performance

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Authors: Callistus I. Iheme, Kenneth E. Asika, Emmanuel I. Ugwor, Chukwuka U. Ogbonna, Ugonna H. Uzoka, Nneamaka A. Chiegboka, Chinwe S. Alisi, Obinna S. Nwabueze, Amanda U. Ezirim, Judeanthony N. Ogbulie

Abstract:

Antimicrobial resistance (AMR) is a major threat to the global health sector. Zinc oxide nanocomposites (ZnONCs), composed of zinc oxide nanoparticles and phytochemicals from Azadirachta indica aqueous leaf extract, were assessed for their physico-chemicals, in silico and in vitro antimicrobial properties on multidrug-resistant Escherichia coli enzymes. Gas chromatography coupled with mass spectroscope (GC-MS) analysis on the ZnONCs revealed the presence of twenty volatile phytochemical compounds, among which is scoparone. Characterization of the ZnONCs was done using ultraviolet-visible spectroscopy (UV-vis), energy dispersive spectroscopy (EDX), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and x-ray diffractometer (XRD). Dehydrogenase enzyme converts colorless 2,3,5-triphenyltetrazolium chloride to the red triphenyl formazan (TPF). The rate of formazan formation in the presence of ZnONCs is proportional to the enzyme activities. The color formation is extracted and determined at 500 nm, and the percentage of enzyme activity is calculated. To determine the bioactive components of the ZnONCs, characterize their binding to enzymes, and evaluate the enzyme-ligand complex stability, respectively Discrete Fourier Transform (DFT) analysis, docking, and molecular dynamics simulations will be employed. The results showed arrays of ZnONCs nanorods with maximal absorption wavelengths of 320 nm and 350 nm and thermally stable at the temperature range of 423.77 to 889.69 ℃. In vitro study assessed the dehydrogenase inhibitory properties of the ZnONCs, conjugate of ZnONCs and ampicillin (ZnONCs-amp), the aqueous leaf extract of A. indica, and ampicillin (standard drug). The findings revealed that at the concentration of 500 μm/mL, 57.89 % of the enzyme activities were inhibited by ZnONCs compared to 33.33% and 21.05% of the standard drug (Ampicillin), and the aqueous leaf extract of the A. indica respectively. The inhibition of the enzyme activities by the ZnONCs at 500 μm/mL was further enhanced to 89.74 % by conjugating with Ampicillin. In silico study on the ZnONCs revealed scoparone as the most viable competitor of nicotinamide adenine dinucleotide (NAD⁺) for the coenzyme binding pocket on E. coli malate and histidinol dehydrogenase. From the findings, it can be concluded that the scoparone components of the nanocomposites in synergy with the zinc oxide nanoparticles inhibited E. coli malate and histidinol dehydrogenase by competitively binding to the NAD⁺ pocket and that the conjugation of the ZnONCs with ampicillin further enhanced the antimicrobial efficiency of the nanocomposite against multidrug resistant E. coli.

Keywords: antimicrobial resistance, dehydrogenase activities, E. coli, zinc oxide nanocomposites

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