Search results for: molecular identification

Authors: Eunae Lee, Oh-Kuen Kwon, Ki-Sub Kim, Jeong Won Kang

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We investigated the dynamic properties of graphene-nanoribbon (GNR) memory encapsulating graphene-nanoflake (GNF) shuttle in the potential to be applicable as a non-volatile random access memory via molecular dynamics simulations. This work explicitly demonstrates that the GNR encapsulating the GNF shuttle can be applied to nonvolatile memory. The potential well was originated by the increase of the attractive vdW energy between the GNRs when the GNF approached the edges of the GNRs. So the bistable positions were located near the edges of the GNRs. Such a nanoelectromechanical non-volatile memory based on graphene is also applicable to the development of switches, sensors, and quantum computing.

Keywords: graphene nanoribbon, graphene nanoflake, shuttle memory, molecular dynamics

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Authors: Hyun-Woo Cho

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It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: L. Heidari, M. Jalili Ghazizade

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In recent years, different petrochemical complexes have been established to produce aromatic compounds. Among them, Nouri Petrochemical Complex (NPC) is the largest producer of aromatic raw materials in the world, and is located in south of Iran. Environmental concerns have been raised in this region due to generation of different types of solid waste generated in the process of aromatics production, and subsequently, industrial waste characterization has been thoroughly considered. The aim of this study is qualitative and quantitative characterization of industrial waste generated in the aromatics production process and determination of the best method for industrial waste management. For this purpose, all generated industrial waste during the production process was determined using a checklist. Four main industrial wastes were identified as follows: spent industrial soil, spent catalyst, spent molecular sieves and spent N-formyl morpholine (NFM) solvent. The amount of heavy metals and organic compounds in these wastes were further measured in order to identify the nature and toxicity of such a dangerous compound. Then industrial wastes were classified based on lab analysis results as well as using different international lists of hazardous waste identification such as EPA, UNEP and Basel Convention. Finally, the best method of waste disposal is selected based on environmental, economic and technical aspects. 

Keywords: aromatic compounds, industrial soil, molecular sieve, normal formyl morpholine solvent

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Authors: T. Rajamäki

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In clean room environment molecular contamination in very small concentrations can cause significant harm for the components and processes. This is commonly referred as airborne molecular contamination (AMC). There is a shortage of high sensitivity continuous measurement data for existence and behavior of several of these contaminants. Accordingly, in most cases correlation between concentration of harmful molecules and their effect on processes is not known. In addition, the formation and distribution of contaminating molecules are unclear. In this work sensitive optical techniques are applied in clean room facilities for investigation of concentrations, forming mechanisms and effects of contaminating molecules. Special emphasis is on reactive acid and base gases ammonia (NH3) and hydrogen fluoride (HF). They are the key chemicals in several operations taking place in clean room processes.

Keywords: AMC, clean room, concentration, reactive gas

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Authors: Arun Kharate, Sarata Kumar Sahu, Susen Kumar Panda, Niranjan Sahoo, H. K. Panda

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In the present study, an attempt has been made for isolation and identification of feline panleukopaenia virus (FPLV) from wild felids of Nandankanan zoo, Odisha, India, along with prevalence study of FPLV. Fecal samples collected from wild felids (26 tigers, 22 lions, 5 leopards, 3 hyenas, 1 jaguar, 2 foxes and 1 wild cat) were subjected to hemagglutinnation test and fluorescent antibody test. In hemagglutinnation test 13 (50%) samples from tiger, 14 (63.63%) samples from lions, 1 (20%) sample from leopards, 1 (50%) from fox, 3 (100%) samples from hyenas and 1 (100%) sample from wild cat were positive. On fluorescent antibody test (FAT), 15 (57.69%) samples from tiger, 18 (81.81%) from lions, 2 (40%) from leopards, 1 (50%) from fox, 3 (100%) from hyenas and 1 (100%) from wild cat were positive. FPLV was isolated using MDBK cell line and preliminary characterization was done on the basis of characteristic cytopathic effect. The virus samples were quantified through titration in MDBK cells. Serological confirmation of FPLV isolates was carried out by HI test, micro-SNT and indirect-ELISA. Physico-chemical characters like pH and temperature resistance along molecular identification using specific FPLV primers was carried out. Seroprevalence study of 36 serum samples employing HI test, micro SNT and indirect-ELISA revealed prevalence of 38.8, 44.4 and 72.2% respectively. During study period an adult tigress and a tiger cub died suspected of feline panleukopenia. The necropsy findings in both animals showed hemorrhagic gastroenteritis. The cytological examination revealed presence of intranuclear inclusion bodies in the intestinal epithelial cells. Spleen, mesenteric lymph node and intestine were positive for feline panleukopenia by FAT. The investigation revealed that feline panleukopenia was prevalent in wild felines of Nandankanan zoo.

Keywords: Feline panleukopenia, fluorescent antibody test, hemagglutination test, indirect-ELISA, Nandankanan zoo

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Authors: Mosaab A. Omara, Layla O. Elmajdoubb, Mohammad Saleh Al-Aboodyc, Ahmed ElSifyd, Ahmed O. Elkhtamd

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The aim of this study is to present the molecular characterization of cysticercus tenuicolis of Taenia hydatigena from livestock isolates in Egypt, using the amplification of sequencing of the mt-CO1 gene. We introduce a detailed image of the Cysticercus tenuicolis infection in ruminant animals in Upper Egypt. Cysticercus tenuicolis inhabits such organs in ruminants as the omentum, viscera, and liver. In the present study, the infection rate of Cysticercus tenuicolis was found to be 16% and 19% in sheep and goat sample respectively. Firstly we report one larval stage of Taenia hydatigena detected in the camel liver in Egypt. Cysticercus tenuicolis infection manifested a higher prevalence in females than in males. Those above 2 years of age manifested a higher infection rate than younger animals. The preferred site for the infection was the omentum: a 70% preference in sheep and a 68% preference in goat samples. The molecular characterization using the mitochondrial cytochrome c oxidase subunit 1 (CO1) gene of isolates from sheep, goats and camels corresponded to T. hydatigena. For this study, molecular characterizations of T. hydatigena were done for the first time in Egypt. Molecular tools are of great assistance in characterizing the Cysticercus tenuicolis parasite especially when the morphological character cannot be detected because the metacestodes are frequently confused with infection by the Hydatid cyst, especially when these occur in the visceral organs. In the present study, Cysticercus tenuicolis manifested high identity in the goat and sheep samples, while differences were found more frequently in the camel samples (10 pairbase). Clearly molecular diagnosis for Cysticercus tenuicolis infection significantly helps to differentiate it from such other metacestodes.

Keywords: cysticercus tenuicolis, its2, genetic, qena, molecular and taenia hydatigena

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Authors: Ekatereine Abashidze, Nino Nazarashvili, Dali Gaganidze, Oleg Gorgadze, Mariam Aznarashvili, Eter Gvritishvili

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Potato is one of the leading agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. Potato production is equal to 25,000 ha and its average yield is 20-25 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (Globodera pallida (Stone) Behrens and Globodera rostochiensis (Wollenveber) Behrens) are harmful around the world. PCN is among the most difficult plant pests to control. Cysts protected by a durable wall can survive for over 30 years . Control of PCN (G. pallida and G. rostochiensis) is regulated by Council Directive 2007/33/EE C. There was no legislative regulation of these pests in Georgia before 2016. By Resolution #302 from July 1, 2016, developed within the action plan of the DCFTA (Deep and Comprehensive Free Trade Area) the Government of Georgia established control over potato cyst nematodes. The Agreement about the legal acts approximation to EU legislation concerns the approval of rules of PCN control and research of these pests. Taking into consideration the above mentioned, it is necessary to study PCN (G. pallida and G. rostochiensis) in the potato-growing areas of Georgia. The aim of this research is to conduct survey of potato cyst nematodes (Globodera rostochiensis and G. pallida) in two geographically distinct regions of Georgia - Samtskhe - Javakheti and Svanetii and to identify the species G. Rostochiensis and G. Pallida by the morphological - morphometric and molecular methods. Soil samples were taken in each village, in a zig-zag pattern on the potato fields of the private sector, using the Metlitsky method. Samples were taken also from infested potato plant roots. To extract nematode cysts from soil samples Fanwick can be used according to standard methods by EPPO. Cysts were measured under a stereoscopic microscope (Leica M50). Identification of the nematod species was carried out according to morphological and morphometric characteristics of the cysts and larvae using appropriate protocols EPPO. For molecular identification, a multiplex PCR test was performed by the universal ITS5 and cyst nematodes’ (G. pallida, G. rostochiensis) specific primers. To identify the species of potato cyst nematodes (PCN) in two regions (Samtskhe-Javakheti and Svaneti) were taken 200 samples, among them: 80 samples in Samtskhe-Javakheti region and 120 in Svaneti region. Cysts of Globiodera spp. were revealed in 50 samples obtained from Samtskhe-Javakheti and 80 samples from Svaneti regions. Morphological, morphometric and molecular analysis of two forms of PCN found in investigated regions of Georgia shows that one form of PCN belongs to G. rostoshiensi; the second form is the different species of Globodera sp.t is the subject of future research. Despite the different geographic locations, larvae and cysts of G. rostoshiensi were found in both regions. But cysts and larvae of G. pallida were not reported. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia: Project # FR17_235.

Keywords: cyst nematode, globodera rostochiensis, globodera pallida, morphologic-morphometric measurement

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Somayeh Akrami, Vali-Allah Mozaffarian, Habib Onsori

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The studied region in this research, watershed Kuhkamar river, is about 112.66 square kilometers, it is located between 45º 48' 9" to 45º 2' 20" N and 38º 34' 15" to 38º 40' 28" E. The gained results of the studies on flora combinations, proved 287 plant species in 190 genera and 51 families. Asteracea with 49 and Lamiaceae with 27 plant species are the major plant families. Among collected species one interesting plant was found and determined as a new record Anemone narcissiflora L. for flora of Iran. This plant is known as a complex species that shows intraspecific speciation and is classified into about 12 subspecies and 10 varieties in world. To identify the infraspecies taxons of this species, in addition to morphological characteristics, the use of appropriate molecular markers for the better isolation of the individuals were needed.

Keywords: Anemone narcissiflora, floristic Study, kuhkamar, molecular marker

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: H. K. Ratre, M. Roy, S. Roy, M. S. Parmar, V. Bhagat

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Mastitis is a common problem of dairy industries. Reduction in milk production and an irreparable damage to the udder associated with the disease are common causes of culling of dairy cows. Milk from infected animals is not suitable for drinking and for making different milk products. So, it has a major economic importance in dairy cattle. The aims of this study were to investigate the bacteriological panorama in milk from udder quarters with subclinical mastitis and to carried out for the molecular characterization of the major isolated organisms, from subclinical mastitis-affected cows in and around Durg and Rajnandgaon district of Chhattisgarh. Isolation and identification of bacteria from the milk samples of subclinical mastitis-affected cows were done by standard and routine culture procedures. A total of 78 isolates were obtained from cows and among the various bacteria isolated, Staphylococcus spp. occupied prime position with occurrence rate of 51.282%. However, other bacteria isolated includeStreptococcus spp. (20.512%), Micrococcus spp. (14.102%), E. coli (8.974%), Klebsiela spp. (2.564%), Salmonella spp. (1.282%) and Proteus spp. (1.282%). Staphylococcus spp. was isolated as the major causative agent of subclinical mastitis in the studied area. Molecular characterization of Staphylococus aureusisolates was done for genetic expression of the virulence genes like ‘nuc’ encoding thermonucleaseexoenzyme, coa and spa by PCR amplification of the respective genes in 25 Staphylococcus isolates. In the present study, 15 isolates (77.27%) out of 20 coagulase positive isolates were found to be genotypically positive for ‘nuc’ where as 20 isolates (52.63%) out of 38 CNS expressed the presence of the same virulence gene. In the present study, three Staphylococcus isolates were found to be genotypically positive for coa gene. The Amplification of the coa gene yielded two different products of 627, 710 bp. The amplification of the gene segment encoding the IgG binding region of protein A (spa) revealed a size of 220 and 253bp in twostaphylococcus isolates. The X-region binding of the spa gene produced an amplicon of 315 bp in one Staphylococcal isolates. Staphylococcus aureus was found to be major isolate (51.28%) responsible for causing subclinical mastitis in cows which also showed expression of virulence genesnuc, coa and spa.

Keywords: mastitis, bacteria, characterization, expression, gene

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Authors: Kenneth Larsen, Astrid Aasland, Synnve Schjølberg, Trond Diseth

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Autism Spectrum Disorders (ASD) are neurodevelopmental disorders emerging in early development characterized by impairment in social communication skills and a restricted, repetitive and stereotyped patterns of behavior and interests. Early identification and interventions potentially improve development and quality of life of children with ASD. Symptoms of ASD are apparent through the second year of life, yet diagnostic age are still around 4 years of age. This study explored whether symptoms associated with ASD are possible to identify in typical Norwegian day-care centers in the second year of life. Results of this study clearly indicates that most described symptoms also are identifiable by day-care staff, and that a short observation list of 5 symptoms clearly identify children with ASD from a sample of normal developing peers.

Keywords: autism, early identification, day-care, screening

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Authors: Fathi Soliman

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With the ultimate goal of developing the separation of n-paraffin as phase change material (PCM) by means of molecular dynamic simulations, we attempt to predict the solubility of aromatic n-paraffin in two organic solvents: Butyl Acetate (BA) and Methyl Iso Butyl Ketone (MIBK). A simple model of aromatic paraffin: 2-hexadecylantharacene with amorphous molecular structure and periodic boundary conditions was constructed. The results showed that MIBK is the best solvent to separate ultra-pure phase change materials and this data was compatible with experimental data done to separate ultra-pure n-paraffin from waste petroleum aromatic paraffin wax, the separated n-paraffin was characterized by XRD, TGA, GC and DSC, moreover; data revealed that the n-paraffin separated by using MIBK is better as PCM than that separated using BA.

Keywords: molecular dynamics simulation, n-paraffin, organic solvents, phase change materials, solvent extraction

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Authors: Muchun Yu, Xue Gao, Qian Chen

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As a novel passive vibration isolation technology, molecular spring isolator (MSI) is investigated in this paper. An MSI consists of water and hydrophobic zeolites as working medium. Under periodic excitation, water molecules intrude into hydrophobic pores of zeolites when the pressure rises and water molecules extrude from hydrophobic pores when pressure drops. At the same time, energy is stored, released and dissipated. An MSI of piston-cylinder structure was designed in this work. Experiments were conducted to investigate the stiffness properties of MSI. The results show that MSI exhibits high-static-low dynamic (HSLD) stiffness. Furthermore, factors such as the quantity of zeolites, temperature, and ions in water are proved to have an influence on the stiffness properties of MSI.

Keywords: hydrophobic zeolites, molecular spring, stiffness, vibration isolation

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Authors: Joon-Hoon Park

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In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

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Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

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A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

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Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

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Authors: Varsha Singh, Shraddha Prajapati, M. B. Kiran

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Texture identification is useful in predicting the functionality of a component. Many of the existing texture identification methods are of contact in nature, which limits its measuring speed. These contact measurement techniques use a diamond stylus and the diamond stylus being sharp going to damage the surface under inspection and hence these techniques can be used in statistical sampling. Though these contact methods are very accurate, they do not give complete information for full characterization of surface. In this context, the presented method assumes special significance. The method uses a relatively low cost vision system for image acquisition. Software is developed based on wavelet transform, for analyzing texture images. Specimens are made using different manufacturing process (shaping, grinding, milling etc.) During experimentation, the specimens are illuminated using proper lighting and texture images a capture using CCD camera connected to the vision system. The software installed in the vision system processes these images and subsequently identify the texture of manufacturing processes.

Keywords: diamond stylus, manufacturing process, texture identification, vision system

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Authors: Mahmoud A. Abdulhamid

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Poly(ether-ether-ketone) (PEEK) has received increased attention due to its outstanding performance in different membrane applications including gas and liquid separation. However, it suffers from a semi-crystalline morphology, bad solubility and low porosity. To fabricate membranes from PEEK, the usage of harsh acid such as sulfuric acid is essential, regardless its hazardous properties. In this work, we report the molecular design of poly(ether-ether-ketones) (iPEEKs) with intrinsic porosity character, by incorporating kinked units into PEEK backbone such as spirobisindane, Tröger's base, and triptycene. The porous polymers were used to fabricate stable membranes for organic solvent nanofiltration application. To better understand the mechanism, we conducted molecular dynamics simulations to evaluate the possible interactions between the polymers and the solvents. Notable enhancement in separation performance was observed confirming the importance of molecular engineering of high-performance polymers. The iPEEKs demonstrated good solubility in polar aprotic solvents, a high surface area of 205–250 m² g⁻¹, and excellent thermal stability. Mechanically flexible nanofiltration membranes were prepared from N-methyl-2-pyrrolidone dope solution at iPEEK concentrations of 19–35 wt%. The molecular weight cutoff of the membranes was fine-tuned in the range of 450–845 g mol⁻¹ displaying 2–6 fold higher permeance (3.57–11.09 L m⁻² h⁻¹ bar⁻¹) than previous reports. The long-term stabilities were demonstrated by a 7 day continuous cross-flow filtration.

Keywords: molecular engineering, polymer synthesis, membrane fabrication, liquid separation

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Authors: M. Moaeen-ud-Din, G. Bilal, M. Yaqoob

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Identification of genes of importance regarding production traits in buffalo is impaired by a paucity of genomic resources. Choice to fill this gap is to exploit data available for cow. The cross-species application of comparative genomics tools is potential gear to investigate the buffalo genome. However, this is dependent on nucleotide sequences similarity. In this study gene diversity between buffalo and cattle was determined by using 86 gene orthologues. There was about 3% difference in all genes in term of nucleotide diversity; and 0.267±0.134 in amino acids indicating the possibility for successfully using cross-species strategies for genomic studies. There were significantly higher non synonymous substitutions both in cattle and buffalo however, there was similar difference in term of dN – dS (4.414 vs 4.745) in buffalo and cattle respectively. Higher rate of non-synonymous substitutions at similar level in buffalo and cattle indicated a similar positive selection pressure. Results for relative rate test were assessed with the chi-squared test. There was no significance difference on unique mutations between cattle and buffalo lineages at synonymous sites. However, there was a significance difference on unique mutations for non synonymous sites indicating ongoing mutagenic process that generates substitutional mutation at approximately the same rate at silent sites. Moreover, despite of common ancestry, our results indicate a different divergent time among genes of cattle and buffalo. This is the first demonstration that variable rates of molecular evolution may be present within the family Bovidae.

Keywords: buffalo, cattle, gene diversity, molecular evolution

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Authors: Christy Rosaline, Rathankar Roa, Waheeta Hopper

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Persistence of tuberculosis, emergence of multidrug-resistance and extensively drug-resistant forms of the disease, has increased the interest in developing new antitubercular drugs. Developing inhibitors for 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase from Mycobacterium tuberculosis (MtbDAH7Ps), an enzyme involved in shikimate pathway, gives a selective target for antitubercular agents. MtbDAH7Ps was screened against ZINC database, and shortlisted compounds were subjected to induce fit docking. Prime/Molecular Mechanics Generalized Born Surface Area calculation was used to validate the binding energy of ligand-protein complex. Molecular Dynamics analysis for of the lead compounds–MtbDAH7Ps complexes showed that the backbone of MtbDAH7Ps in their complexes were stable. These results suggest that the shortlisted lead compounds ZINC04097114, ZINC15163225, ZINC16857013, ZINC06275603, and ZINC05331260 could be developed into novel drug leads to inhibit DAH7Ps in Mycobacterium tuberculosis.

Keywords: MtbDAH7Ps, Mycobacterium tuberculosis, HTVS, molecular dynamics

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Authors: Emilie Zimet

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During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.

Keywords: identification, student selection, communication, special education, school policy, planning for intervention

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Authors: Micheale Yifter Weldemichael, Stefaan Werbrouck, Hailay Mehari Gebremedhn

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Sesame (Sesamum indicum L.) is among the most important oilseed crops for its high edible oil quality and quantity. Sesame is grown for food, medicinal, pharmaceutical, and industrial uses. Sesame is also cultivated as a main cash crop in Asia and Africa by smallholder farmers. Despite the global exponential increase in sesame cultivation area, its production and productivity remain low, mainly due to biotic and abiotic constraints. Notwithstanding the efforts to solve these problems, a low level of genetic variation and inadequate genomic resources hinder the progress of sesame improvement. The objective of this paper is, therefore, to review recent advances in the area of molecular breeding and transformation to overcome major production constraints and could result in enhanced and sustained sesame production. This paper reviews various researches conducted to date on molecular breeding and genetic transformation in sesame focusing on molecular markers used in assessing the available online database resources, genes responsible for key agronomic traits as well as transgenic technology and genome editing. The review concentrates on quantitative and semi-quantitative studies on molecular breeding for key agronomic traits such as improvement of yield components, oil and oil-related traits, disease and insect/pest resistance, and drought, waterlogging and salt tolerance, as well as sesame genetic transformation and genome editing techniques. Pitfalls and limitations of existing studies and methodologies used so far are identified and some priorities for future research directions in sesame genetic improvement are identified in this review.

Keywords: molecular breeding, oil, sesame, shattering

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Authors: Nikhil Agrawal, Adam A. Skelton

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Alzheimer’s disease (AD) is one of the most common forms of dementia, which is caused by misfolding and aggregation of amyloid beta (Aβ) peptides into amyloid-β fibrils (Aβ fibrils). To disrupt the remodeling of Aβ fibrils, a number of candidate molecules have been proposed. To study the molecular mechanisms of Aβ fibrils remodeling we performed a series of all-atom molecular dynamics simulations, a total time of 3µs, in explicit solvent. Several previously undiscovered candidate molecule-Aβ fibrils binding modes are unraveled; one of which shows the direct conformational change of the Aβ fibril by understanding the physicochemical factors responsible for binding and subsequent remodeling of Aβ fibrils by the candidate molecule, open avenues into structure-based drug design for AD can be opened.

Keywords: alzheimer’s disease, amyloid, MD simulations, misfolded protein

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Authors: Sabitha Rani A., Nagamani V.

Abstract:

Embelia ribes Burm.f (Family-Myrsinaceae) commonly known as Vidanga or Baibirang, is one of the important medicinal plants of India. The seed extract is reported to be antidiabetic, antitumour, analgesic, anti-inflammatory, antispermatogenic, free radical scavenging activities and widely used in more than 75 Ayurvedic commercial formulations. Among the 100 different species of Embelia, E. ribes is considered as a major source of Embelin, a bioactive compound. Because of high demand and low availability, the seeds of E. ribes are substituted with many cheaper alternatives. Therefore, the present study of RAPD-PCR analysis was undertaken to develop molecular markers for identification of E. ribes. A total of 13 different seed samples of Embelia were collected from different agro-climatic regions of India. The seeds of E.ribes were collected from Kalpetta, Kerala and three different seed samples were collected from traders of Odisha, Madhya Pradesh, Maharastra. The other nine seed samples were collected from local traders which they have collected from different regions of India. Genomic DNA was isolated from different seed samples E. ribes and RAPD-PCR was performed on 13 different seed samples using 47 random primers. Out of all the primers, only 22 primers produced clear and highly-reproducible banding patterns. The 22 selected RAPD primers generated a total of 280 alleles with an average of 12 alleles per primer pair. In the present study, we have identified three RAPD-PCR markers i.e. OPF5_480 bp, OPH11_520 bp and OPH4_530 bp which can be used for genetic fingerprinting of E. ribes. This methodology can be employed for identification of original E. ribes and also distinguishing it from other substitutes and adulterants.

Keywords: Embelia ribes, RAPD-PCR, primers, genetic analysis

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Authors: Ashok Kalagura

Abstract:

This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Michel Kulhandjian, Dimitris A. Pados

Abstract:

The objective of this work is to develop a theoretical framework for reliable digital recording system identification from digital audio files alone, for forensic purposes. A digital recording system consists of a microphone and a digital sound processing card. We view the cascade as a system of unknown transfer function. We expect same manufacturer and model microphone-sound card combinations to have very similar/near identical transfer functions, bar any unique manufacturing defect. Input voice (or other) signals are modeled as non-stationary processes. The technical problem under consideration becomes blind deconvolution with non-stationary inputs as it manifests itself in the specific application of digital audio recording equipment classification.

Keywords: blind system identification, audio fingerprinting, blind deconvolution, blind dereverberation

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Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

Abstract:

The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

Procedia PDF Downloads 511