Search results for: molecular characterization

Authors: Benhammadi Hocine, Djamel Boubaya, Chaffai Hicham

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Meskiana Area is characterized by a semi-arid climate where the water supply for irrigation and industry is not sufficient as the priority goes for domestic use. To meet the increasing population growth and development, the authorities have considered building a new water retaining structure on some major temporary water streams. For this purpose Chebabta site on Oued Meskiana was chosen as the future dam site. It is large enough to store the desired volume of water. This study comes to investigate the conditions of the site and the adequacy of the ground as a foundation for the projected dam. The conditions of the site include the geological structure and mainly the presence of discontinuities in the formation on which the dam will be built, the nature of the lithologies under the foundation and the future lake, and the presence of any hazard. This site characterization is usually carried out using different methods in order to highlight any underground buried problematic structure. In this context, the different geophysical technics remain the most used ones. Three geophysical methods were used in the case of the Chebabta dam site, namely, electric survey, seismic refraction, and tomography. The choice of the technics and the location of the scan line was made on the basis of the available geological data. In this sense, profiles have been established on both banks of Oued Meskiana. The obtained results have allowed a better characterization of the geological structure, defining the limit between the surface cover and the bedrock, which is, in other words, the limit between the weathered zone and the bedrock. Their respective thicknesses were also determined by seismic refraction and electrical resistivity sounding. However, the tomography imaging technic has succeeded in positioning a fault structure passing through the right bank of the wadi.

Keywords: dam site, fault, geophysic, investigation, Meskiana

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Authors: Nikolaos Georgoulopoulos, Alkis Hatzopoulos, Konstantinos Karamitsios, Konstantinos Kotrotsios, Alexandros I. Metsai

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In modern server systems, business critical applications run in different types of infrastructure, such as cloud systems, physical machines and virtualization. Often, due to high load and over time, various hardware faults occur in servers that translate to errors, resulting to malfunction or even server breakdown. CPU, RAM and hard drive (HDD) are the hardware parts that concern server administrators the most regarding errors. In this work, selected RAM, HDD and CPU errors, that have been observed or can be simulated in kernel ring buffer log files from two groups of Linux servers, are investigated. Moreover, a severity characterization is given for each error type. Better understanding of such errors can lead to more efficient analysis of kernel logs that are usually exploited for fault diagnosis and prediction. In addition, this work summarizes ways of simulating hardware errors in RAM and HDD, in order to test the error detection and correction mechanisms of a Linux server.

Keywords: hardware errors, Kernel logs, Linux servers, RAM, hard disk, CPU

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Authors: Rym Zouari, Sami Ben Amar, Abdelwaheb Dogui

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This paper presents an experimental characterization of the anisotropic mechanical behavior of 4 textile woven fabrics with different weaves (Twill 3, Plain, Twill4 and Satin 4) by off-axis tensile testing. These tests are applied according seven directions oriented by 15° increment with respect to the warp direction. Fixed and articulated jaws are used. Analysis of experimental results is done through global (Effort/Elongation curves) and local scales. Global anisotropy was studied from the Effort/Elongation curves: shape, breaking load (Frup), tensile elongation (EMT), tensile energy (WT) and linearity index (LT). Local anisotropy was studied from the measurement of strain tensor components in the central area of the specimen as a function of testing orientation and effort: longitudinal strain ɛL, transverse strain ɛT and shearing ɛLT. The effect of used jaws is also analyzed.

Keywords: anisotropy, off-axis tensile test, strain fields, textile woven fabric

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Authors: Adewole Tomiwa Adetunji, Francis Bayo Lewu, Richard Mundembe

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Plants require nitrogen (N) to support desired production levels. There is a need for better understanding of N transport mechanism in order to improve N assimilation by plant root. Nitrogen is available to plants in the form of nitrate or ammonium, which are transported into the cell with the aid of various transport proteins. Ammonium transporters (AMTs) play a role in the uptake of ammonium, the form in which N is preferentially absorbed by plants. Solanum tuberosum AMT1 (StAMT1) was amplified, sequenced and characterized using molecular biology and bioinformatics methods. Nucleotide database sequences were used to design 976 base pairs AMT1-specific primers which include forward primer 5’- GCCATCGCCGCCGCCGG-3’ and reverse primer 5’-GGGTCAGATCCATACCCGC-3’. These primers were used to amplify the Solanum tuberosum AMT1 internal regions. Nucleotide sequencing, alignment and phylogenetic analysis assigned StAMT1 to the AMT1 family due to the clade and high similarity it shared with other plant AMT1 genes. The deduced amino acid sequences showed that StAMT1 is 92%, 83% and 76% similar to Solanum lycopersicum LeAMT1.1, Lotus japonicus LjAMT1.1, and Solanum lycopersicum LeAMT1.2 respectively. StAMT1 fragments were shown to correspond to the 5th-10th trans-membrane domains. Residue StAMT1 D15 is predicted to be essential for ammonium transport, while mutations of StAMT1 S76A may further enhance ammonium transport.

Keywords: ammonium transporter, bioinformatics, nitrogen, primers, Solanum tuberosum

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Authors: Ananthakrishna L. R., Ramesh D., Kumar Wodeyar, Kotresh A. M., Gururaj P. M.

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Malnad Gidda is the indigenous recognized cattle breed of Shivamogga District of Karnataka state, India is known for its disease resistance to many of the infectious diseases. There are 25 LRR (Leucine Rich Repeats) identified in bovine (Bos indicus) TLR9. The amino acid sequence of LRR is deduced to nucleotide sequence in BLASTx bioinformatic online tools. LRR2 to LRR10 are involved in pathogen recognition and binding in human TLR9 which showed a higher degree of nucleotide variations with respect to disease resistance to various pathogens. Hence, primers were designed to amplify the flanking sequences of LRR2 to LRR10, to discover the nucleotide variations if any, in Malnad Gidda breed of Cattle which is associated with disease resistance. The DNA isolated from peripheral blood mononuclear cells of ten Malnad Gidda cattle. A desired and specific amplification product of 0.8 kb was obtained at an annealing temperature of 56.6ᵒC. All the PCR products were sequenced on both sides by gene-specific primers. The sequences were compared with TLR9 sequence of cross breed cattle obtained from NCBI data bank. The sequence analysis between Malnad Gidda and crossbreed cattle revealed no nucleotide variations in the region LRR2 to LRR9 which shows the conserved in pathogen binding domain (LRR) of TLR9.

Keywords: leucine rich repeats, Malnad Gidda, cross breed, TLR9

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Authors: Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević, Lidija R. Jevrić, Stela Jokić

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The subject of this paper is to correlate antibacterial behavior of benzimidazole derivatives with their molecular characteristics using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on the inhibitory activity of benzimidazole derivatives against Staphylococcus aureus. The data were processed by linear least squares (LLS) and artificial neural network (ANN) procedures. The LLS mathematical models have been developed as a calibration models for prediction of the inhibitory activity. The quality of the models was validated by leave one out (LOO) technique and by using external data set. High agreement between experimental and predicted inhibitory acivities indicated the good quality of the derived models. These results are part of the CMST COST Action No. CM1306 "Understanding Movement and Mechanism in Molecular Machines".

Keywords: Antibacterial, benzimidazoles, chemometric, QSAR.

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Authors: Cahit Demetgul, Sahin Bayraktar, Neslihan Beyazit

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Metalloenzymes are enzyme proteins containing metal ions, which are directly bound to the protein or to enzyme-bound nonprotein components. One of the major metalloenzymes that play a key role in oxidation reactions is catechol oxidase, which shows catecholase activity i.e. oxidation of a broad range of catechols to quinones through the four-electron reduction of molecular oxygen to water. Studies on the model compounds mimicking the catecholase activity are very useful and promising for the development of new, more efficient bioinspired catalysts, for in vitro oxidation reactions. In this study, a new tetradentate asymmetrical Schiff-base and its Cu(II) complex were synthesized by condensation of 4-nitro-1,2-phenylenediamine with 6-formyl-7-hydroxy-5-methoxy-2-methylbenzopyran-4-one and by using an appropriate Cu(II) salt, respectively. The prepared compounds were characterized by elemental analysis, FT-IR, NMR, UV-Vis and magnetic susceptibility. The catecholase-mimicking activity of the new Schiff Base Cu(II) complex was performed for the oxidation of 3,5-di-tert-butylcatechol (3,5-DTBC) in methanol at 25 °C, where the electronic spectra were recorded at different time intervals. The yield of the quinone (3,5-DTBQ) was determined from the measured absorbance at 400 nm of the resulting solution. The compatibility of catalytic reaction with Michaelis-Menten kinetics was also investigated. In conclusion, we have found that our new Schiff Base Cu(II) complex presents a significant capacity to catalyze the oxidation reaction of the catechol to o-quinone.

Keywords: catecholase activity, Michaelis-Menten kinetics, Schiff base, transition metals

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Authors: Babak Safaei, A. M. Fattahi

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Polymer/carbon nanotube nanocomposites have a wide range of promising applications Due to their enhanced properties. In this work, free vibration analysis of single-walled carbon nanotube-reinforced composite plates is conducted in which carbon nanotubes are embedded in an amorphous polyethylene. The rule of mixture based on various types of plate model namely classical plate theory (CLPT), first-order shear deformation theory (FSDT), and higher-order shear deformation theory (HSDT) was employed to obtain fundamental frequencies of the nanocomposite plates. Generalized differential quadrature (GDQ) method was used to discretize the governing differential equations along with the simply supported and clamped boundary conditions. The material properties of the nanocomposite plates were evaluated using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long-(10,10) SWCNT composites. Then the results obtained directly from MD simulations were fitted with those calculated by the rule of mixture to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results are presented to address the influences of nanotube volume fraction and edge supports on the value of fundamental frequency of carbon nanotube-reinforced composite plates corresponding to both long- and short-nanotube composites.

Keywords: nanocomposites, molecular dynamics simulation, free vibration, generalized, differential quadrature (GDQ) method

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Tan Yong Sheng Edgar, Yeong Wai Yee

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Age-related macular degeneration (AMD) is one of the leading cause of blindness. It can cause severe visual loss due to damaged retinal pigment epithelium (RPE). RPE is an important component of the retinal tissue. It functions as a transducing boundary for visual perception making it an essential factor for sight. The RPE also functions as a metabolically complex and functional cell layer that is responsible for the local homeostasis and maintenance of the extra photoreceptor environment. Thus one of the suggested method of treating such diseases would be regenerating these RPE cells. As such, we intend to grow these cells using a synthetic scaffold to provide a stable environment that reduces the batch effects found in natural scaffolds. Stiffness of the scaffold will also be investigated to determine the optimal Young’s modulus for cultivating these cells. The cells will be generated into a monolayer cell sheet and their functions such as formation of tight junctions and gene expression patterns will be assessed to evaluate the cell sheet quality compared to a native RPE tissue.

Keywords: RPE, scaffold, characterization, biomaterials, colloids and nanomedicine

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Authors: Nazanin Sheibanian, Raffaella Sesana, Sedat Ozbilen

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In recent years, high-entropy alloys (HEAs) have attracted considerable attention due to their unique properties and potential applications. In this study, novel HEA coatings were prepared on Mg substrates using mechanically alloyed HEA powder feedstocks based on Al_(0.1-0.5)CoCrCuFeNi and MnCoCrCuFeNi multi-material systems. The coatings were deposited by the Cold Spray (CS) process using three different temperatures of the process gas (N2) (650°C, 750°C, and 850°C) to examine the effect of gas temperature on coating properties. In this study, Infrared Thermography (non-destructive) was examined as a possible quality control technique for HEA coatings applied to magnesium substrates. Active Thermography was employed to characterize coating properties using the thermal response of the coating. Various HEA chemical compositions and deposition temperatures have been investigated. As a part of this study, a comprehensive macro and microstructural analysis of Cold Spray (CS) HEA coatings has been conducted using macrophotography, optical microscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM+EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), microhardness tests, roughness measurements, and porosity assessments. These analyses provided insight into phase identification, microstructure characterization, deposition, particle deformation behavior, bonding mechanisms, and identifying a possible relationship between physical properties and thermal responses. Based on the figures and tables, it is evident that the Maximum Relative Radiance (∆RMax) of each sample differs depending on both the chemical composition of HEA and the temperature at which Cold Spray is applied.

Keywords: active thermography, coating, cold spray, high- entropy alloy, material characterization

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Authors: Muhammad H. Alu’datt, Inteaz Alli

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This study was conducted to prepare and evaluate the biological properties of protein co-precipitates from flaxseed and soybean. Protein was prepared by NaOH extraction through the mixing of soybean flour (Sf) and flaxseed flour (Ff) or mixtures of soybean extract (Se) and flaxseed extract (Fe). The protein co-precipitates were precipitated by isoelectric (IEP) and isoelectric-heating (IEPH) co-precipitation techniques. Effects of extraction and co-precipitation techniques on co-precipitate yield were investigated. Native-PAGE, SDS-PAGE were used to study the molecular characterization. Content and antioxidant activity of extracted free and bound phenolic compounds were evaluated for protein co-precipitates. Removal of free and bound phenolic compounds from protein co-precipitates showed little effects on the electrophoretic behavior of the proteins or the protein subunits of protein co-precipitates. Results showed that he highest protein contents and yield were obtained in for Sf-Ff/IEP co-precipitate with values of 53.28 and 25.58% respectively as compared to protein isolates and other co-precipitates. Results revealed that the Sf-Ff/IEP showed a higher content of bound phenolic compounds (53.49% from total phenolic content) as compared to free phenolic compounds (46.51% from total phenolic content). Antioxidant activities of extracted bound phenolic compounds with and without heat treatment from Sf-Ff/IEHP were higher as compared to free phenolic compounds extracted from other protein co-precipitates (29.68 and 22.84%, respectively).

Keywords: antioxidant, phenol, protein co-precipitate, yield

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Authors: Ramandeep Kaur M. Malhi, Prashant K. Srivastava, G.Sandhya Kiran

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Quantitative estimates of foliar biochemicals, namely chlorophyll content (CC), serve as key information for the assessment of plant productivity, stress, and the availability of nutrients. This also plays a critical role in predicting the dynamic response of any vegetation to altering climate conditions. The advent of hyperspectral data with an enhanced number of available wavelengths has increased the possibility of acquiring improved information on CC. Retrieval of CC is extensively carried through well known spectral indices derived from hyperspectral data. In the present study, an attempt is made to develop hyperspectral indices by identifying optimum bands for CC estimation in Butea monosperma (Lam.) Taub growing in forests of Shoolpaneshwar Wildlife Sanctuary, Narmada district, Gujarat State, India. 196 narrow bands of EO-1 Hyperion images were screened, and the best optimum wavelength from blue, green, red, and near infrared (NIR) regions were identified based on the coefficient of determination (R²) between band reflectance and laboratory estimated CC. The identified optimum wavelengths were then employed for developing 12 hyperspectral indices. These spectral index values and CC values were then correlated to investigate the relation between laboratory measured CC and spectral indices. Band 15 of blue range and Band 22 of green range, Band 40 of the red region, and Band 79 of NIR region were found to be optimum bands for estimating CC. The optimum band based combinations on hyperspectral data proved to be the most effective indices for quantifying Butea CC with NDVI and TVI identified as the best (R² > 0.7, p < 0.01). The study demonstrated the significance of band characterization in the development of the best hyperspectral indices for the chlorophyll estimation, which can aid in monitoring the vitality of forests.

Keywords: band, characterization, chlorophyll, hyperspectral, indices

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Authors: S. Chandrasekaran, S. Nandita, M. Shivathmika, Srikrishnan Shivakumar

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The objective of the research work is to analyze the computational chemical-composition of carbohydrates in the context of healthcare informatics. The computation involves the representation of complex chemical molecular structure of carbohydrate using graph theory and in a deployable Chemical Markup Language (CML). The parallel molecular structure of the chemical molecules with or without other adulterants for the sake of business profit can be analyzed in terms of robustness and derivatization measures. The rural healthcare program should create awareness in malnutrition to reduce ill-effect of decomposition and help the consumers to know the level of such energy storage mixtures in a quantitative way. The earlier works were based on the empirical and wet data which can vary from time to time but cannot be made to reuse the results of mining. The work is carried out on the quantitative computational chemistry on carbohydrates to provide a safe and secure right to food act and its regulations.

Keywords: carbohydrates, chemical-composition, chemical markup, robustness, food safety

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Authors: S. Dargouthi, S. Boughdiri, B. Tangour

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This work invoked two complementary parts. In the first, we performed a theoretical study of various dimers of molecular of titanium dioxide. Five structures were examined. Three among them, the (T), (C) and (T/P) isomers, may be considered as stable compounds because they represent absolute minima on their potential energy surfaces. (T) and (C) may coexist because they are separted by only 6.5 kcal mol-1 but (T/P) dimer is in a metastable state from an energetic point of view. Non bonded dimer (P) transforms into its homologue (O) which has been considered as transitory specie with low lifetime which evolves to (T) structure. In the second part, we highlight the possible stabilization of (T), (C) and (P) dimers by encapsulation in carbon nanotubes. This indicates the probable role that plays this transitory specie the polymerization process of molecular TiO2. Confinement is suitable to control the fast evolution process and could towards the synthesis of new titanium dioxide nanostructured materials. An alternative description of TiO2 polymorphs (Rutie, anatase et Brookite) is proposed from (T), (C) and (T/P) dimmers motifs.

Keywords: titanium dioxide, carbon nanotube, confinement. encapsulation, transitory specie

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Authors: Hiroyuki Aoki

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The glass transition phenomenon has been extensively studied for a long time. The glass transition of polymer materials is assigned to the transition of the dynamics of the chain backbone segment. However, the detailed mechanism of the transition behavior of the segmental motion is still unclear. In the current work, the single molecule detection technique was employed to reveal the trajectory of the molecular motion of the single polymer chain. The center segment of poly(butyl methacrylate) chain was labeled by a perylenediimide dye molecule and observed by a highly sensitive fluorescence microscope in a defocus condition. The translational and rotational diffusion of the center segment in a single polymer chain was analyzed near the glass transition temperature. The direct observation of the individual polymer chains revealed the intermittent behavior of the segmental motion, indicating the spatial inhomogeneity.

Keywords: glass transition, molecular motion, polymer materials, single molecule

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Authors: Malalage Mudara Peiris

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Objectives of the study are: the biosynthesis of silver nanoparticles (AgNPs) using Escherichia coli, Acinetobacter baumannii and Staphylococcus aureus, characterization of silver nanoparticles and determination of antimicrobial activity against E. coli, P. aeruginosa, S. aureus, MRSA, and C. Albicans. Methods: E. coli (ATCC 25922), A. baumanii (clinical strain), S. aureus (clinical strain) cultured in nutrient broth medium were used for biosynthesis of AgNPs. Culture conditions (AgNO3 concentration, pH, incubation time and temperature) were optimized. Characterization of synthesized NPs was done by UV-Visible spectroscopy. The antimicrobial activity of the synthesized NPs was studied using the good diffusion assay against E. coli, S. aureus, MRSA (Methicillin-resistant Staphylococcus aureus), P. aeruginosa and C. Albicans. Results: All the selected bacteria produced silver nanoparticles at alkaline pH above 0.3 g/L AgNO3 concentration. The optimum reaction temperature was 60oC. According to the UV-Visible spectroscopy, the maximum absorbance was found to be around 420 - 430 nm indicating the presence of AgNPs. According to the good diffusion results, AgNPs produced by S. aureus resulted in the larger zone of inhibition (ZOI) against the selected pathogens, while AgNPs produced by E. coli showed comparatively smaller ZOI. In general, biosynthesized AgNPs were highly effective against gram-negative bacteria compared to gram-positive bacterial and fungal species. Conclusions: Green AgNPs produced by each bacterium show antimicrobial activity against the selected pathogens. AgNPs produced by S. aureus are the most effective NPs among tested AgNPs, while AgNPs produced by E. coli are the least effective. Further characterization of NPs is required to study the physical properties of silver NPs.

Keywords: green nanotechnology, silver nanoparticles, bacteria, antimicrobial activity

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Authors: S. Fröhlich, M. Herold, M. Allmer

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Early stage quantitative analysis of host cell protein (HCP) variations is challenging yet necessary for comprehensive bioprocess development. High resolution mass spectrometry (HRMS) provides a high-end technology for accurate identification alongside with quantitative information. Hereby we describe a flexible HRMS assay platform to quantify HCPs relevant in microbial expression systems such as E. Coli in both up and downstream development by means of MVDA tools. Cell pellets were lysed and proteins extracted, purified samples not further treated before applying the SMART tryptic digest kit. Peptides separation was optimized using an RP-UHPLC separation platform. HRMS-MSMS analysis was conducted on an Orbitrap Velos Elite applying CID. Quantification was performed label-free taking into account ionization properties and physicochemical peptide similarities. Results were analyzed using SIEVE 2.0 (Thermo Fisher Scientific) and SIMCA (Umetrics AG). The developed HRMS platform was applied to an E. Coli expression set with varying productivity and the corresponding downstream process. Selected HCPs were successfully quantified within the fmol range. Analysing HCP networks based on pattern analysis facilitated low level quantification and enhanced validity. This approach is of high relevance for high-throughput screening experiments during upstream development, e.g. for titer determination, dynamic HCP network analysis or product characterization. Considering the downstream purification process, physicochemical clustering of identified HCPs is of relevance to adjust buffer conditions accordingly. However, the technology provides an innovative approach for label-free MS based quantification relying on statistical pattern analysis and comparison. Absolute quantification based on physicochemical properties and peptide similarity score provides a technological approach without the need of sophisticated sample preparation strategies and is therefore proven to be straightforward, sensitive and highly reproducible in terms of product characterization.

Keywords: process analytical technology, mass spectrometry, process characterization, MVDA, pattern recognition

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Authors: Y. Hajjam, I. T. Alami, S. M. Udupa, S. Cherkaoui

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Faba bean (Vicia faba L.) is an important food legume crop in Morocco. It is mainly used as human food and feed for animals. Faba bean also plays an important role in cereal-based cropping systems, when rotated with cereals it improves soil fertility by fixing N2 in root nodules mediated by Rhizobium. Both faba bean and its biological nitrogen fixation symbiotic bacterium Rhizobium are affected by different stresses such as: salinity, drought, pH, heavy metal, and the uptake of inorganic phosphate compounds. Therefore, the aim of the present study was to evaluate the phenotypic diversity among the faba bean rhizobial isolates and to select the tolerant strains that can fix N2 under environmental constraints for inoculation particularly for affected soils, in order to enhance the productivity of faba bean and to improve soil fertility. Result have shown that 62% of isolates were fast growing with the ability of producing acids compounds , while 38% of isolates are slow growing with production of alkalins. Moreover, 42.5% of these isolates were able to solubilize inorganic phosphate Ca3(PO4)2 and the index of solubilization was ranged from 2.1 to 3.0. The resistance to extreme pH, temperature, water stress heavy metals and antibiotics lead us to classify rhizobial isolates into different clusters. Finally, the authentication test under greenhouse conditions showed that 55% of the rhizobial isolates could induce nodule formation on faba bean (Vicia faba L.) under greenhouse experiment. This phenotypic characterization may contribute to improve legumes and non legumes crops especially in affected soils and also to increase agronomic yield in the dry areas.

Keywords: rhizobia, vicia faba, phenotypic characterization, nodule formation, environmental constraints

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Authors: Balwinder Singh

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The present research is a paper on the characterization of aluminum alloy-6063 hybrid metal matrix composites using three different reinforcement materials (SiC, red mud, and fly ash) through stir casting method. The red mud was used in solid form, and particle size range varies between 103-150 µm. During this investigation, fly ash is received from Guru Nanak Dev Thermal Plant (GNDTP), Bathinda. The study has been done by using Taguchi’s L9 orthogonal array by taking fraction wt.% (SiC 5%, 7.5%, and 10% and Red Mud and Fly Ash 2%, 4%, and 6%) as input parameters with their respective levels. The study of the mechanical properties (tensile strength, impact strength, and microhardness) has been done by using Analysis of Variance (ANOVA) with the help of MINITAB 17 software. It is revealed that silicon carbide is the most significant parameter followed by red mud and fly ash affecting the mechanical properties, respectively. The fractured surface morphology of the composites using Field Emission Scanning Electron Microscope (FESEM) shows that there is a good mixing of reinforcement particles in the matrix. Energy-dispersive X-ray spectroscopy (EDS) was performed to know the presence of the phases of the reinforced material.

Keywords: reinforcement, silicon carbide, fly ash, red mud

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Authors: Javier Varillas, Jorge Alcalá

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We investigate dislocation avalanche phenomena in face-centered cubic (FCC) and body-centered cubic (BCC) crystals using massive, large-scale molecular dynamics (MD) simulations. The analysis is focused on the intermittent development of dense dislocation arrangements subjected to uniaxial tensile straining under displacement control. We employ a novel computational scheme that allows us to inject an entangled dislocation structure in periodic MD domains. We assess the emission of plastic bursts (or dislocation avalanches) in terms of the sharp stress drops detected in the stress-strain curve. The plastic activity corresponds to the sporadic operation of specific dislocation glide processes exhibiting quiescent periods between successive avalanche events. We find that the plastic intermittences in our simulations do not overlap in time under sufficiently low strain rates as dissipation operates faster than driving, where the dense dislocation networks evolve through the emission of dislocation avalanche events whose carried slip adheres to self-organized power-law distributions. These findings enable the extension of the slip distributions obtained from strict displacement-controlled micropillar compression experiments towards smaller values of slip size. Our results furnish further understanding upon the development of entangled dislocation networks in metal plasticity, including specific mechanisms of dislocation propagation and annihilation, along with the evolution of specific dislocation populations through dislocation density analyses.

Keywords: dislocations, intermittent plasticity, molecular dynamics, slip distributions

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Authors: Lavinia Ciungu

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In the last decades, developing algebras related to the logical foundations of quantum mechanics became a central topic of research. Generally known as quantum structures, these algebras serve as models for the formalism of quantum mechanics. In this work, we introduce the notion of quantum-Wajsberg algebras by redefining the quantum-MV algebras starting from involutive BE algebras. We give a characterization of quantum-Wajsberg algebras, investigate their properties, and show that, in general, quantum-Wajsberg algebras are not (commutative) quantum-B algebras. We also define the ∨-commutative quantum-Wajsberg algebras and study their properties. Furthermore, we prove that any Wajsberg algebra (bounded ∨-commutative BCK algebra) is a quantum-Wajsberg algebra, and we give a condition for a quantum-Wajsberg algebra to be a Wajsberg algebra. We prove that Wajsberg algebras are both quantum-Wajsberg algebras and commutative quantum-B algebras. We establish the connection between quantum-Wajsberg algebras and quantum-MV algebras, proving that the quantum-Wajsberg algebras are term equivalent to quantum-MV algebras. We show that, in general, the quantum-Wajsberg algebras are not commutative quantum-B algebras and if a quantum-Wajsberg algebra is self-distributive, then the corresponding quantum-MV algebra is an MV algebra. Our study could be a starting point for the development of other implicative counterparts of certain existing algebraic quantum structures.

Keywords: quantum-Wajsberg algebra, quantum-MV algebra, MV algebra, Wajsberg algebra, BE algebra, quantum-B algebra

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Authors: Md. Fazlul Karim, Ashik Sharfaraz, Aysha Ferdoushi

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Background: Computational medicinal chemistry approaches are used for designing and identifying new drug-like molecules, predicting properties and pharmacological activities, and optimizing lead compounds in drug development. SIRT7, a nicotinamide adenine dinucleotide (NAD+)-dependent deacylase which regulates aging, is an emerging target for cancer therapy with mounting evidence that SIRT7 downregulation plays important roles in reversing cancer phenotypes and suppressing tumor growth. Activation or altered expression of SIRT7 is associated with the progression and invasion of various cancers, including liver, breast, gastric, prostate, and non-small cell lung cancer. Objectives: The goal of this work was to identify potent and selective bioactive candidate inhibitors of SIRT7 by in silico screening of small molecule compounds obtained from Nigella sativa (N. sativa). Methods: SIRT7 structure was retrieved from The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), and its active site was identified using CASTp and metaPocket. Molecular docking simulation was performed with PyRx 0.8 virtual screening software. Drug-likeness properties were tested using SwissADME and pkCSM. In silico toxicity was evaluated by Osiris Property Explorer. Bioactivity was predicted by Molinspiration software. Antitumor activity was screened for Prediction of Activity Spectra for Substances (PASS) using Way2Drug web server. Molecular dynamics (MD) simulation was carried out by Desmond v3.6 package. Results: A total of 159 bioactive compounds from the N. Sativa were screened against the SIRT7 enzyme. Five bioactive compounds: chrysin (CID:5281607), pinocembrin (CID:68071), nigellidine (CID:136828302), nigellicine (CID:11402337), and epicatechin (CID:72276) were identified as potent SIRT7 anti-cancer candidates after docking score evaluation and applying Lipinski's Rule of Five. Finally, MD simulation identified Chrysin as the top SIRT7 anti-cancer candidate molecule. Conclusion: Chrysin, which shows a potential inhibitory effect against SIRT7, can act as a possible anti-cancer drug candidate. This inhibitor warrants further evaluation to check its pharmacokinetics and pharmacodynamics properties both in vitro and in vivo.

Keywords: SIRT7, antitumor, molecular docking, molecular dynamics simulation

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Authors: Chul Lee, Seoae Cho, Erich D. Jarvis, Heebal Kim

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Vocal learning, the ability to imitate vocalizations based on auditory experience, is a homoplastic character state observed in different independent lineages of animals such as songbirds, parrots, hummingbirds and human. It has now become possible to perform genome-wide molecular analyses across vocal learners and vocal non-learners with the recent expansion of avian genome data. It was analyzed the whole genomes of human and 48 avian species including those belonging to the three avian vocal learning lineages, to determine if behavior and neural convergence are associated with molecular convergence in divergent species of vocal learners. Analyses of 8295 orthologous genes across bird species revealed 141 genes with amino acid substitutions specific to vocal learners. Out of these, 25 genes have vocal learner specific genetic homoplasies, and their functions were enriched for learning. Several sites in these genes are estimated under convergent evolution and positive selection. A potential role for a subset of these genes in vocal learning was supported by associations with gene expression profiles in vocal learning brain regions of songbirds and human disease that cause language dysfunctions. The key candidate gene with multiple independent lines of the evidences specific to vocal learners was DRD5. Our findings suggest cAMP-based learning pathway in avian vocal learners, indicating molecular homoplastic changes associated with a complex behavioral trait, vocal learning.

Keywords: amino acid substitutions, convergent evolution, positive selection, vocal learning

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Authors: Bahattin Abay

Abstract:

Thin film of polycyclic aromatic hydrocarbon rubrene, C₄₂H₂₈ (5,6,11,12-tetraphenyltetracene), has been surfaced on Moderately Doped (MD) n-InP substrate as an interfacial layer by means of spin coating technique for the electronic modification of Au/MD n-InP structure. Ex situ annealing has been carried out at 150 °C for three minutes under a brisk flow of nitrogen for the better adhesion of the deposited film with the substrate surface. Room temperature electrical characterization has been performed on the C₄₂H₂₈/MD n-InP hybrid junctions by current-voltage (I-V) and capacitance-voltage (C-V) measurement in the dark. It has been seen that the C₄₂H₂₈/MD n-InP structure demonstrated extraordinary rectifying behavior. An effective barrier height (BH) as high as 0.743 eV, along with an ideality factor very close to unity (n=1.203), has been achieved for C₄₂H₂₈/n-InP organic/inorganic device. A thin C₄₂H₂₈ interfacial layer between Au and MD n-InP also reduce the reverse leakage current by almost four orders of magnitude and enhance the BH about 0.278 eV. This good performance of the device is ascribed to the passivation effect of organic interfacial layer between Au and n-InP. By using C-V measurement, in addition, the value of BH of the C₄₂H₂₈/n-InP organic/inorganic hybrid junctions have been obtained as 0.796 eV. It has been seen that both of the BH value (0.743 and 0.796 eV) for the organic/inorganic hybrid junction obtained I-V and C-V measurement, respectively are significantly larger than that of the conventional Au/n-InP structure (0.465 and 0.503 eV). It was also seen that the device had good sensitivity to the light under 100 mW/cm² illumination conditions. The obtained results indicated that modification of the interfacial potential barrier for Metal/n-InP junctions might be attained using polycyclic aromatic hydrocarbon thin interlayer C₄₂H₂₈.

Keywords: I-V and C-V measurements, heterojunction, n-InP, rubrene, surface passivation

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Authors: Siti Rafeah Md Rafei, Karen Wang Yanping, Park Mi Kyoung

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Tissue samples are precious supply for molecular studies or disease identification diagnosed using molecular assays, namely real-time PCR (qPCR). It is critical to establish the most favorable nucleic acid extraction that gives the PCR-amplifiable genomic DNA. Furthermore, automated nucleic acid extraction is an appealing alternative to labor-intensive manual methods. Operational complexity, defined as the number of steps required to obtain an extracted sample, is one of the criteria in the comparison. Here we are comparing the One BioMed’s automated X8 platform with the commercially available manual-operated kits from QIAGEN Mini Kit and Roche. We extracted DNA from rat fresh-frozen tissue (from different type of organs) in the matrices. After tissue pre-treatment, it is added to the One BioMed’s X8 pre-filled cartridge, and the QIAGEN QIAmp column respectively. We found that the results after subjecting the eluates to the Real Time PCR using BIORAD CFX are comparable.

Keywords: DNA extraction, frozen tissue, PCR, qPCR, rat

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Authors: Rungsinee Sothornvit, Pattrathip Rodsamran

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Rice stubble consists of a high content of cellulose and can be synthesized as a cellulose derivative such as carboxymethyl cellulose (CMC) to value added products from agricultural waste. Therefore, the synthesis conditions and characterization the properties of CMC from rice stubble (CMCr) were investigated. Hemicellulose and lignin were first removed from the rice stubble using 10% NaOH at 55 C for 3 h and 5% NaOCl at 75 C for 15 min, respectively. Rice stubble cellulose was swollen in 30% NaOH and isopropanol as a solvent. The content of chloroacetic acid (5–7 g in 5 g of alkali cellulose), reaction temperature (50 and 70 C) and time (180, 270 and 360 min) were explored to obtain CMC. It was found that synthesis conditions did not affect significantly on moisture content and pH of CMCr. The best quality of CMCr was synthesized by using 7 g of chloroacetic acid and reacted at 50 C for 180 min based on 5 g of rice stubble cellulose. Degree of substitution (DS), viscosity and purity of CMCr were 0.64, 36.03 cP and 90.18 %, respectively. Furthermore, Fourier transform infrared (FT–IR) spectroscopy confirmed the presence of carboxymethyl substituents. CMCr was categorized in commercial scale as a low viscosity material and it can be used as film forming packaging materials for food and pharmaceutical product applications.

Keywords: rice stubble, cellulose, carboxymethyl cellulose, degree of substitution, purity

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Authors: Samira B. R. Prado, Paulo R. Melfi, Beatriz T. Minguzzi, João P. Fabi

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Fruit softening is the main change that occurs during papaya (Carica papaya L.) ripening. It is characterized by the depolymerization of cell wall polysaccharides, especially the pectic fractions, which causes cell wall disassembling. However, it is uncertain how the modification of the two main pectin polysaccharides fractions (water-soluble – WSF, and oxalate-soluble fractions - OSF) accounts for fruit softening. The aim of this work was to correlate molecular weight changes of WSF and OSF with the gene expression of pectin-solubilizing enzymes (pectinases) during papaya ripening. Papaya fruits obtained from a producer were harvest and storage under specific conditions. The fruits were divided in five groups according to days after harvesting. Cell walls from all groups of papaya pulp were isolated and fractionated (WSF and OSF). Expression profiles of pectinase genes were achieved according to the MIQE guidelines (Minimum Information for publication of Quantitative real-time PCR Experiments). The results showed an increased yield and a decreased molecular weight throughout ripening for WSF and OSF. Gene expression data support that papaya softening is achieved by polygalacturonases (PGs) up-regulation, in which their actions might have been facilitated by the constant action of pectinesterases (PMEs). Moreover, BGAL1 gene was up-regulated during ripening with a simultaneous galactose release, suggesting that galactosidases (GALs) could also account for pulp softening. The data suggest that a solubilization of galacturonans and a depolymerization of cell wall components were caused mainly by the action of PGs and GALs.

Keywords: carica papaya, fruit ripening, galactosidases, plant cell wall, polygalacturonases

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Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

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Authors: Qi Wu, Dian-Yong Chen, Feng-Kun Guo, Gang Li

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In the past decade, a growing number of new hadron states have been observed, which are dubbed as XYZ states in the heavy quarkonium mass regions. In this work, we present our study on the production of some new hadron states. In particular, we investigate the processes Υ(5S,6S)→ Zb (10610)/Zb (10650)π, Bc→ Zc (3900)/Zc (4020)π and Λb→ Pc (4312)/Pc (4440)/Pc (4457)K. (1) For the production of Zb (10610)/Zb (10650) from Υ(5S,6S) decay, two types of bottom-meson loops were discussed within a nonrelativistic effective field theory. We found that the loop contributions with all intermediate states being the S-wave ground state bottom mesons are negligible, while the loops with one bottom meson being the broad B₀* or B₁' resonance could provide the dominant contributions to the Υ(5S)→ Zb⁽'⁾ π. (2) For the production of Zc (3900)/Zc (4020) from Bc decay, the branching ratios of Bc⁺→ Z (3900)⁺ π⁰ and Bc⁺→ Zc (4020)⁺ π⁰ are estimated to be of order of 10⁽⁻⁴⁾ and 10⁽⁻⁷⁾ in an effective Lagrangian approach. The large production rate of Zc (3900) could provide an important source of the production of Zc (3900) from the semi-exclusive decay of b-flavored hadrons reported by D0 Collaboration, which can be tested by the exclusive measurements in LHCb. (3) For the production of Pc (4312), Pc (4440) and Pc (4457) from Λb decay, the ratio of the branching fraction of Λb→ Pc K was predicted in a molecular scenario by using an effective Lagrangian approach, which is weakly dependent on our model parameter. We also find the ratios of the productions of the branching fractions of Λb→ Pc K and Pc→ J/ψ p can be well interpreted in the molecular scenario. Moreover, the estimated branching fractions of Λb→ Pc K are of order 10⁽⁻⁶⁾, which could be tested by further measurements in LHCb Collaboration.

Keywords: effective Lagrangian approach, hadron loops, molecular states, new hadron states

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