Search results for: molecular techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8397

Search results for: molecular techniques

7887 Succinonitrile Modified Polyacrylamide as a Quasi-Solid Electrolyte for an Organic Based Electrochromic Device

Authors: Benjamin Orimolade, Emily Draper

Abstract:

The interest in all solid electrochromic devices (ECD) is ongoing. This is because these devices offer realistic applications of electrochromic materials in products such as sensors, windows and energy storage devices. The use of quasi-solid (gel) electrolytes for the construction of these ECDs is attractive because of their ease of preparation, availability, low cost, improved electrochromic performance, good ionic conductivity and prevention of leakages in ECDs. Herein, we developed a gel electrolyte consisting of polyacrylamide modified with succinonitrile for an ECD containing leucine-modified naphthalene diimide (NDI-L) as electrochromic material. The amount of succinonitrile in the gel was optimized, and the structure, surface morphology, and ionic conductivity of the electrolytes were assessed using microscopic techniques and electrochemical methods. The ECD fabricated with the gel electrolyte displayed good electrochromic performance with a fast switching response of up to 10 s and outstanding stability. These results add significant insight into understanding the inter- and intra-molecular interaction in succinonitrile gel electrolytes and provide a typical practicable high-performance gel electrolyte material for solid electrochromic devices.

Keywords: electrochromic device, gel electrolytes, naphthalene diimide, succinonitrile

Procedia PDF Downloads 47
7886 Gradient Boosted Trees on Spark Platform for Supervised Learning in Health Care Big Data

Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

Abstract:

Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

Procedia PDF Downloads 230
7885 Analysis of Spamming Threats and Some Possible Solutions for Online Social Networking Sites (OSNS)

Authors: Dilip Singh Sisodia, Shrish Verma

Abstract:

Spamming is the most common issue seen nowadays in the Internet especially in Online Social Networking Sites (like Facebook, Twitter, and Google+ etc.). Spam messages keep wasting Internet bandwidth and the storage space of servers. On social network sites; spammers often disguise themselves by creating fake accounts and hijacking user’s accounts for personal gains. They behave like normal user and they continue to change their spamming strategy. To prevent this, most modern spam-filtering solutions are deployed on the receiver side; they are good at filtering spam for end users. In this paper we are presenting some spamming techniques their behaviour and possible solutions. We have analyzed how Spammers enters into online social networking sites (OSNSs) and how they target it and the techniques they use for it. The five discussed techniques of spamming techniques which are clickjacking, social engineered attacks, cross site scripting, URL shortening, and drive by download. We have used elgg framework for demonstration of some of spamming threats and respective implementation of solutions.

Keywords: online social networking sites, spam, attacks, internet, clickjacking / likejacking, drive-by-download, URL shortening, networking, socially engineered attacks, elgg framework

Procedia PDF Downloads 335
7884 Searching for Novel Scaffolds of Triazole Non-Nucleoside Inhibitors of HIV-1 Reverse Transcriptase

Authors: Tomasz Frączek, Agata Paneth, Rafał Kamiński, Agnieszka Krakowiak, Piotr Paneth

Abstract:

Azoles are a promising class of the new generation of HIV-1 nonnucleoside reverse transcriptase inhibitors (NNRTIs). From thousands of reported compounds, many possess the same basic structure of an aryl substituted azole ring linked by a thioglycolamide chain with another aromatic ring. To find novel extensions for this primary scaffold, we explored the 5-position substitution of triazole NNRTIs using molecular docking followed by synthesis of selected compounds. We discovered that heterocyclic substituents in 5-position of the triazole ring are detrimental to the inhibitory activity of compounds with 4-membered thioglycolamide linker. This substitution seems to be viable only for compounds with a shorter 2-membered linker such as in derivatives of 4‐benzyl‐3‐(benzyl-sulfanyl)‐5‐(thiophen‐2‐yl)‐4H‐1,2,4‐triazole reported earlier. A new scaffold of 2‐[(4‐benzyl‐5‐methyl‐4H‐1,2,4‐triazol‐3‐yl)sulfanyl]‐N‐phenylacetamide has been identified in this study.

Keywords: docking, molecular modeling, drug design, novel scaffolds

Procedia PDF Downloads 530
7883 Multidrug Therapies For HIV: Hybrid On-Off, Hysteresis On-Off Control and Simple STI

Authors: Magno Enrique Mendoza Meza

Abstract:

This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

Procedia PDF Downloads 387
7882 Contrast Enhancement of Masses in Mammograms Using Multiscale Morphology

Authors: Amit Kamra, V. K. Jain, Pragya

Abstract:

Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other state-of-the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.

Keywords: enhancement, mammography, multi-scale, mathematical morphology

Procedia PDF Downloads 409
7881 Allura Red, Sunset Yellow and Amaranth Azo Dyes for Corrosion Inhibition of Mild Steel in 0.5 H₂SO₄ Solutions

Authors: Ashish Kumar Singh, Preeti Tiwari, Shubham Srivastava, Rajiv Prakash, Herman Terryn, Gopal Ji

Abstract:

Corrosion inhibition potential of azo dyes namely Allura red (AR), Sunset Yellow (SY) and Amaranth (AN) have been investigated in 0.5 M H2SO4 solutions by electrochemical impedance spectroscopy (EIS), Tafel polarization curves, linear polarization curves, open circuit potential (ocp) curves, UV-Visible spectroscopy, Fourier Transform Infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) techniques. Amaranth dye is found to provide highest corrosion inhibition (90 %) against mild steel corrosion in sulfuric acid solutions among all the tested dyes; while SY and AR dye shows 80% and 78% corrosion inhibition efficiency respectively. The electrochemical measurements and surface morphology analysis reveal that molecular adsorption of dyes at metal acid interface is accountable for inhibition of mild steel corrosion in H2SO4 solutions. The adsorption behavior of dyes has been investigated by various isotherms models, which verifies that it is in accordance with Langmuir isotherm.

Keywords: mild steel, Azo dye, EIS, Langmuir isotherm

Procedia PDF Downloads 361
7880 Investigation of the Mechanism, Régio and Sterioselectivity Using the 1,3-Dipolar Cycloaddition Reaction of Fused 1h-Pyrrole-2,3-Diones with Nitrones: Molecular Electron Density Theory Study

Authors: Ameur Soukaina, Zeroual Abdellah, Mazoir Noureddine

Abstract:

Molecular Electron Density Theory (MEDT) elucidates the regioselectivity of the [4+2] cycloaddition reaction between 3-aroylpyrrolo[1,2-α]quinoxaline-1,2,4(5H)-trione and butyl vinyl ether Regioselectivity and stereoselectivity. The regioselectivity mechanisms of these reactions were investigated by evaluating potential energy surfaces calculated for cycloaddition processes and DFT density-based reactivity indices. These methods have been successfully applied to predict preferred regioisomers for different method alternatives. Reactions were monitored by performing transition state optimizations, calculations of intrinsic reaction coordinates, and activation energies. The observed regioselectivity was rationalized using DFT-based reactivity descriptors such as the Parr function. Solvent effects were also investigated in 1,4-dioxane solvent using a field model for self-consistent reactions. The results were compared with experimental data to find good agreement.

Keywords: cycloaddition, DFT, ELF, MEDT, parr, stereoselectivité

Procedia PDF Downloads 92
7879 Innovative Teaching Learning Techniques and Learning Difficulties of Adult Learners in Literacy Education Programmes in Calabar Metropolis, Cross River State, Nigeria

Authors: Simon Ibor Akpama

Abstract:

The study investigated the extent to which innovative teaching-learning techniques can influence and attenuate learning difficulties among adult learners participating in different literacy education programmes in Calabar Metropolis, Cross River State, Nigeria. A quasi-experimental design was adopted to collect data from a sample size of 150 participants of the programme. The sample was drawn using the simple random sampling method. As an experimental study, the 150 participants were divided into two equal groups –the first was the experimental group while the second was the control. A pre-test was administered to the two groups which were later exposed to a post-test after treatment. Two instruments were used for data collection. The first was the guide for the Literacy Learning Difficulties Inventory (LLDI). Three hypotheses were postulated and tested as .05 level of significance using Analysis of Covariance (ANOVA) test statistics. Results of the analysis firstly showed that the two groups (treatment and control) did not differ in the pre-test regarding their literacy learning difficulties. Secondly, the result showed that for each hypothesis, innovative teaching-learning techniques significantly influenced adult learners’ (participants) literacy learning difficulties. Based on these findings, the study recommends the use of innovative teaching-learning techniques in adult literacy education centres to mitigate the learning difficulties of adult learners in literacy education programmes in Calabar Metropolis.

Keywords: teaching, learning, techniques, innovative, difficulties, programme

Procedia PDF Downloads 114
7878 Performance Analysis of Shunt Active Power Filter for Various Reference Current Generation Techniques

Authors: Vishal V. Choudhari, Gaurao A. Dongre, S. P. Diwan

Abstract:

A number of reference current generation have been developed for analysis of shunt active power filter to mitigate the load compensation. Depending upon the type of load the technique has to be chosen. In this paper, six reference current generation techniques viz. instantaneous reactive power theory(IRP), Synchronous reference frame theory(SRF), Perfect harmonic cancellation(PHC), Unity power factor method(UPF), Self-tuning filter method(STF), Predictive filtering method(PFM) are compared for different operating conditions. The harmonics are introduced because of non-linear loads in the system. These harmonics are eliminated using above techniques. The results and performance of system simulated on MATLAB/Simulink platform. The system is experimentally implemented using DS1104 card of dSPACE system.

Keywords: SAPF, power quality, THD, IRP, SRF, dSPACE module DS1104

Procedia PDF Downloads 580
7877 Synthesis of Y2O3 Films by Spray Coating with Milled EDTA ・Y・H Complexes

Authors: Keiji Komatsu,Tetsuo Sekiya, Ayumu Toyama, Atsushi Nakamura, Ikumi Toda, Shigeo Ohshio, Hiroyuki Muramatsu, Hidetoshi Saitoh

Abstract:

Yttrium oxide (Y2O3) films have been successfully deposited with yttrium-ethylenediaminetetraacetic acid (EDTA・Y・H) complexes prepared by various milling techniques. The effects of the properties of the EDTA・Y・H complex on the properties of the deposited Y2O3 films have been analyzed. Seven different types of the raw EDTA・Y・H complexes were prepared by various commercial milling techniques such as ball milling, hammer milling, commercial milling, and mortar milling. The milled EDTA・Y・H complexes exhibited various particle sizes and distributions, depending on the milling method. Furthermore, we analyzed the crystal structure, morphology and elemental distribution profile of the metal oxide films deposited on stainless steel substrate with the milled EDTA・Y・H complexes. Depending on the milling technique, the flow properties of the raw powders differed. The X-ray diffraction pattern of all the samples revealed the formation of Y2O3 crystalline phase, irrespective of the milling technique. Of all the different milling techniques, the hammer milling technique is considered suitable for fabricating dense Y2O3 films.

Keywords: powder sizes and distributions, flame spray coating techniques, Yttrium oxide

Procedia PDF Downloads 382
7876 Robust Image Design Based Steganographic System

Authors: Sadiq J. Abou-Loukh, Hanan M. Habbi

Abstract:

This paper presents a steganography to hide the transmitted information without excite suspicious and also illustrates the level of secrecy that can be increased by using cryptography techniques. The proposed system has been implemented firstly by encrypted image file one time pad key and secondly encrypted message that hidden to perform encryption followed by image embedding. Then the new image file will be created from the original image by using four triangles operation, the new image is processed by one of two image processing techniques. The proposed two processing techniques are thresholding and differential predictive coding (DPC). Afterwards, encryption or decryption keys are generated by functional key generator. The generator key is used one time only. Encrypted text will be hidden in the places that are not used for image processing and key generation system has high embedding rate (0.1875 character/pixel) for true color image (24 bit depth).

Keywords: encryption, thresholding, differential predictive coding, four triangles operation

Procedia PDF Downloads 479
7875 Statistical Tools for SFRA Diagnosis in Power Transformers

Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

Abstract:

For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

Procedia PDF Downloads 687
7874 An Investigation of Direct and Indirect Geo-Referencing Techniques on the Accuracy of Points in Photogrammetry

Authors: F. Yildiz, S. Y. Oturanc

Abstract:

Advances technology in the field of photogrammetry replaces analog cameras with reflection on aircraft GPS/IMU system with a digital aerial camera. In this system, when determining the position of the camera with the GPS, camera rotations are also determined by the IMU systems. All around the world, digital aerial cameras have been used for the photogrammetry applications in the last ten years. In this way, in terms of the work done in photogrammetry it is possible to use time effectively, costs to be reduced to a minimum level, the opportunity to make fast and accurate. Geo-referencing techniques that are the cornerstone of the GPS / INS systems, photogrammetric triangulation of images required for balancing (interior and exterior orientation) brings flexibility to the process. Also geo-referencing process; needed in the application of photogrammetry targets to help to reduce the number of ground control points. In this study, the use of direct and indirect geo-referencing techniques on the accuracy of the points was investigated in the production of photogrammetric mapping.

Keywords: photogrammetry, GPS/IMU systems, geo-referecing, digital aerial camera

Procedia PDF Downloads 398
7873 Role of Estrogen Receptor-alpha in Mammary Carcinoma by Single Nucleotide Polymorphisms and Molecular Docking: An In-silico Analysis

Authors: Asif Bilal, Fouzia Tanvir, Sibtain Ahmad

Abstract:

Estrogen receptor alpha, also known as estrogen receptor-1, is highly involved in risk of mammary carcinoma. The objectives of this study were to identify non-synonymous SNPs of estrogen receptor and their association with breast cancer and to identify the chemotherapeutic responses of phytochemicals against it via in-silico study design. For this purpose, different online tools. to identify pathogenic SNPs the tools were SIFT, Polyphen, Polyphen-2, fuNTRp, SNAP2, for finding disease associated SNPs the tools SNP&GO, PhD-SNP, PredictSNP, MAPP, SNAP, MetaSNP, PANTHER, and to check protein stability Mu-Pro, I-Mutant, and CONSURF were used. Post-translational modifications (PTMs) were detected by Musitedeep, Protein secondary structure by SOPMA, protein to protein interaction by STRING, molecular docking by PyRx. Seven SNPs having rsIDs (rs760766066, rs779180038, rs956399300, rs773683317, rs397509428, rs755020320, and rs1131692059) showing mutations on I229T, R243C, Y246H, P336R, Q375H, R394S, and R394H, respectively found to be completely deleterious. The PTMs found were 96 times Glycosylation; 30 times Ubiquitination, a single time Acetylation; and no Hydroxylation and Phosphorylation were found. The protein secondary structure consisted of Alpha helix (Hh) is (28%), Extended strand (Ee) is (21%), Beta turn (Tt) is 7.89% and Random coil (Cc) is (44.11%). Protein-protein interaction analysis revealed that it has strong interaction with Myeloperoxidase, Xanthine dehydrogenase, carboxylesterase 1, Glutathione S-transferase Mu 1, and with estrogen receptors. For molecular docking we used Asiaticoside, Ilekudinuside, Robustoflavone, Irinoticane, Withanolides, and 9-amin0-5 as ligands that extract from phytochemicals and docked with this protein. We found that there was great interaction (from -8.6 to -9.7) of these ligands of phytochemicals at ESR1 wild and two mutants (I229T and R394S). It is concluded that these SNPs found in ESR1 are involved in breast cancer and given phytochemicals are highly helpful against breast cancer as chemotherapeutic agents. Further in vitro and in vivo analysis should be performed to conduct these interactions.

Keywords: breast cancer, ESR1, phytochemicals, molecular docking

Procedia PDF Downloads 59
7872 Molecular Diagnosis of Influenza Strains Was Carried Out on Patients of the Social Security Clinic in Karaj Using the RT-PCR Technique

Authors: A. Ferasat, S. Rostampour Yasouri

Abstract:

Seasonal flu is a highly contagious infection caused by influenza viruses. These viruses undergo genetic changes that result in new epidemics across the globe. Medical attention is crucial in severe cases, particularly for the elderly, frail, and those with chronic illnesses, as their immune systems are often weaker. The purpose of this study was to detect new subtypes of the influenza A virus rapidly using a specific RT-PCR method based on the HA gene (hemagglutinin). In the winter and spring of 2022_2023, 120 embryonated egg samples were cultured, suspected of seasonal influenza. RNA synthesis, followed by cDNA synthesis, was performed. Finally, the PCR technique was applied using a pair of specific primers designed based on the HA gene. The PCR product was identified after purification, and the nucleotide sequence of purified PCR products was compared with the sequences in the gene bank. The results showed a high similarity between the sequence of the positive samples isolated from the patients and the sequence of the new strains isolated in recent years. This RT-PCR technique is entirely specific in this study, enabling the detection and multiplication of influenza and its subspecies from clinical samples. The RT-PCR technique based on the HA gene, along with sequencing, is a fast, specific, and sensitive diagnostic method for those infected with influenza viruses and its new subtypes. Rapid molecular diagnosis of influenza is essential for suspected people to control and prevent the spread of the disease to others. It also prevents the occurrence of secondary (sometimes fatal) pneumonia that results from influenza and pathogenic bacteria. The critical role of rapid diagnosis of new strains of influenza is to prepare a drug vaccine against the latest viruses that did not exist in the community last year and are entirely new viruses.

Keywords: influenza, molecular diagnosis, patients, RT-PCR technique

Procedia PDF Downloads 55
7871 Multiple Negative-Differential Resistance Regions Based on AlN/GaN Resonant Tunneling Structures by the Vertical Growth of Molecular Beam Epitaxy

Authors: Yao Jiajia, Wu Guanlin, LIU Fang, Xue Junshuai, Zhang Jincheng, Hao Yue

Abstract:

Resonant tunneling diodes (RTDs) based on GaN have been extensively studied. However, no results of multiple logic states achieved by RTDs were reported by the methods of epitaxy in the GaN materials. In this paper, the multiple negative-differential resistance regions by combining two discrete double-barrier RTDs in series have been first demonstrated. Plasma-assisted molecular beam epitaxy (PA-MBE) was used to grow structures consisting of two vertical RTDs. The substrate was a GaN-on-sapphire template. Each resonant tunneling structure was composed of a double barrier of AlN and a single well of GaN with undoped 4-nm space layers of GaN on each side. The AlN barriers were 1.5 nm thick, and the GaN well was 2 nm thick. The resonant tunneling structures were separated from each other by 30-nm thick n+ GaN layers. The bottom and top layers of the structures, grown neighboring to the spacer layers that consist of 200-nm-thick n+ GaN. These devices with two tunneling structures exhibited uniform peaks and valleys current and also had two negative differential resistance NDR regions equally spaced in bias voltage. The current-voltage (I-V) characteristics of resonant tunneling structures with diameters of 1 and 2 μm were analyzed in this study. These structures exhibit three stable operating points, which are investigated in detail. This research demonstrates that using molecular beam epitaxy MBE to vertically grow multiple resonant tunneling structures is a promising method for achieving multiple negative differential resistance regions and stable logic states. These findings have significant implications for the development of digital circuits capable of multi-value logic, which can be achieved with a small number of devices.

Keywords: GaN, AlN, RTDs, MBE, logic state

Procedia PDF Downloads 79
7870 Underwater Remotely Operated Vehicle (ROV) Exploration

Authors: M. S. Sukumar

Abstract:

Our objective is to develop a full-fledged system for exploring and studying nature of fossils and to extend this to underwater archaeology and mineral mapping. This includes aerial surveying, imaging techniques, artefact extraction and spectrum analysing techniques. These techniques help in regular monitoring of fossils and also the sensing system. The ROV was designed to complete several tasks which simulate collecting data and samples. Given the time constraints, the ROV was engineered for efficiency and speed in performing tasks. Its other major design consideration was modularity, allowing the team to distribute the building process, to easily test systems as they were completed and troubleshoot and replace systems as necessary. Our design itself had several challenges of on-board waterproofed sensor mounting, waterproofing of motors, ROV stability criteria, camera mounting and hydrophone sound acquisition.

Keywords: remotely operated vehicle (ROV) dragonair, underwater archaeology, full-fledged system, aerial imaging and detection

Procedia PDF Downloads 228
7869 Ultradrawing and Ultimate Tensile Properties of Ultrahigh Molecular Weight Polyethylene Composite Fibers Filled with Activated Nanocarbon Particles with Varying Specific Surface Areas

Authors: Wang-Xi Fan, Yi Ding, Zhong-Dan Tu, Kuo-Shien Huang, Chao-Ming Huang, Jen-Taut Yeh

Abstract:

Original and/or functionalized activated nanocarbon particles with a quoted specific surface area of 100, 500, 1000 and 1400 m2/g, respectively, were used to investigate the influence of specific surface areas of activated nanocarbon on ultra drawing and ultimate tensile properties of ultrahigh molecular weight polyethylene (UHMWPE), UHMWPE/activated nanocarbon and UHMWPE/ functionalized activated nanocarbon fibers. The specific surface areas of well dispersed functionalized activated nanocarbon in UHMWPE/functionalized activated nanocarbon fibers can positively affect their ultra drawing, orientation, ultimate tensile properties and “micro-fibril” characteristics. Excellent orientation and ultimate tensile properties of UHMWPE/nanofiller fibers can be prepared by ultra drawing the UHMWPE/functionalized activated nanocarbon as-prepared fibers with optimal contents and compositions of functionalized activated nanocarbon. The ultimate tensile strength value of the best prepared UHMWPE/functionalized activated nanocarbon drawn fiber reached 8.0 GPa, which was about 2.86 times of that of the best-prepared UHMWPE drawn fiber prepared in this study. Specific surface area, morphological and Fourier transform infrared analyses of original and functionalized activated nanocarbon and/or investigations of thermal, orientation factor and ultimate tensile properties of as-prepared and/or drawn UHMWPE/functionalized activated nanocarbon fibers were performed to understand the above-improved ultra drawing and ultimate tensile properties of the UHMWPE/functionalized activated nanocarbon fibers.

Keywords: activated nanocarbon, specific surface areas, ultradrawing, ultrahigh molecular weight polyethylene

Procedia PDF Downloads 357
7868 Bioinformatic Approaches in Population Genetics and Phylogenetic Studies

Authors: Masoud Sheidai

Abstract:

Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

Procedia PDF Downloads 110
7867 Electrostatic and Dielectric Measurements for Hair Building Fibers from DC to Microwave Frequencies

Authors: K. Y. You, Y. L. Then

Abstract:

In the recent years, the hair building fiber has become popular, in other words, it is an effective method which helps people who suffer hair loss or sparse hair since the hair building fiber is capable to create a natural look of simulated hair rapidly. In the markets, there are a lot of hair fiber brands that have been designed to formulate an intense bond with hair strands and make the hair appear more voluminous instantly. However, those products have their own set of properties. Thus, in this report, some measurement techniques are proposed to identify those products. Up to five different brands of hair fiber are tested. The electrostatic and dielectric properties of the hair fibers are macroscopically tested using design DC and high-frequency microwave techniques. Besides, the hair fibers are microscopically analysis by magnifying the structures of the fiber using scanning electron microscope (SEM). From the SEM photos, the comparison of the uniformly shaped and broken rate of the hair fibers in the different bulk samples can be observed respectively.

Keywords: hair fiber, electrostatic, dielectric properties, broken rate, microwave techniques

Procedia PDF Downloads 304
7866 Inhibitory Effects of Ambrosia trifida L. on the Development of Root Hairs and Protein Patterns of Radicles

Authors: Ji-Hyon Kil, Kew-Cheol Shim, Kyoung-Ae Park, Kyoungho Kim

Abstract:

Ambrosia trifida L. is designated as invasive alien species by the Act on the Conservation and Use of Biodiversity by the Ministry of Environment, Korea. The purpose of present paper was to investigate the inhibitory effects of aqueous extracts of A.trifida on the development of root hairs of Triticum aestivum L., and Allium tuberosum Rottler ex Spreng and the electrophoretic protein patterns of their radicles. The development of root hairs was inhibited by increasing of aqueous extract concentrations. Through SDS-PAGE, the electrophoretic protein bands of extracted proteins from their radicles were appeared in controls, but protein bands of specific molecular weight disappeared or weakened in treatments. In conclusion, inhibitory effects of A. trifida made two receptor species changed morphologically, and at the molecular level in early growth stage.

Keywords: Ambrosia trifida L., invasive alien species, inhibitory effect, root hair, electrophoretic protein, radicle

Procedia PDF Downloads 348
7865 N₂O₂ Salphen-Like Ligand and Its Pd(II), Ag(I) and Cu(II) Complexes as Potentially Anticancer Agents: Design, Synthesis, Antimicrobial, CT-DNA Binding and Molecular Docking

Authors: Laila H. Abdel-Rahman, Mohamed Shaker S. Adam, Ahmed M. Abu-Dief, Hanan El-Sayed Ahmed

Abstract:

In this investigation, Cu(II), Pd(II) and Ag(I) complexes with the tetra-dentate DSPH Schiff base ligand were synthesized. The DSPH Schiff base and its complexes were characterized by using different physicochemical and spectral analysis. The results revealed that the metal ions coordinated with DSPH ligand through azomethine nitrogen and phenolic oxygen. Cu(II), Pd(II) and Ag(I) complexes are present in a 1:1 molar ratio. Pd(II) and Ag(I) complexes have square planar geometries while, Cu(II) has a distorted octahedral (Oh) geometry. All investigated complexes are nonelectrolytes. The investigated compounds were tested against different strains of bacteria and fungi. Both prepared compounds showed good results of inhibition against the selected pathogenic microorganism. Moreover, the interaction of investigated complexes with CT-DNA was studied via various techniques and the binding modes are mainly intercalative and grooving modes. Operating Environment MOE package was used to do docking studies for the investigated complexes to explore the potential binding mode and energy. Furthermore, the growth inhibitory effect of the investigated compounds was examined on some cancer cells lines.

Keywords: tetradentate, antimicrobial, CT-DNA interaction, docking, anticancer

Procedia PDF Downloads 232
7864 Comparison of Different Machine Learning Algorithms for Solubility Prediction

Authors: Muhammet Baldan, Emel Timuçin

Abstract:

Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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7863 Intrusion Detection Techniques in NaaS in the Cloud: A Review

Authors: Rashid Mahmood

Abstract:

The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

Procedia PDF Downloads 305
7862 CuIn₃Se₅ Colloidal Nanocrystals and Its Ink-Coated Films for Photovoltaics

Authors: M. Ghali, M. Elnimr, G. F. Ali, A. M. Eissa, H. Talaat

Abstract:

CuIn₃Se₅ material is indexed as ordered vacancy compounds having excellent matching properties with CuInGaSe (CIGS) solar absorber layer. For example, the valence band offset of CuIn₃Se₅ with CIGS is nearly 0.3 eV, and the lattice mismatch is less than 1%, besides the absence of discontinuity in their conduction bands. Thus, CuIn₃Se₅ can work as a passivation layer for repelling holes from CIGS/CdS interface and hence to reduce the interface carriers recombination and consequently enhancing the efficiency of CIGS/CdS solar cells. Theoretically, it was reported earlier that an improvement in the efficiency of p-CIGS-based solar cell with a thin ~100 nm of n-CuIn₃Se₅ layer is expected. Recently, a reported experiment demonstrated significant improvement in the efficiency of Molecular Beam Epitaxy (MBE) grown CIGS solar cells from 13.4 to 14.5% via inserting a thin layer of MBE-grown Cu(In,Ga)₃Se₅ layer at the CdS/CIGS interface. It should be mentioned that CuIn₃Se₅ material in either bulk or thin film form, are usually fabricated by high vacuum physical vapor deposition techniques (e.g., three-source co-evaporation, RF sputtering, flash evaporation, and molecular beam epitaxy). In addition, achieving photosensitive films of n-CuIn₃Se₅ material is important for new hybrid organic/inorganic structures, where inorganic photo-absorber layer, with n-type conductivity, can form n–p junction with organic p-type material (e.g., conductive polymers). A detailed study of the physical properties of CuIn₃Se₅ is still necessary for better understanding of device operation and further improvement of solar cells performance. Here, we report on the low-cost synthesis of CuIn₃Se₅ material in nano-scale size, with an average diameter ~10nm, using simple solution-based colloidal chemistry. In contrast to traditionally grown bulk tetragonal CuIn₃Se₅ crystals using high Vacuum-based technology, our colloidal CuIn₃Se₅ nanocrystals show cubic crystal structure with a shape of nanoparticles and band gap ~1.33 eV. Ink-coated thin films prepared from these nanocrystals colloids; display n-type character, 1.26 eV band gap and strong photo-responsive behavior with incident white light. This suggests the potential use of colloidal CuIn₃Se₅ as an active layer in all-solution-processed thin film solar cells.

Keywords: nanocrystals, CuInSe, thin film, optical properties

Procedia PDF Downloads 147
7861 Multivariate Analysis of Spectroscopic Data for Agriculture Applications

Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

Abstract:

In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest

Procedia PDF Downloads 179
7860 Use of Technology to Improve Students’ Attitude in Learning Mathematics of Non- Mathematics Undergraduate Students

Authors: Asia Majeed

Abstract:

The learning of mathematics in science, engineering and social science programs can be enhanced through practical problem-solving techniques. The instructors can design their lessons with some strategies to improve students’ educational needs and accomplishments in mathematics classrooms. The use of technology in class problem solving and application sessions can enhance deep understanding of mathematics among students. As mathematician, we believe in subject specific and content-driven teaching methods. Through technology the relationship between the physical problems and the mathematical models can be analyzed. This paper is about selective use of technology in mathematics classrooms and helpful to others mathematics instructors who wishes to improve their traditional teaching techniques to improve students’ attitude in learning mathematics. These techniques corpus can be used in teaching large mathematics classes in science, technology, engineering, and social science.

Keywords: attitude in learning mathematics, mathematics, non-mathematics undergraduate students, technology

Procedia PDF Downloads 202
7859 Application of Change Detection Techniques in Monitoring Environmental Phenomena: A Review

Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

Abstract:

Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

Procedia PDF Downloads 265
7858 Bioinformatics High Performance Computation and Big Data

Authors: Javed Mohammed

Abstract:

Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

Procedia PDF Downloads 356