Search results for: molecular descriptors
2098 Machine Learning Assisted Prediction of Sintered Density of Binary W(MO) Alloys
Authors: Hexiong Liu
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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy
Procedia PDF Downloads 432097 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
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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 652096 Prediction of Anticancer Potential of Curcumin Nanoparticles by Means of Quasi-Qsar Analysis Using Monte Carlo Method
Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain
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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR
Procedia PDF Downloads 2782095 2D Fingerprint Performance for PubChem Chemical Database
Authors: Fatimah Zawani Abdullah, Shereena Mohd Arif, Nurul Malim
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The study of molecular similarity search in chemical database is increasingly widespread, especially in the area of drug discovery. Similarity search is an application in the field of Chemoinformatics to measure the similarity between the molecular structure which is known as the query and the structure of chemical compounds in the database. Similarity search is also one of the approaches in virtual screening which involves computational techniques and scoring the probabilities of activity. The main objective of this work is to determine the best fingerprint when compared to the other five fingerprints selected in this study using PubChem chemical dataset. This paper will discuss the similarity searching process conducted using 6 types of descriptors, which are ECFP4, ECFC4, FCFP4, FCFC4, SRECFC4 and SRFCFC4 on 15 activity classes of PubChem dataset using Tanimoto coefficient to calculate the similarity between the query structures and each of the database structure. The results suggest that ECFP4 performs the best to be used with Tanimoto coefficient in the PubChem dataset.Keywords: 2D fingerprints, Tanimoto, PubChem, similarity searching, chemoinformatics
Procedia PDF Downloads 2572094 Development of DNA Fingerprints in Selected Medicinal Plants of India
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Conventionally, morphological descriptors are routinely used for establishing the identity of varieties. But these morphological descriptors suffer from many drawbacks such as influence of environment on trait expression, epistatic interactions, pleiotrophic effects etc. Furthermore, the paucity of a sufficient number of these descriptors for unequivocal identification of increasing number of reference collection varieties enforces to look for alternatives. Therefore, DNA based finger-print based techniques were selected to define the systematic position of the selected medicinal plants like Plumbago zeylanica, Desmodium gangeticum, Uraria picta. DNA fingerprinting of herbal plants can be useful in authenticating the various claims of medical uses related to the plants, in germplasm characterization and conservation. In plants it has not only helped in identifying species but also in defining a new realm in plant genomics, plant breeding and in conserving the biodiversity. With world paving way for developments in biotechnology, DNA fingerprinting promises a very powerful tool in our future endeavors. Data will be presented on the development of microsatellite markers (SSR) used to fingerprint, characterize, and assess genetic diversity among 12 accessions of both Plumbago zeylanica, 4 accessions of Desmodium gengaticum, 4 accessions of Uraria Picta.Keywords: Plumbago zeylanica, Desmodium gangeticum, Uraria picta, microsaetllite markers
Procedia PDF Downloads 1872093 Exploring the Design of Prospective Human Immunodeficiency Virus Type 1 Reverse Transcriptase Inhibitors through a Comprehensive Approach of Quantitative Structure Activity Relationship Study, Molecular Docking, and Molecular Dynamics Simulations
Authors: Mouna Baassi, Mohamed Moussaoui, Sanchaita Rajkhowa, Hatim Soufi, Said Belaaouad
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The objective of this paper is to address the challenging task of targeting Human Immunodeficiency Virus type 1 Reverse Transcriptase (HIV-1 RT) in the treatment of AIDS. Reverse Transcriptase inhibitors (RTIs) have limitations due to the development of Reverse Transcriptase mutations that lead to treatment resistance. In this study, a combination of statistical analysis and bioinformatics tools was adopted to develop a mathematical model that relates the structure of compounds to their inhibitory activities against HIV-1 Reverse Transcriptase. Our approach was based on a series of compounds recognized for their HIV-1 RT enzymatic inhibitory activities. These compounds were designed via software, with their descriptors computed using multiple tools. The most statistically promising model was chosen, and its domain of application was ascertained. Furthermore, compounds exhibiting comparable biological activity to existing drugs were identified as potential inhibitors of HIV-1 RT. The compounds underwent evaluation based on their chemical absorption, distribution, metabolism, excretion, toxicity properties, and adherence to Lipinski's rule. Molecular docking techniques were employed to examine the interaction between the Reverse Transcriptase (Wild Type and Mutant Type) and the ligands, including a known drug available in the market. Molecular dynamics simulations were also conducted to assess the stability of the RT-ligand complexes. Our results reveal some of the new compounds as promising candidates for effectively inhibiting HIV-1 Reverse Transcriptase, matching the potency of the established drug. This necessitates further experimental validation. This study, beyond its immediate results, provides a methodological foundation for future endeavors aiming to discover and design new inhibitors targeting HIV-1 Reverse Transcriptase.Keywords: QSAR, ADMET properties, molecular docking, molecular dynamics simulation, reverse transcriptase inhibitors, HIV type 1
Procedia PDF Downloads 482092 QSAR Study and Haptotropic Rearrangement in Estradiol Derivatives
Authors: Mohamed Abd Esselem Dems, Souhila Laib, Nadjia Latelli, Nadia Ouddai
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In this work, we have developed QSAR model for Relative Binding Affinity (RBA) of a large diverse set of estradiol among these derivatives, the organometallic derivatives. By dividing the dataset into a training set of 24 compounds and a test set of 6 compounds. The DFT method was used to calculate quantum chemical descriptors and physicochemical descriptors (MR and MLOGP) were performed using E-Dragon. All the validations indicated that the QSAR model built was robust and satisfactory (R2 = 90.12, Q2LOO = 86.61, RMSE = 0.272, F = 60.6473, Q2ext =86.07). We have therefore apply this model to predict the RBA, for two isomers β and α wherein Mn(CO)3 complex with the aromatic ring of estradiol, and the two isomers show little appreciation for the estrogenic receptor (RBAβ = 1.812 and RBAα = 1.741).Keywords: DFT, estradiol, haptotropic rearrangement, QSAR, relative binding affinity
Procedia PDF Downloads 2562091 Thick Disc Molecular Gas Fraction in NGC 6946
Authors: Narendra Nath Patra
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Several recent studies reinforce the existence of a thick molecular disc in galaxies along with the dynamically cold thin disc. Assuming a two-component molecular disc, we model the disc of NGC 6946 as a four-component system consists of stars, HI, thin disc molecular gas, and thick disc molecular gas in vertical hydrostatic equilibrium. Following, we set up the joint Poisson-Boltzmann equation of hydrostatic equilibrium and solve it numerically to obtain a three-dimensional density distribution of different baryonic components. Using the density solutions and the observed rotation curve, we further build a three-dimensional dynamical model of the molecular disc and consecutively produce simulated CO spectral cube and spectral width profile. We find that the simulated spectral width profiles distinguishably differs for different assumed thick disc molecular gas fraction. Several CO spectral width profiles are then produced for different assumed thick disc molecular gas fractions and compared with the observed one to obtain the best fit thick disc molecular gas fraction profile. We find that the thick disc molecular gas fraction in NGC 6946 largely remains constant across its molecular disc with a mean value of 0.70 +/- 0.09. We also estimate the amount of extra-planar molecular gas in NGC 6946. We find 60% of the total molecular gas is extra-planar at the central region, whereas this fraction reduces to ~ 35% at the edge of the molecular disc. With our method, for the first time, we estimate the thick disc molecular gas fraction as a function of radius in an external galaxy with sub-kpc resolution.Keywords: galaxies: kinematics and dynamic, galaxies: spiral, galaxies: structure , ISM: molecules, molecular data
Procedia PDF Downloads 1002090 Artificial Intelligence in Bioscience: The Next Frontier
Authors: Parthiban Srinivasan
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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction
Procedia PDF Downloads 3272089 QSAR Study on Diverse Compounds for Effects on Thermal Stability of a Monoclonal Antibody
Authors: Olubukayo-Opeyemi Oyetayo, Oscar Mendez-Lucio, Andreas Bender, Hans Kiefer
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The thermal melting curve of a protein provides information on its conformational stability and could provide cues on its aggregation behavior. Naturally-occurring osmolytes have been shown to improve the thermal stability of most proteins in a concentration-dependent manner. They are therefore commonly employed as additives in therapeutic protein purification and formulation. A number of intertwined and seemingly conflicting mechanisms have been put forward to explain the observed stabilizing effects, the most prominent being the preferential exclusion mechanism. We attempted to probe and summarize molecular mechanisms for thermal stabilization of a monoclonal antibody (mAb) by developing quantitative structure-activity relationships using a rationally-selected library of 120 osmolyte-like compounds in the polyhydric alcohols, amino acids and methylamines classes. Thermal stabilization potencies were experimentally determined by thermal shift assays based on differential scanning fluorimetry. The cross-validated QSAR model was developed by partial least squares regression using descriptors generated from Molecular Operating Environment software. Careful evaluation of the results with the use of variable importance in projection parameter (VIP) and regression coefficients guided the selection of the most relevant descriptors influencing mAb thermal stability. For the mAb studied and at pH 7, the thermal stabilization effects of tested compounds correlated positively with their fractional polar surface area and inversely with their fractional hydrophobic surface area. We cannot claim that the observed trends are universal for osmolyte-protein interactions because of protein-specific effects, however this approach should guide the quick selection of (de)stabilizing compounds for a protein from a chemical library. Further work with a large variety of proteins and at different pH values would help the derivation of a solid explanation as to the nature of favorable osmolyte-protein interactions for improved thermal stability. This approach may be beneficial in the design of novel protein stabilizers with optimal property values, especially when the influence of solution conditions like the pH and buffer species and the protein properties are factored in.Keywords: thermal stability, monoclonal antibodies, quantitative structure-activity relationships, osmolytes
Procedia PDF Downloads 2922088 Molecular Clustering and Velocity Increase in Converging-Diverging Nozzle in Molecular Dynamics Simulation
Authors: Jeoungsu Na, Jaehawn Lee, Changil Hong, Suhee Kim
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A molecular dynamics simulation in a converging-diverging nozzle was performed to study molecular collisions and their influence to average flow velocity according to a variety of vacuum levels. The static pressures and the dynamic pressure exerted by the molecule collision on the selected walls were compared to figure out the intensity variances of the directional flows. With pressure differences constant between the entrance and the exit of the nozzle, the numerical experiment was performed for molecular velocities and directional flows. The result shows that the velocities increased at the nozzle exit as the vacuum level gets higher in that area because less molecular collisions.Keywords: cavitation, molecular collision, nozzle, vacuum, velocity increase
Procedia PDF Downloads 4012087 Resource Framework Descriptors for Interestingness in Data
Authors: C. B. Abhilash, Kavi Mahesh
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Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.Keywords: RDF, interestingness, knowledge base, semantic data
Procedia PDF Downloads 1222086 Molecular Insights into the 5α-Reductase Inhibitors: Quantitative Structure Activity Relationship, Pre-Absorption, Distribution, Metabolism, and Excretion and Docking Studies
Authors: Richa Dhingra, Monika, Manav Malhotra, Tilak Raj Bhardwaj, Neelima Dhingra
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5-Alpha-reductases (5AR), a membrane bound, NADPH dependent enzyme and convert male hormone testosterone (T) into more potent androgen dihydrotestosterone (DHT). DHT is the required for the development and function of male sex organs, but its overproduction has been found to be associated with physiological conditions like Benign Prostatic Hyperplasia (BPH). Thus the inhibition of 5ARs could be a key target for the treatment of BPH. In present study, 2D and 3D Quantitative Structure Activity Relationship (QSAR) pharmacophore models have been generated for 5AR based on known inhibitory concentration (IC₅₀) values with extensive validations. The four featured 2D pharmacophore based PLS model correlated the topological interactions (–OH group connected with one single bond) (SsOHE-index); semi-empirical (Quadrupole2) and physicochemical descriptors (Mol. wt, Bromines Count, Chlorines Count) with 5AR inhibitory activity, and has the highest correlation coefficient (r² = 0.98, q² =0.84; F = 57.87, pred r² = 0.88). Internal and external validation was carried out using test and proposed set of compounds. The contribution plot of electrostatic field effects and steric interactions generated by 3D-QSAR showed interesting results in terms of internal and external predictability. The well validated 2D Partial Least Squares (PLS) and 3D k-nearest neighbour (kNN) models were used to search novel 5AR inhibitors with different chemical scaffold. To gain more insights into the molecular mechanism of action of these steroidal derivatives, molecular docking and in silico absorption, distribution, metabolism, and excretion (ADME) studies were also performed. Studies have revealed the hydrophobic and hydrogen bonding of the ligand with residues Alanine (ALA) 63A, Threonine (THR) 60A, and Arginine (ARG) 456A of 4AT0 protein at the hinge region. The results of QSAR, molecular docking, in silico ADME studies provide guideline and mechanistic scope for the identification of more potent 5-Alpha-reductase inhibitors (5ARI).Keywords: 5α-reductase inhibitor, benign prostatic hyperplasia, ligands, molecular docking, QSAR
Procedia PDF Downloads 1322085 Molecular Junctions between Graphene Strips: Electronic and Transport Properties
Authors: Adel Belayadi, Ahmed Mougari, Boualem Bourahla
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Molecular junctions are currently considered a promising style in the miniaturization of electronic devices. In this contribution, we provide a tight-binding model to investigate the quantum transport properties across-molecular junctions sandwiched between 2D-graphene nanoribbons in the zigzag direction. We investigate, in particular, the effect of embedded atoms such as Gold and Silicon across the molecular junction. The results exhibit a resonance behavior in terms of incident Fermi levels, depending on the molecular junction type. Additionally, the transport properties under a perpendicular magnetic field exhibit an oscillation for the transmittance versus the magnetic field strength.Keywords: molecular junction, 2D-graphene nanoribbons, quantum transport properties, magnetic field
Procedia PDF Downloads 572084 Retrieving Similar Segmented Objects Using Motion Descriptors
Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou
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The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval
Procedia PDF Downloads 3452083 Global Based Histogram for 3D Object Recognition
Authors: Somar Boubou, Tatsuo Narikiyo, Michihiro Kawanishi
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In this work, we address the problem of 3D object recognition with depth sensors such as Kinect or Structure sensor. Compared with traditional approaches based on local descriptors, which depends on local information around the object key points, we propose a global features based descriptor. Proposed descriptor, which we name as Differential Histogram of Normal Vectors (DHONV), is designed particularly to capture the surface geometric characteristics of the 3D objects represented by depth images. We describe the 3D surface of an object in each frame using a 2D spatial histogram capturing the normalized distribution of differential angles of the surface normal vectors. The object recognition experiments on the benchmark RGB-D object dataset and a self-collected dataset show that our proposed descriptor outperforms two others descriptors based on spin-images and histogram of normal vectors with linear-SVM classifier.Keywords: vision in control, robotics, histogram, differential histogram of normal vectors
Procedia PDF Downloads 2422082 In Silico Modeling of Drugs Milk/Plasma Ratio in Human Breast Milk Using Structures Descriptors
Authors: Navid Kaboudi, Ali Shayanfar
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Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.Keywords: logistic regression, breastfeeding, descriptors, penetration
Procedia PDF Downloads 352081 Molecular Docking Assessment of Pesticides Binding to Bacterial Chitinases
Authors: Diana Larisa Vladoiu, Vasile Ostafe, Adriana Isvoran
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Molecular docking calculations reveal that pesticides provide favorable interactions with the bacterial chitinases. Pesticides interact with both hydrophilic and aromatic residues involved in the active site of the enzymes, their positions partially overlapping the substrate and the inhibitors locations. Molecular docking outcomes, in correlation with experimental literature data, suggest that the pesticides may be degraded or having an inhibitor effect on the activity of these enzymes, depending of the application dose and rate.Keywords: chitinases, inhibition, molecular docking, pesticides
Procedia PDF Downloads 5102080 A Comparative and Mixed Methods Study of Possible Selves of Adolescent Boys in an Observation Home and a Children's Home in India
Authors: Apurva Sapra
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The aim of this research was to study and compare the nature of expected, feared and hoped-for selves in institutionalized adolescent boys in two residential settings – an observation home with children in conflict with the law, and a children’s home with children in need of care and protection. The study uses a concurrent mixed methods design, in which eight adolescent boys from each group, aged 13-17, were asked to respond to a questionnaire, followed by an in-depth interview. The questionnaire looked into the total scores on current, probable and hoped-for/feared positive and negative self-descriptors. Possible selves of both groups were found to be influenced by their unique histories, such as with their experience of violence, interaction with the police and emphasis given on education. Expected selves and hoped-for selves were similar within the two groups. However, they were more concrete and attainable in the observation home and more ambitious in the children’s home. Quantitative results showed that on the positive self-descriptors, the participants in the observation home had a slightly lower total score on the current parameter as on the probable and hoped-for parameters. The participants in the children’s home showed similar results on current and probable positive self-descriptors, with higher scores on the hoped-for parameter. For most of the negative self-descriptors, the current score for the observation home group was lower than the expected score, and for the children’s home group, they were feared slightly more than they were expected. Along with the nature of possible selves, the study also looked into threats and support to desired and feared possible selves, as well as strategies to attain the desired possible selves and avoid feared possible selves. While threats to possible selves were identified as external and internal in both groups, the participants in the children’s home tended to identify threats as external. The categories of support were similar across the two groups, although the nature of support provided differed. Strategies adopted by participants in the observation home could be clearly divided as past, present and future strategies, while those adopted by participants in the children’s home had an overlap with past and future strategies. The institution was perceived as having a negative influence for the future in the observation home group, but positive in the children’s home group. Limitations of the study and recommendations for future research, policy setting and the counselling profession are discussed.Keywords: adolescents, expected self, feared self, hoped-for self, institutions, possible selves
Procedia PDF Downloads 1982079 Effect of Plasticizer Additives on the Mechanical Properties of Cement Composite: A Molecular Dynamics Analysis
Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar
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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular/nanoscale models is demonstrated.Keywords: cement composite, mechanical properties, molecular dynamics, plasticizer additives
Procedia PDF Downloads 4142078 Images Selection and Best Descriptor Combination for Multi-Shot Person Re-Identification
Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli
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To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection
Procedia PDF Downloads 2472077 Application of Molecular Markers for Crop Improvement
Authors: Monisha Isaac
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Use of molecular markers for selecting plants with desired traits has been started long back. Due to their heritable characteristics, they are useful for identification and characterization of specific genotypes. The study involves various types of molecular markers used to select multiple desired characters in plants, their properties, and advantages to improve crop productivity in adverse climatological conditions for the purpose of providing food security to fast-growing global population. The study shows that genetic similarities obtained from molecular markers provide more accurate information and the genetic diversity can be better estimated from the genetic relationship obtained from the dendrogram. The information obtained from markers assisted characterization is more suitable for the crops of economic importance like sugarcane.Keywords: molecular markers, crop productivity, genetic diversity, genotype
Procedia PDF Downloads 4752076 Topological Analysis of Hydrogen Bonds in Pyruvic Acid-Water Mixtures
Authors: Ferid Hammami
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The molecular geometries of the possible conformations of pyruvic acid-water complexes (PA-(H₂O)ₙ = 1- 4) have been fully optimized at DFT/B3LYP/6-311G ++ (d, p) levels of calculation. Among several optimized molecular clusters, the most stable molecular arrangements obtained when one, two, three, and four water molecules are hydrogen-bonded to a central pyruvic acid molecule are presented in this paper. Apposite topological and geometrical parameters are considered as primary indicators of H-bond strength. Atoms in molecules (AIM) analysis shows that pyruvic acid can form a ring structure with water, and the molecular structures are stabilized by both strong O-H...O and C-H...O hydrogen bonds. In large clusters, classical O-H...O hydrogen bonds still exist between water molecules, and a cage-like structure is built around some parts of the central molecule of pyruvic acid. The electrostatic potential energy map (MEP) and the HOMO-LUMO molecular orbital (highest occupied molecular orbital-lowest unoccupied molecular orbital) analysis has been performed for all considered complexes.Keywords: pyruvic acid, PA-water complex, hydrogen bonding, DFT, AIM, MEP, HOMO-LUMO
Procedia PDF Downloads 1742075 Characterization on Molecular Weight of Polyamic Acids Using GPC Coupled with Multiple Detectors
Authors: Mei Hong, Wei Liu, Xuemin Dai, Yanxiong Pan, Xiangling Ji
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Polyamic acid (PAA) is the precursor of polyimide (PI) prepared by a two-step method, its molecular weight and molecular weight distribution not only play an important role during the preparation and processing, but also influence the final performance of PI. However, precise characterization on molecular weight of PAA is still a challenge because of the existence of very complicated interactions in the solution system, including the electrostatic interaction, hydrogen bond interaction, dipole-dipole interaction, etc. Thus, it is necessary to establisha suitable strategy which can completely suppress these complex effects and get reasonable data on molecular weight. Herein, the gel permeation chromatography (GPC) coupled with differential refractive index (RI) and multi-angle laser light scattering (MALLS) detectors were applied to measure the molecular weight of (6FDA-DMB) PAA using different mobile phases, LiBr/DMF, LiBr/H3PO4/THF/DMF, LiBr/HAc/THF/DMF, and LiBr/HAc/DMF, respectively. It was found that combination of LiBr with HAc can shield the above-mentioned complex interactions and is more conducive to the separation of PAA than only addition of LiBr in DMF. LiBr/HAc/DMF was employed for the first time as a mild mobile phase to effectively separate PAA and determine its molecular weight. After a series of conditional experiments, 0.02M LiBr/0.2M HAc/DMF was fixed as an optimized mobile phase to measure the relative and absolute molecular weights of (6FDA-DMB) PAA prepared, and the obtained Mw from GPC-MALLS and GPC-RI were 35,300 g/mol and 125,000 g/mol, respectively. Particularly, such a mobile phase is also applicable to other PAA samples with different structures, and the final results on molecular weight are also reproducible.Keywords: Polyamic acids, Polyelectrolyte effects, Gel permeation chromatography, Mobile phase, Molecular weight
Procedia PDF Downloads 152074 Improved Performance in Content-Based Image Retrieval Using Machine Learning Approach
Authors: B. Ramesh Naik, T. Venugopal
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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms
Procedia PDF Downloads 1422073 Object Detection Based on Plane Segmentation and Features Matching for a Service Robot
Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan
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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots
Procedia PDF Downloads 5012072 Using Electronic Portfolio to Promote English Speaking Ability of EFL Undergraduate Students
Authors: Jiraporn Lao-Un, Dararat Khampusaen
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Lack of exposure to English language in the authentic English setting naturally leads to a lack of fluency in the language. As a result, Thai EFL learners are struggling in meeting with the communication 'can do' descriptors of the Common European Framework of References (CEFR) required by the Ministry of Education. This initial phase of the ongoing study, employing the e-portfolio to promote the English speaking ability, probed into the effects of the use of e-portfolio on Thai EFL nursing students' speaking ability. Also, their opinions towards the use of e-portfolio to enhance their speaking ability were investigated. The participants were 44 undergraduate nursing students at a Thai College of Nursing. The participants undertook four lessons to promote their communication skills according to the CEFR criteria. Throughout the semester, the participants videotaped themselves while completing the four speaking tasks. The videos were then uploaded onto the e-portfolio website where the researcher provided them with the feedbacks. The video records were analyzed by the speaking rubric designed according to the CEFR 'can do' descriptors. Also, students were required to record self-reflections in video format and upload onto the same URL Students' oral self-reflections were coded to find out the perceptions towards the use of the e-portfolio in promoting their speaking ability. The results from the two research instruments suggested the effectiveness of the tool on improving speaking ability, learner autonomy and media literacy skills. In addition, the oral reflection videos revealed positive opinion towards the tool. The discussion offers the current status of English speaking ability among Thai EFL students. This reveals the gaps between the EFL speaking ability and the CEFR ‘can do’ descriptors. In addition, the author raises the light on integration of the 21st century IT tool to enhance these students’ speaking ability. Lastly, the theoretical implications and recommendation for further study in integrating electronic tools to promote language skills in the EFL context are offered for further research.Keywords: EFL communication, EFL speaking, English communication, E-learning, E-portfolio, speaking ability, Thai EFL learners
Procedia PDF Downloads 1282071 Human Action Retrieval System Using Features Weight Updating Based Relevance Feedback Approach
Authors: Munaf Rashid
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For content-based human action retrieval systems, search accuracy is often inferior because of the following two reasons 1) global information pertaining to videos is totally ignored, only low level motion descriptors are considered as a significant feature to match the similarity between query and database videos, and 2) the semantic gap between the high level user concept and low level visual features. Hence, in this paper, we propose a method that will address these two issues and in doing so, this paper contributes in two ways. Firstly, we introduce a method that uses both global and local information in one framework for an action retrieval task. Secondly, to minimize the semantic gap, a user concept is involved by incorporating features weight updating (FWU) Relevance Feedback (RF) approach. We use statistical characteristics to dynamically update weights of the feature descriptors so that after every RF iteration feature space is modified accordingly. For testing and validation purpose two human action recognition datasets have been utilized, namely Weizmann and UCF. Results show that even with a number of visual challenges the proposed approach performs well.Keywords: relevance feedback (RF), action retrieval, semantic gap, feature descriptor, codebook
Procedia PDF Downloads 4312070 Design of Organic Inhibitors from Quantum Chemistry
Authors: Rahma Tibigui, Ikram Hadj Said, Rachid Belkada, Dalila Hammoutene
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The vulnerability of industrial facilities is highly concerned with multiple risks from corrosion. The commonly adopted solution is based on the use of organic inhibitors, which are gradually being replaced by environmentally friendly organic inhibitors. In our work, we carried out a quantum chemical study based on the Density Functional Theory (DFT) method at the B3LYP/6-311G (d,p) level of theory. The inhibitory performance of a derivative of the tetrazole molecule has been investigated and reported as a carbon steel-friendly corrosion inhibitor in hydrochloric acid (HCl) medium. The relationship is likely to exist between the molecular structure of this compound as well as its various global reactivity descriptors, and its corrosion inhibition efficiency, which was examined and then discussed. The results show low values of ΔE, which represent strong adsorption of the inhibitor on the steel surface. Moreover, the flat adsorption orientation confirmed the great ability to donate (accept) electrons to (from) steel, fabricating an anchored barrier to prevent steel from corrosion.Keywords: eco-friendly, corrosion inhibitors, tetrazole, DFT
Procedia PDF Downloads 1992069 An Insight into the Conformational Dynamics of Glycan through Molecular Dynamics Simulation
Authors: K. Veluraja
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Glycan of glycolipids and glycoproteins is playing a significant role in living systems particularly in molecular recognition processes. Molecular recognition processes are attributed to their occurrence on the surface of the cell, sequential arrangement and type of sugar molecules present in the oligosaccharide structure and glyosidic linkage diversity (glycoinformatics) and conformational diversity (glycoconformatics). Molecular Dynamics Simulation study is a theoretical-cum-computational tool successfully utilized to establish glycoconformatics of glycan. The study on various oligosaccharides of glycan clearly indicates that oligosaccharides do exist in multiple conformational states and these conformational states arise due to the flexibility associated with a glycosidic torsional angle (φ,ψ) . As an example: a single disaccharide structure NeuNacα(2-3) Gal exists in three different conformational states due to the differences in the preferential value of glycosidic torsional angles (φ,ψ). Hence establishing three dimensional structural and conformational models for glycan (cartesian coordinates of every individual atoms of an oligosaccharide structure in a preferred conformation) is quite crucial to understand various molecular recognition processes such as glycan-toxin interaction and glycan-virus interaction. The gycoconformatics models obtained for various glycan through Molecular Dynamics Simulation stored in our 3DSDSCAR (3DSDSCAR.ORG) a public domain database and its utility value in understanding the molecular recognition processes and in drug design venture will be discussed.Keywords: glycan, glycoconformatics, molecular dynamics simulation, oligosaccharide
Procedia PDF Downloads 96