Search results for: spectroscopy data analysis

Authors: Sujatha Edla

Abstract:

Introduction: New compounds and possible uses for the bioactive substances produced by freshwater cyanobacteria are constantly being discovered through research. Certain molecules are hazardous to the environment and human health, but others have potential applications in industry, biotechnology, and pharmaceuticals. These discoveries advance our knowledge of the varied functions these microbes perform in different ecosystems. Cyanobacterial silver nanoparticles (AgNPs) have special qualities and possible therapeutic advantages, which make them very promising for a range of medicinal uses. Aim: In our study; the attention was focused on the analysis and characterization of bioactive compounds extracted from freshwater cyanobacteria Planktothricoides raciorskii and its comparative study on Cyanobacteria-mediated silver nanoparticles synthesized by cell-free extract of Planktothricoides raciorskii. Material and Methods: A variety of bioactive secondary metabolites have been extracted, purified, and identified from cyanobacterial species using column chromatography, FTIR, and GC-MS/MS chromatography techniques and evaluated for antibacterial and cytotoxic studies, where the Cyanobacterial silver nanoparticles (CSNPs) were characterized by UV-Vis spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Fourier transform infrared (FTIR) analysis and were further tested for antibacterial and cytotoxic efficiency. Results: The synthesis of CSNPs was confirmed through visible color change and shift of peaks at 430–445 nm by UV-Vis spectroscopy. The size of CSNPs was between 22 and 34 nm and oval-shaped which were confirmed by SEM and TEM analyses. The FTIR spectra showed a new peak at the range of 3,400–3,460 cm−1 compared to the control, confirming the reduction of silver nitrate. The antibacterial activity of both crude bioactive compound extract and CSNPs showed remarkable activity with Zone of inhibition against E. coli with 9.5mm and 10.2mm, 13mm and 14.5mm against S. paratyphi, 9.2mm and 9.8mm zone of inhibition against K. pneumonia by both crude extract and CSNPs, respectively. The cytotoxicity as evaluated by extracts of Planktothricoides raciorskii against MCF7-Human Breast Adenocarcinoma cell line and HepG2- Human Hepatocellular Carcinoma cell line employing MTT assay gave IC50 value of 47.18ug/ml, 110.81ug/ml against MCF7cell line and HepG2 cell line, respectively. The cytotoxic evaluation of Planktothricoides raciorskii CSNPs against the MCF7cell line was 43.37 ug/ml and 20.88 ug/ml against the HepG2 cell line. Our ongoing research in this field aims to uncover the full therapeutic potential of cyanobacterial silver nanoparticles and address any associated challenges.

Keywords: cyanobacteria, silvernanoparticles, pharmaceuticals, bioactive compounds, cytotoxic

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Authors: G. Nyongombe, Guy L. Kabongo, B. M. Mothudi, M. S. Dhlamini

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A series of Transition Metals Oxides (TMOs) doped graphene were synthesized and successfully used as supercapacitor electrode materials. The as-synthesized materials exhibited exceptional electrochemical properties owing to the combined properties of its constituents; high surface area and good conductivity were achieved. Several analytical characterization techniques were employed to investigate the morphology, crystal structure atomic arrangement and elemental chemical state in the materials for which scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) were conducted, respectively. Moreover, the electrochemical properties of the as-synthesized materials were examined by performing cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS) measurements. Furthermore, the effect of doping concentration on the interlayer distance of the graphene materials and the charge transfer resistance are investigated and correlated to the exceptional current density which was multiplied by a factor of ~80 after TMOs doping in graphene. Finally, the resulting high capacitance obtained confirms the contribution of grapheme exceptional electronic conductivity and large surface area on the electrode materials. Such good-performing electrode materials are highly promising for supercapacitors and other energy storage devices.

Keywords: energy density, graphene, supercapacitors, TMOs

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Authors: Jan Karl, Ondrej Suchy, Eliska Fiserova, Milan Ruzicka

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The evolving electromobility and all the electronics also bring an increase of danger with used Li-batteries. Li-batteries have been used in many industries, and currently many types of the batteries are available. Batteries have different compositions that affect their behavior. In the field of Li-battery safety, there are some areas of little discussion, such as extinguishing of fires caused by Li-batteries as well as toxicity of gaseous compounds released from Li batteries, transport or storage. Technical Institute of Fire Protection, which is a part of Fire Brigades of the Czech Republic, is dealing with the safety of Li batteries. That is the reason why we are dealing with toxicity of gaseous compounds released under conditions of fire, mechanical damage, overcharging and other emergencies that may occur. This is necessary for protection of intervening of fire brigade units, people in the vicinity and other envirnomental consequences. In this work, different types of batteries (Li-ion, Li-Po, LTO, LFP) with different kind of damage were tested, and the toxicity and total amount of released gases were studied. These values were evaluated according to their environmental hazard. FTIR spectroscopy was used for the evaluation of toxicity. We used a FTIR gas cell for continuous measurement. The total amount of released gases was determined by collecting the total gas phase through the absorbers and then determining the toxicants absorbed into the solutions. Based on the obtained results, it is possible to determine the protective equipment necessary for the event of an emergency with a Li-battery, to define the environmental load and the immediate danger in an emergency.

Keywords: Li-battery, toxicity, gaseous toxic compounds, FTIR spectroscopy

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Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry

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Zirconium alloys are used as core components of nuclear reactors due to their high wear resistance, good corrosion properties, and good mechanical stability at high temperatures. Water flows inside the pressure tube through fuel claddings, which produces vibration of these core components and results in the wear of some components. Some components are subjected to the environment of coolant water containing LiOH which results in the corrosion of these components. The present work simulates some of these conditions to determine the failure mechanisms under these conditions and the effect of various parameters on them. Friction and wear experiments were performed varying the surrounding environment (room temperature, high temperature, and water submerged), duration, frequency, and displacement amplitude. Electrochemical corrosion experiments were performed by varying the concentration of LiOH in water. The worn and corroded surfaces were analyzed using scanning electron microscopy (SEM) to analyze the wear and corrosion mechanism and energy dispersive x-ray spectroscopy (EDS) and Raman spectroscopy to analyze the tribo-oxide layer formed during the wear and oxide layer formed during the corrosion. Wear increases with frequency and amplitude, and corrosion increases with LiOH concentration in water.

Keywords: zirconium alloys, wear, oxide layer, corrosion, EIS, linear polarization

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Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

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Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: multi-agent system, safety analysis, safety model, integration map

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Authors: C. Slim

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This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.

Keywords: Artificial Neural Networks (ANN), Support vector machine (SVM), Data Envelopment Analysis (DEA), Aggregations, indicators of performance

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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Authors: M. Jerold, V. Sivasubramanian

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This study reports the removal of Malachite Green (MG) from simulated wastewater by using marine macro algae Ulva lactuca. Batch biosorption experiments were carried out to determine the biosorption capacity. The biosorption capacity was found to be maximum at pH 10. The effect of various other operation parameters such as biosorbent dosage, initial dye concentration, contact time and agitation was also investigated. The equilibrium attained at 120 min with 0.1 g/L of biosorbent. The isotherm experimental data fitted well with Langmuir Model with R² value of 0.994. The maximum Langmuir biosorption capacity was found to be 76.92 mg/g. Further, Langmuir separation factor RL value was found to be 0.004. Therefore, the adsorption is favorable. The biosorption kinetics of MG was found to follow pseudo second-order kinetic model. The mechanistic study revealed that the biosorption of malachite onto Ulva lactuca was controlled by film diffusion. The solute transfer in a solid-liquid adsorption process is characterized by the film diffusion and/or particle diffusion. Thermodynamic study shows ΔG° is negative indicates the feasibility and spontaneous nature for the biosorption of malachite green. The biosorbent was characterized using Scanning Electron Microscopy, Fourier Transform Infrared Spectroscopy, and elemental analysis (CHNS: Carbon, Hydrogen, Nitrogen, Sulphur). This study showed that Ulva lactuca can be used as promising biosorbent for the removal of MG from wastewater.

Keywords: biosorption, Ulva lactuca, wastewater, malachite green, isotherm, kinetics

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Authors: Bunthida Chunngam, Thanyanan Worasesthaphong

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This research had objective to develop of the website learning the local wisdom in Phra Nakhon Si Ayutthaya province and studied satisfaction of system user. This research sample was multistage sample for 100 questionnaires, analyzed data to calculated reliability value with Cronbach’s alpha coefficient method α=0.82. This system had 3 functions which were system using, system feather evaluation and system accuracy evaluation which the statistics used for data analysis was descriptive statistics to explain sample feature so these statistics were frequency, percentage, mean and standard deviation. This data analysis result found that the system using performance quality had good level satisfaction (4.44 mean), system feather function analysis had good level satisfaction (4.11 mean) and system accuracy had good level satisfaction (3.74 mean).

Keywords: website, learning, local wisdom, Phra Nakhon Si Ayutthaya province

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Authors: Sook Ching Yee, Angela Siew Hoong Lee

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Big data technologies have become a trend to exploit business opportunities and provide valuable business insights through the analysis of big data. However, there are still many organizations that have yet to adopt big data technologies especially small and medium organizations (SME). This study uses the technology acceptance model (TAM) to look into several constructs in the TAM and other additional constructs which are positive affect, negative affect, organizational factor and motivational factor. The conceptual model proposed in the study will be tested on the relationship and influence of positive affect, negative affect, organizational factor and motivational factor towards the intention to use big data technologies to produce an outcome. Empirical research is used in this study by conducting a survey to collect data.

Keywords: big data technologies, motivational factor, negative affect, organizational factor, positive affect, technology acceptance model (TAM)

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Tahira Imtiaz, Karim Ullah

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This paper aims to incorporate the banks employees’ perspective on acceptability of Islamic banking by the customers of Peshawar. A qualitative approach is adopted for which six in-depth interviews with employees of Islamic banks are conducted. The employees were asked to share their experience regarding customers’ acceptance attitude towards acceptability of Islamic banking. Collected data was analyzed through thematic analysis technique and its synthesis with the current literature. Through data analysis a theoretical framework is developed, which highlights the factors which drive customers towards Islamic banking, as witnessed by the employees. The practical implication of analyzed data evident that a new model could be developed on the basis of four determinants of human preference namely: inner satisfaction, time, faith and market forces.

Keywords: customers’ attraction, employees’ perspective, Islamic banking, Riba

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Authors: Muhammad Tariq, Muhammad Waseem, Muhammad Hidayat Rasool

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Isolation and characterization of chromium tolerant Staphylococcus aureus from industrial wastewater and their potential use to bioremediate environmental chromium. Objectives: Chromium with its great economic importance in industrial use is major metal pollutant of the environment. Chromium are used in different industries for various applications such as textile, dyeing and pigmentation, wood preservation, manufacturing pulp and paper, chrome plating, steel and tanning. The release of untreated chromium in industrial effluents causes serious threat to environment and human health, therefore, the current study designed to isolate chromium tolerant Staphylococcus aureus for removal of chromium prior to their final discharge into the environment due to its cost effective and beneficial advantage over physical and chemical methods. Methods: Wastewater samples were collected from discharge point of different industries. Heavy metal analysis by atomic absorption spectrophotometer and microbiological analysis such as total viable count, total coliform, fecal coliform and Escherichia coli were conducted. Staphylococcus aureus was identified through gram’s staining, biomeriux vitek 2 microbial identification system and 16S rRNA gene amplification by polymerase chain reaction. Optimum growth conditions with respect to temperature, pH, salt concentrations and effect of chromium on the growth of bacteria, resistance to other heavy metal ions, minimum inhibitory concentration and chromium uptake ability of Staphylococcus aureus strain K1 was determined by spectrophotometer. Antibiotic sensitivity pattern was also determined by disc diffusion method. Furthermore, chromium uptake ability was confirmed by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope equipped with Oxford Energy Dipersive X-ray (EDX) micro analysis system. Results: The results presented that optimum temperature was 35ᵒC, pH was 8.0 and salt concentration was 0.5% for growth of Staphylococcus aureus K1. The maximum uptake ability of chromium by bacteria was 20mM than other heavy metal ions. The antibiotic sensitivity pattern revealed that Staphylococcus aureus was vancomycin and methicillin sensitive. Non hemolytic activity on blood agar and negative coagulase reaction showed that it was non-pathogenic. Furthermore, the growth of bacteria decreases in the presence of chromium and maximum chromium uptake by bacteria observed at optimum growth conditions. Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM) and Energy dispersive X-ray (EDX) analysis confirmed the presence of chromium uptake by Staphylococcus aureus K1. Conclusion: The study revealed that Staphylococcus aureus K1 have the potential to bio-remediate chromium toxicity from wastewater. Gradually, this biological treatment becomes more important due to its advantage over physical and chemical methods to protect environment and human health.

Keywords: wastewater, staphylococcus, chromium, bioremediation

Procedia PDF Downloads 169

Authors: Rezzouq Asiya, Bouftou Abderrahim, Belfadil Doha, Taoufyk Azzeddine, El Bouchti Mehdi, Zyade Souad, Cherkaoui Omar, Majid Sanaa

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Plastic packaging is widely used, but its pollution is a major environmental problem. Solutions require new sustainable technologies, environmental management, and the use of bio-based polymers as sustainable packaging. Cellulose acetate (CA) is a biobased polymer used in a variety of applications such as the manufacture of plastic films, textiles, and filters. However, it has limitations in terms of thermal stability and rigidity, which necessitates the addition of plasticizers to optimize its use in packaging. Plasticizers are molecules that increase the flexibility of polymers, but their influence on the chemical and physical properties of films (CA) has not been studied in detail. Some studies have focused on mechanical and thermal properties. However, an in-depth analysis is needed to understand the interactions between the additives and the polymer matrix. In this study, the aim is to examine the effect of two types of plasticizers, glycerol (a conventional plasticizer) and an ionic liquid, on the transparency, mechanical, thermal and barrier properties of cellulose acetate (CA) films prepared by the solution-casting method . Various analytical techniques were used to characterize these films, including infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), water vapor permeability (WVP), oxygen permeability, scanning electron microscopy (SEM), opacity, transmission analysis and mechanical tests.

Keywords: cellulose acetate, plasticizers, biopolymers, ionic liquid, glycerol.

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Authors: E. Moroydor Derun, P. Gurses, M. Yildirim, A. S. Kipcak, T. Ibroska, S. Piskin

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Due to their strong mechanical and thermal properties magnesium borates have a wide usage area such as ceramic industry, detergent production, friction reducing additive and grease production. In this study, microwave synthesis of magnesium borates from MgCl2.6H2O (Magnesium chloride hexahydrate), MgO (Magnesium oxide) and H3BO3 (Boric acid) for different reaction times is researched. X-ray Diffraction (XRD) and Fourier Transform Infrared (FT-IR) Spectroscopy are used to find out how the reaction time sways on the products. The superficial properties are investigated with Scanning Electron Microscopy (SEM). According to XRD analysis, the synthesized compounds are 00-041-1407 pdf coded Shabinite (Mg5(BO3)4Cl2(OH)5.4(H2O)) and 01-073-2158 pdf coded Karlite (Mg7(BO3)3(OH,Cl)5).

Keywords: magnesium borate, microwave synthesis, XRD, SEM

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Authors: Mohammed Al-Khadher

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Currently, we are witnessing rapid advancements in the field of information and communications technology, forcing us, as psychologists, to combat the psychological and social effects of such developments. It also drives us to continually look for the development and preparation of measurement tools compatible with the changes brought about by the digital revolution. In this context, the current study aimed to identify the factor analysis of the Smartphone Addiction Inventory (SPAI) in the Republic of Yemen. The sample consisted of (1920) university students (1136 males and 784 females) who answered the inventory, and the data was analyzed using the statistical software (AMOS V25). The factor analysis results showed a goodness-of-fit of the data five-factor model with excellent indicators, as RMSEA-(.052), CFI-(.910), GFI-(.931), AGFI-(.915), TLI-(.897), NFI-(.895), RFI-(.880), and RMR-(.032). All within the ideal range to prove the model's fit of the scale’s factor analysis. The confirmatory factor analysis results showed factor loading in (4) items on (Time Spent), (4) items on (Compulsivity), (8) items on (Daily Life Interference), (5) items on (Craving), and (3) items on (Sleep interference); and all standard values of factor loading were statistically significant at the significance level (>.001).

Keywords: smartphone addiction inventory (SPAI), confirmatory factor analysis (CFA), yemeni students, people at risk of smartphone addiction

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Authors: Ellen Nhedzi Gozo

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Unavailability of adequate hydro-meteorological data has always limited the analysis and understanding of hydrological behaviour of several dam catchments including Mazowe Dam in Zimbabwe. The problem of insufficient data for Mazowe Dam catchment analysis was solved by extracting catchment characteristics and aerial hydro-meteorological data from ASTER, LANDSAT, Shuttle Radar Topographic Mission SRTM remote sensing (RS) images using ILWIS, ArcGIS and ERDAS Imagine geographic information systems (GIS) software. Available observed hydrological as well as meteorological data complemented the use of the remotely sensed information. Ground truth land cover was mapped using a Garmin Etrex global positioning system (GPS) system. This information was then used to validate land cover classification detail that was obtained from remote sensing images. A bathymetry survey was conducted using a SONAR system connected to GPS. Hydrological modelling using the HBV model was then performed to simulate the hydrological process of the catchment in an effort to verify the reliability of the derived parameters. The model output shows a high Nash-Sutcliffe Coefficient that is close to 1 indicating that the parameters derived from remote sensing and GIS can be applied with confidence in the analysis of Mazowe Dam catchment.

Keywords: geographic information systems, hydrological modelling, remote sensing, water resources management

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Authors: Sofia Sehli, Zainab El Ouafi, Casey Eddington, Soumaya Jbara, Kasambula Arthur Shem, Islam El Jaddaoui, Ayorinde Afolayan, Olaitan I. Awe, Allissa Dillman, Hassan Ghazal

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The ability to promptly sequence whole genomes at a relatively low cost has revolutionized the way we study the microbiome. Microbiologists are no longer limited to studying what can be grown in a laboratory and instead are given the opportunity to rapidly identify the makeup of microbial communities in a wide variety of environments. Analyzing whole genome sequencing (WGS) data is a complex process that involves multiple moving parts and might be rather unintuitive for scientists that don’t typically work with this type of data. Thus, to help lower the barrier for less-computationally inclined individuals, TAXAPRO was developed at the first Omics Codeathon held virtually by the African Society for Bioinformatics and Computational Biology (ASBCB) in June 2021. TAXAPRO is an advanced metagenomics pipeline that accurately assembles organelle genomes from whole-genome sequencing data. TAXAPRO seamlessly combines WGS analysis tools to create a pipeline that automatically processes raw WGS data and presents organism abundance information in both a tabular and graphical format. TAXAPRO was evaluated using COVID-19 patient gut microbiome data. Analysis performed by TAXAPRO demonstrated a high abundance of Clostridia and Bacteroidia genera and a low abundance of Proteobacteria genera relative to others in the gut microbiome of patients hospitalized with COVID-19, consistent with the original findings derived using a different analysis methodology. This provides crucial evidence that the TAXAPRO workflow dispenses reliable organism abundance information overnight without the hassle of performing the analysis manually.

Keywords: metagenomics, shotgun metagenomic sequence analysis, COVID-19, pipeline, bioinformatics

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Authors: Om Viroje

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Quantum machine learning represents a frontier in computational technology, promising significant advancements in data processing capabilities. This study explores the significance of data encoding techniques, specifically amplitude and phase encoding, in this emerging field. By employing a comparative analysis methodology, the research evaluates how these encoding techniques affect the accuracy, efficiency, and noise resilience of quantum algorithms. Our findings reveal that amplitude encoding enhances algorithmic accuracy and noise tolerance, whereas phase encoding significantly boosts computational efficiency. These insights are crucial for developing robust quantum frameworks that can be effectively applied in real-world scenarios. In conclusion, optimizing encoding strategies is essential for advancing quantum machine learning, potentially transforming various industries through improved data processing and analysis.

Keywords: quantum machine learning, data encoding, amplitude encoding, phase encoding, noise resilience

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Authors: Byungmin Cho, Dongchul Lee, Taejin Kim, Minhee Lee

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The procedure for the seismic retrofit of existing buildings includes the seismic evaluation. In the evaluation step, it is assessed whether the buildings have satisfactory performance against seismic load. Based on the results of that, the buildings are upgraded. To evaluate seismic performance of the buildings, it usually goes through the model transformation from elastic analysis to inelastic analysis. However, when the data is not delivered through the interwork, engineers should manually input the data. In this process, since it leads to inaccuracy and loss of information, the results of the analysis become less accurate. Therefore, in this study, the process for the seismic evaluation of existing buildings using structural information modeling is suggested. This structural information modeling makes the work economic and accurate. To this end, it is determined which part of the process could be computerized through the investigation of the process for the seismic evaluation based on ASCE 41. The structural information modeling process is developed to apply to the seismic evaluation using Perform 3D program usually used for the nonlinear response history analysis. To validate this process, the seismic performance of an existing building is investigated.

Keywords: existing building, nonlinear analysis, seismic performance, structural information modeling

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Authors: Ramona Zharfpeykan, Paul Rouse

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Organizational sustainability is important to both organizations themselves and their stakeholders. Despite its increasing popularity and increasing numbers of organizations reporting sustainability, research on evaluating and comparing the sustainability performance of companies is limited. The aim of this study was to develop models to measure sustainability performance for both cross-sectional and longitudinal comparisons across companies in the same or different industries. A secondary aim was to see if sustainability reports can be used to evaluate sustainability performance. The study used both a content analysis of Australian sustainability reports in mining and metals and financial services for 2011-2014 and a survey of Australian and New Zealand organizations. Two methods ranging from a composite index using uniform weights to data envelopment analysis (DEA) were employed to analyze the data and develop the models. The results show strong statistically significant relationships between the developed models, which suggests that each model provides a consistent, systematic and reasonably robust analysis. The results of the models show that for both industries, companies that had sustainability scores above or below the industry average stayed almost the same during the study period. These indices and models can be used by companies to evaluate their sustainability performance and compare it with previous years, or with other companies in the same or different industries. These methods can also be used by various stakeholders and sustainability ranking companies such as the Global Reporting Initiative (GRI).

Keywords: data envelopment analysis, sustainability, sustainability performance measurement system, sustainability performance index, global reporting initiative

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Authors: Somayeh Khanjani, Hamideh Abolghasemi, Hadi Shirzad, Samaneh Nabavi

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At world market can be currently encountered a wide range of gemological objects that are incorrectly declared, treated, or it concerns completely different materials that try to copy precious objects more or less successfully. Counterfeiting of precious commodities is a problem faced by governments in most countries. Police have seized many counterfeit coins that looked like the real coins and because the feeling to the touch and the weight were very similar to those of real coins. Most people were fooled and believed that the counterfeit coins were real ones. These counterfeit coins may have been made by big criminal organizations. To elucidate the manufacturing process, not only the quantitative analysis of the coins but also the comparison of their morphological characteristics was necessary. Several modern techniques have been applied to prevent counterfeiting of coins. The objective of this study was to demonstrate the potential of X-ray Fluorescence (XRF) technique and the other analytical techniques for example SEM/EDX/WDX, FT-IR/ATR and Raman Spectroscopy. Using four elements (Cu, Ag, Au and Zn) and obtaining XRF for several samples, they could be discriminated. XRF technique and SEM/EDX/WDX are used for study of chemical composition. XRF analyzers provide a fast, accurate, nondestructive method to test the purity and chemistry of all precious metals. XRF is a very promising technique for rapid and non destructive counterfeit coins identification in forensic science.

Keywords: counterfeit coins, X-ray fluorescence, forensic, FT-IR

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Authors: Anurag Kumar Pandey, Tapan Kumar Nath, Santanu Dhara

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Polluted water by industrial effluents or dyes has become a major global concern, particularly in developing countries. Such environmental contaminants constitute a serious threat to biodiversity, ecosystems, and human health worldwide; thus, their treatment is critical. The usage of nanoparticles has been discovered to be a potential water treatment method with high efficiency, cheap manufacturing costs, and green synthesis. Carbon dots have attracted the interest of researchers due to their unique properties, such as high water solubility, ease of production, great electron-donating ability, and low toxicity. In this context, we synthesized iodine-doped clove buds-derived carbon dots (I-CCDs) for the Fenton-like degradation of environmental contaminants in water (such as methylene blue (MB) and rhodamine-B (Rh-B) dye). The formation of I-CCDs has been confirmed using various spectroscopy techniques. I-CCDs have demonstrated remarkable optical, cytocompatibility, and antibacterial capabilities. The C-dots that were synthesized were found to be an effective catalyst for the reduction of MB and Rh-B utilizing NaBH4 as a reducing agent. UV-visible spectroscopy was used to construct a detailed pathway for dye reduction step by step. As-prepared I-CCDs have the potential to be a promising solution for wastewater purification and treatment systems.

Keywords: iodine-doped carbon dots, wastewater treatment and purification, environmental friendly, antibacterial

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

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Authors: Swarnadip Ghosh

Abstract:

Sentiment Analysis is the process of detecting the contextual polarity of text. In other words, it determines whether a piece of writing is positive, negative or neutral.Sentiment analysis of documents holds great importance in today's world, when numerous information is stored in databases and in the world wide web. An efficient algorithm to illicit such information, would be beneficial for social, economic as well as medical purposes. In this project, we have developed an algorithm to classify a document into positive or negative. Using our algorithm, we obtained a feature set from the data, and classified the documents based on this feature set. It is important to note that, in the classification, we have not used the independence assumption, which is considered by many procedures like the Naive Bayes. This makes the algorithm more general in scope. Moreover, because of the sparsity and high dimensionality of such data, we did not use empirical distribution for estimation, but developed a method by finding degree of close clustering of the data points. We have applied our algorithm on a movie review data set obtained from IMDb and obtained satisfactory results.

Keywords: sentiment, Run's Test, cross validation, higher dimensional pmf estimation

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Authors: María Magdalena Méndez-González, Miguel García Rocha, Carlos Manuel Yermo De la Cruz

Abstract:

Calcium phosphate (Ca5(PO4)3(X)) is widely used in orthopedic applications and is widely used as powder and granules. However, their presence in bone is in the form of nanometric needles 60 nm in length with a non-stoichiometric phase of apatite contains CO3-2, Na+, OH-, F-, and other ions in a matrix of collagen fibers. The crystal size, morphology control and interaction with cells are essential for the development of nanotechnology. The structural results of calcium phosphate, synthesized by chemical precipitation with crystal size of 22.85 nm are presented in this paper. The calcium phosphate powders were analyzed by X-ray diffraction, energy dispersive spectroscopy (EDS), infrared spectroscopy and FT-IR transmission electron microscopy. Network parameters, atomic positions, the indexing of the planes and the calculation of FWHM (full width at half maximum) were obtained. The crystal size was also calculated using the Scherer equation d (hkl) = cλ/βcosѲ. Where c is a constant related to the shape of the crystal, the wavelength of the radiation used for a copper anode is 1.54060Å, Ѳ is the Bragg diffraction angle, and β is the width average peak height of greater intensity. Diffraction pattern corresponding to the calcium phosphate called hydroxyapatite phase of a hexagonal crystal system was obtained. It belongs to the space group P63m with lattice parameters a = 9.4394 Å and c = 6.8861 Å. The most intense peak is obtained 2Ѳ = 31.55 (FWHM = 0.4798), with a preferred orientation in 121. The intensity difference between the experimental data and the calculated values is attributable to the temperature at which the sintering was performed. The intensity of the highest peak is at angle 2Ѳ = 32.11. The structure of calcium phosphate obtained was a hexagonal configuration. The intensity changes in the peaks of the diffraction pattern, in the lattice parameters at the corners, indicating the possible presence of a dopant. That each calcium atom is surrounded by a tetrahedron of oxygen and hydrogen was observed by infrared spectra. The unit cell pattern corresponds to hydroxyapatite and transmission electron microscopic crystal morphology corresponding to the hexagonal phase with a preferential growth along the c-plane was obtained.

Keywords: structure, nanoparticles, calcium phosphate, metallurgical and materials engineering

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Authors: Nathainail Bashir, Neil Anderson

Abstract:

The objective of this study site was to investigate the current state of the practice with regards to karst detection methods and recommend the best method and pattern of arrays to acquire the desire results. Proper site investigation in karst prone regions is extremely valuable in determining the location of possible voids. Two geophysical techniques were employed: multichannel analysis of surface waves (MASW) and electric resistivity tomography (ERT).The MASW data was acquired at each test location using different array lengths and different array orientations (to increase the probability of getting interpretable data in karst terrain). The ERT data were acquired using a dipole-dipole array consisting of 168 electrodes. The MASW data was interpreted (re: estimated depth to physical top of rock) and used to constrain and verify the interpretation of the ERT data. The ERT data indicates poorer quality MASW data were acquired in areas where there was significant local variation in the depth to top of rock.

Keywords: dipole-dipole, ERT, Karst terrains, MASW

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Authors: Fahad Hanash Alzahrani

Abstract:

This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Han-Qin Zheng, Yi-Fan Chiang-Hsieh, Chia-Hung Chien, Wen-Chi Chang

Abstract:

As the most important non-vascular plants, algae have many research applications, including high species diversity, biofuel sources, adsorption of heavy metals and, following processing, health supplements. With the increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes, an integrated resource for retrieving gene expression data and metabolic pathway is essential for functional analysis and systems biology in algae. However, gene expression profiles and biological pathways are displayed separately in current resources, and making it impossible to search current databases directly to identify the cellular response mechanisms. Therefore, this work develops a novel AlgaePath database to retrieve gene expression profiles efficiently under various conditions in numerous metabolic pathways. AlgaePath, a web-based database, integrates gene information, biological pathways, and next-generation sequencing (NGS) datasets in Chlamydomonasreinhardtii and Neodesmus sp. UTEX 2219-4. Users can identify gene expression profiles and pathway information by using five query pages (i.e. Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-Expression Analysis). The gene expression data of 45 and 4 samples can be obtained directly on pathway maps in C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively. Genes that are differentially expressed between two conditions can be identified in Folds Search. Furthermore, the Gene Group Analysis of AlgaePath includes pathway enrichment analysis, and can easily compare the gene expression profiles of functionally related genes in a map. Finally, Co-Expression Analysis provides co-expressed transcripts of a target gene. The analysis results provide a valuable reference for designing further experiments and elucidating critical mechanisms from high-throughput data. More than an effective interface to clarify the transcript response mechanisms in different metabolic pathways under various conditions, AlgaePath is also a data mining system to identify critical mechanisms based on high-throughput sequencing.

Keywords: next-generation sequencing (NGS), algae, transcriptome, metabolic pathway, co-expression

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Authors: Marwa A. A. Ragab, Amira F. El-Yazbi, Amr El-Hawiet

Abstract:

The analysis of heavy metals in honey samples is crucial. When found in honey, they denote environmental pollution. Some of these heavy metals as lead either present at low or high concentrations are considered to be toxic. Other heavy metals, for example, copper and zinc, if present at low concentrations, they considered safe even vital minerals. On the contrary, if they present at high concentrations, they are toxic. Their voltammetric determination in honey represents a challenge due to the presence of other electro-active components as vitamins, which may overlap with the peaks of the metal, hindering their accurate and precise determination. The simultaneous analysis of some vitamins: nicotinic acid (B3) and riboflavin (B2), and heavy metals: lead, cadmium, and zinc, in honey samples, was addressed. The analysis was done in 0.1 M Potassium Chloride (KCl) using a hanging mercury drop electrode (HMDE), followed by chemometric manipulation of the voltammetric data using the derivative method. Then the derivative data were convoluted using discrete Fourier functions. The proposed method allowed the simultaneous analysis of vitamins and metals though their varied responses and sensitivities. Although their peaks were overlapped, the proposed chemometric method allowed their accurate and precise analysis. After the chemometric treatment of the data, metals were successfully quantified at low levels in the presence of vitamins (1: 2000). The heavy metals limit of detection (LOD) values after the chemometric treatment of data decreased by more than 60% than those obtained from the direct voltammetric method. The method applicability was tested by analyzing the selected metals and vitamins in real honey samples obtained from different botanical origins.

Keywords: chemometrics, overlapped voltammetric peaks, derivative and convoluted derivative methods, metals and vitamins

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